Tag Archives: photogrammetry

Using existing mapping data to control UAV mapping flights – Part 1 – Preliminary Ideas and Experimentation

An intrinsic problem with photogrammetry is its requirement to keep the camera facing the subject matter. A much higher quality and more accurate 3D model is produced using the method than taking photographs at an oblique angle. This is especially true of buildings with with flat facades, (this has already been discussed in another blog).

Work has been done using computer vision to automate the control of the camera position so that it follows targets selected by the pilot. Although this has potential for some recording methods such as site tours, as discussed in another blog, it doesn’t aid in the recording of complex topography or architecture. Although there is potential for the recording of architectural elements using computer vision  technologies (this will be discussed in a later blog).

Other work is being done in using a low detail 3D model of a building to aid in the control of a UAV flying around it, but these are more aimed at collision avoidance than quality recording.

While in the future i plan to look at the potential pre-scanning a building with an aerial LiDAR scanner mounted on a drone before recording with UAV.

Potential solution

The camera gimbal of a UAV can be controlled both remotely and from the autopilot of the UAV which could be used to always keep the camera facing the subject matter, but without pertinent information this would have to be done manually. With wireless camera technology it is possible to remotely view what the camera is recording and so control the movement of the gimbal when required, but this would require a second person to control the camera while the UAV is being flown and would be difficult to implement effectively and costly in a commercial environment.

But it would seem to be possible to use existing 3D data of an area to control the flight of a UAV; both controlling the altitude and the angle that the camera gimbal is pointing. I have already discussed the use of DroneKit Python to create a UAV mapping flight, thish can also be used to control the angle of the camera gimbal.

Existing Data

There are a number of existing sources of data that can be used to aid in creating a mapping flight.

Within the UK LiDAR data is freely available at different spatial resolutions, much of the country is available down to 1m while other areas are available down to 0.25 m.

This resource through processing in GIS (Geographic Information System) software provides all of the information required to create a flight path over the area under study and to control the angle of the camera gimbal so that it will record it to a higher quality than before.

A digital elevation model (DEM) created using photogrammetry from existing overlapping aerial photographs can also be employed once it is georeferenced to its correct location. This resource may provide a higher spatial resolution than the LiDAR data and so a better resource for the creation of the flight path, but the landscape and structures may have changed since the photographs were taken causing problems (this can of course be a problem with the LiDAR data as well).

Co-ordinate system problems

One complication with using LiDAR data to control the UAV is the fact that it is in a different co-ordinate system than the GPS of the UAV (OSGB and WGS84). This can be solved be translating one set of data to the co-ordinate system of the other. As the number of points for the mission path will be a lot less than that for the LiDAR data it would make sense to convert the GPS data to OSGB, but this also requires that it be converted back after the flight path has been created added a certain amount of inaccuracy into the data as a conversion is never 100% accurate.

required Data

Three different pieces of data need to be derived from the LiDAR data which are required for the UAV mapping flight:

  • Altitude.
  • Slope.
  • Aspect.

The Altitude is contained within each point of the LiDAR data and is used when displaying the data in GIS software.

The Slope of the topography/buildings is measure in increments up to 90 degrees, with o degrees being flat and 90 degrees being a vertical face.

The Aspect is which way any slope is pointing in is measured in increments from 1-360 degrees. (degrees).

 

Slope_angles

Slope angles

Although it would be possible to create software that extracts the data from the LiDAR file while creating a flight path this is not currently an option. The flight path is currently created in a piece of software such as the Open Source ‘Mission Planner’ system. In this an area is chosen together with other variables and an optimal flight path is created. This flight path file can then be saved, it contains the X and Y co-ordinates of each point of the mission.

UAV Control

At its simplest the flight path can be created with the altitude and slope derived from the LiDAR being used to control both the UAV altitude and camera gimbal angle. This would work well for sloping topography but would be more complicated for areas with sharp breaks in slope (such as buildings).

Altitude Control

The altitude will need to be carefully controlled to make sure that the quality of the imaginary is consistent across the whole area under study. At its simplest this is easy to do using the altitude data within the LiDAR data, together with obstacle avoidance sensors to aid with safety.

The problem arises when needing to record something near or completely vertical. Rather than requiring a set altitude the UAV needs to maintain a set distance horizontally. This may be possible by creating a buffer in the data around steeply sloping areas.

Drone_flight_path

Problem with vertical offset

Camera Gimbal Control

Most low cost UAV systems come with a 2-axis gimbals, this means that the camera is stabilized so that it always stays in a horizontal plane but also that its rotation can be controlled downwards.

Gimbal_angle

The angle of the gimbal begins at 0 degrees for a forward pointing position to 90 degrees for a downwards facing position. This is how is its controlled within DroneKit.

As seen earlier the slope is calculated between 0 and 90 degrees for a slope.

There are two intrinsic problems with this method:

  1. The slope only goes between 0 and 90 degrees so there is no aspect data within it. If the drone camera is to be controlled to record the building as it flies over if needs to know which way the building is pointing as the 45 degrees on the left is not the same as the 45 degrees on the right. This could be solved by combining the information from the slope and aspect to give more detailed resulting data.
  2. Most standard gimbals are designed to only point forwards and downwards. This means that the UAV has to turn around to record the back side of the building or it needs to fly the path in reverse. The other solution is to use a UAV with a camera that can point in 360 degrees.

GIS Processing

A certain amount of processing is required within GIS software to get the required data from the LiDAR data and combine it with the required mapping flight path. For this ArcGIS has been used both due to its availability at university and my own familiarity with it.

Lidar

Considering the LiDAR data is for a specific square it makes sense to use raster data rather than the points and lines of vector data as it retains the accuracy of the data. The LiDAR data can be simply loaded into the GIS software as a raster.

Within GIS software the Aspect and Slope can be calculated and a raster created showing the results.

This can be done using the Spatial Analyst or 3D Analyst Toolboxes to provide Slope and Aspect rasters.

The data for these can be incorporated into Attribute Tables which can be exported into text files. It is possible to combine all of the data into one attribute table containing the Altitude, Slope and Aspect.

Although it is possible to export this whole raster file including all of the data it is not currently possible to automatically derive the data in software using the flight path, so a flight path has to be loaded into the GIS software.

Flight Path

The flight path file we created in the Mission Planner software needs to be loaded into a feature class in the GIS software. This can be done by loading the point data for the flight path into the software, this is the beginning and end point for each of the back and forth paths across the area needed to be recorded.

We next need to recreate the flight path using ‘point to line’.

Even though we have recreated the lines, deriving enough data from them is not possible as the flight path is designed to fly back and forth at a set altitude. For this reason we need to create a number of extra points. This can be done using ‘Construct points’ where points can be created at set intervals along a line. This can be linked to the level of data that is being used, so for this LiDAR data the points can be set at intervals of 1m.

Once this his has been done ‘Extract multi-values to points’ can be run on the 3 sets of data to create a table containing all of the required data for each point on the flight path we have created.

UAV Mission Creation

Now that we have all of the required input data for the UAV mapping flight we need to create the mission within Dronekit Python.

For the first level of experimentation we can just load the point data file into python then create a number of points for the UAV to fly to which give the X and Y co-ordinates and the required altitude. At the same time we can also program in the angle for the camera gimbal. It may be best to have the UAV hover at the positions for a second or two so that we know how the recording is going.

As already mentioned if we are only using a 2-axis gimbal we are going to have to have the UAV turn through 180 degrees to record the back sides of buildings and slopes sloping away from the camera. We should be able to do this by altering the UAV Yaw. We will need to have the Python read the aspect angle and change how it creates the flight path depending on the aspect of the slope/building.

Future Directions

ArcGIS allows the use of Python to run tools in its toolbox so it seems possible to create a python script which would automatically create a file with all of the information required from input files of LiDAR data and a flight path.

As QGIS also allows the use of python it would also seem possible to create the required file within this open-source solution.

 

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UAV Building Facade Recording – Part 1 – Preliminary Ideas and Experimentation

The recording of buildings is an important area in Cultural Heritage, whether for conditional surveys or to record something that is about to be destroyed.

Traditional methods rely upon survey equipment such as Total Stations to take a number of points on the façade, but this results in only points and lines with no great surface detail.

Other more detailed survey techniques such as laser scanning and photogrammetry have also been employed. But laser scanning is expensive and both the techniques are generally ground based missing detail of the façade that is not visible from this position. Scaffolding or a cherry picker can be used to record the whole of the building but again this can add to the cost the recording.

Photogrammetry is a low cost method of producing high quality results but relies upon having the camera parallel to the building to produce the best results, as capturing photographs from an angle brings inaccuracies into the recording as well as there being more detail at the bottom of the 3D model created than at the top.

The UAV would seem to provide an ideal platform to carry a camera parallel to the building, recording photographs with the required photogrammetry overlap. And with its autopilot it would seem possible to automate the recording process allowing the mapping of the façade in the same way that the UAV  can map the ground.

There are of course a number of problems that need to be overcome.

Building Façade Recording

Manual

Building façade recording can be done manually with a UAV, but the larger and more complicated the building façade the mode difficult it is to do this accurately. As the pilot needs to control the UAV accurately in 3 dimensions as well as controlling its speed.

Although the results for an experimental UAV mission are acceptable the difficulty of maintaining a manual position can be seen in the image below.

Automatic

In order to automate the process you need to determine what parameters are required to record a building façade using photogrammetry.

These can be seen below.

Excel Calculations

Building facade recording parameters

First experimentation was done by taking the co-ordinates of the two ends of an example the wall from Google Earth (The south facing wall of the lay brothers’ quarters at Waverley Abbey in Surrey was used). These co-ordinates can then be used to determine the bearing that the wall lies upon and its width. Using the camera parameters and level of detail the required distance from the wall for the flight can be calculated using trigonometry. Trigonometry is once again used to calculate the offset positions for the left and right extent of the flight.

 

The image overlap can be used to determine the number of photographs required in the horizontal and vertical, and hence the change of altitude that is required for each flight pass of the building.

Calculate altitude changes

Calculate altitude

Although it is planned to have the ability for the UAV to hover and take photographs, it is much easier to have it take photographs as it flies across the building façade. This requires the additional calculations and control of optimum flight speed and shutter speed to take photographs which are not adversely effected by motion blur.

Shutter speed formula

Shutter speed formula

Shutter speed calculions

Shutter speed calculations

These preliminary calculations were done in Microsoft Excel.

DroneKit

The drone manufacturer 3DR provides a series of software development kits (SDKs) for writing applications to control your UAV using one of the open-source autopilot systems they support.

DroneKit Python uses the Python programming language and provides a number of examples to help with programming the flight of a UAV; these include flying from co-ordinate to co-ordinate up to complete missions. Together with this there is an API (application program interface) reference which provides all of the Python commands that can be used to control the UAV.

Python

Python is a fairly easy to learn programming language and as DroneKit already requires it to be installed and setup it makes sense to use the same language to calcuate the required paramaters for the flight path. This was done with the aid of a number of online resources. A graphical user interface (GUI) was created using the Tkinter Python package and was used to enter the data. The python code did the calculations then a file is exported which combines these calculations with the DroneKit code for controlling the autopilot. The final file when run will control the UAV flight.

Python GUI

Python GUI

Virtual Drone

Experimentation doesn’t need to be done with a live UAV, it can actually be done with a virtual one using a number of pieces of open-source software. These include Mission  Planner, ArduCopterMAVProxy and SITL (Software in the loop)

Virtual Drone

Virtual Drone

Next Steps

Experimentation with a UAV using the hardware and software is the next step to test whether a GPS can be used in close proximity to a structure.

Limitations of standard UAV GPS accuracy to within the range of meters also complicates the use of this method of controlling the flight. This either needs to be solved with the use of a more accurate GPS (although the proximity to the building may block the signal), sensors that measure distances or the use of computer vision technologies to control the UAV position. The UAV afterall currently only need to fly between two set points then at set altitudes above the ground.

High Dynamic Range Photography/Photogrammetry – Part 1

High Dynamic Range (HDR) Photography

High Dynamic Range is a popular photographic technique that is used to produce more realistic photographic results or artistic images. It is a technique that can be used to try and replicate what the human eye can see as the dynamic range of a camera is limited and it is unable to record the lightest and darkest elements in a single photograph. This can be remedied by taking a number of photographs with varying shutter speed/aperture combinations and combining them using specialist software to produce a photograph with a greater dynamic range than can be recorded in a single photograph.

Many new digital cameras have the ability to produce HDR photographs using Auto Exposure Bracketing (AEB), special HDR settings (this may process the images for you resulting in an HDR photo on the camera but losing the originals) or manually setting the camera up.

Limitations of archaeological and cultural heritage photography

An intrinsic problem with taking photographs in archaeological and cultural heritage contexts is lighting; both too much and too little lighting are factors that hamper recording images that include as much detail as possible.

In the case of archaeological excavations attempts have been made to limit the problems in section photography by either reflecting more light in using white card or using a tarpaulin to cast a shadow. Both of these techniques work but require time and manpower.

The same problem is encountered in building recording where in an outside environment strong lighting can cause both bleached out areas and heavy shadows.

Netley Abbey - East Window

Netley Abbey, Hampshire – East Window. Photograph demonstrating the problem of strong oblique lighting causing both too much and too little light in the same image.

While lighting through windows can cause similar problems on the inside of buildings.

Netley Abbey, Hampshire - Sacristy/Library.

Netley Abbey, Hampshire – Sacristy/Library. Photograph demonstrating the effect of excessive light coming through a window causing the dual problems of both too much light near to the window and too little light in other areas.

In order to reveal elements in dark shadow a high exposure camera setting is required, while bright bleached out areas are only revealed with low exposures. These elements together with well lit areas cannot by revealed in one single photograph, this is where High Dynamic Range photography comes in.

HDR Photography in Archaeology

HDR Photography was introduced to Archaeology by David Wheatley in 2010, he provided examples of its use in improving the standard recording methods of excavations, cave sites and even using archived analogue archaeological photographs. Sadly its use was not embraced by the community probably due to technological limitations at the time and the inherent conservatism of the industry and museum archives which were yet to embrace digital photographic technology. Technology and the industry have now caught up with his ideas, with digital cameras being present on most if not all excavations, while other scholars have now begun to bring the technology to the technique of 3D recording using photogrammetry.

HDR Field Archaeology Photography

Photography is one of the primary recording techniques within field archaeology and has been since the introduction of discipline, but conservatism within field archaeology has meant that it was only fairly recently that digital photography became the primary recording technology.

Digital cameras have a number of benefits within archaeology:

  • The ability to take numerous photographs on one memory card.
  • No need to pay to process films.
  • No need to digitize the photographs.
  • Where once excavators may have been told to limit the number of photographs taken on an excavation to keep the processing costs down, digital media allows almost limitless photographs to be taken.
  • Photographs can be as easy as point and click with the camera controlling all of the settings.

But they also have drawbacks:

  • Where once archaeologists knew how to use an analogue camera to take bracketed shots, the automatic setting on digital cameras is commonly the only setting used as it produces results at a required level of quality, this means that the archaeologist may not know how to properly operate the camera.
  • Although almost limitless photographs can be taken, limits should be included as the archive may still need to be sorted through.
  • The requirements for digital storage can be complicated and costly.

Although not ideal, a number of modern cameras now come with an HDR setting on them which in many cases can be changed to the required level of bracketing, although only the merged photograph is saved losing the possibility of later re-processing the photographs with different settings.

Field Archaeology Archive Photographs

One benefit of traditional bracketing of analogue photographs for archaeological excavations is that they provide an ideal resource for conducting HDR processing. These archives have multiple photographs at different exposure levels which can be digitized and processed to provide better results than the originals and be re-entered into the archive with the digitized originals.

HDR using archive slides from excavations at the Cove, Avebury using archive slides (Wheatley 2010)

HDR using archive slides from excavations at the Cove, Avebury (Wheatley 2010)

HDR Building Photography

Building recording is an area that can be significantly enhanced by the use of HDR. It is difficult to provide adequate lighting in many cases, meaning that some areas are brightly illuminated while others are dimly lit loosing information in both cases.

Processing bracketed images into an HDR image provides a greatly enhanced image.

HDR Photogrammetry

Recent developments in camera technology, HDR software and photogrammetry software have allowed the introduction of HDR Photogrammetry. Thanks to the additional information present in the photographs models of higher detail and accuracy can be created in non-optimal lighting conditions.

As well as the ability to use tone mapped images produced from HDR images the Agisoft PhotoScan Photogrammetry software can also process .exr file format High Dynamic Range images into 3D models.

HDR Object Photogrammetry

One area under study is its use in photographing objects. The benefits are determined by the type of material used, some are greatly enhanced by HDR while others are little altered.

Image matching result from the images originated with different HDR processing: a) No HDR; b) tone mapped images from HDR processing (Guidi et al 2014)

Image matching result from the images originated
with different HDR processing: a) No HDR; b) tone mapped
images from HDR processing (Guidi et al 2014)

HDR Building Photogrammetry

We have already seen the benefits of HDR Photography in building recording and this can continue with photogrammetry.

Netley-Window-PG

Photogrammetry point cloud of the east window of Netley Abbey, Hampshire showing how the raking sunlight on the left-hand side of the window has bleached out the photographs and lost detail

Both the increased level of quality of the photograph and the higher amount of detail present in the 3D model can easily be seen in the HDR photogrammetry model.

Software Solutions

A number of software solutions are available for the processing of HDR photographs, these range from high end photographic software such as Adobe Photoshop and Lightroom, through to HDR specific pieces of software and even open source solutions. HDRSoft’s Photomatrix comes in a number of versions which include plugins for different software packages such as Adobe Lightroom, Photoshop Elements, Photoshop and Apple Aperture. With low cost solutions such as Fusion HDR or free open-source solutions such as LuminanceHDR also being available.

In order to be view-able on low contrast monitors and paper the images need to go through a process called tone mapping, this replicates the appearance of the high dynamic range photograph on these media.

Downloaded imaged can be batch processed in software such as Photomatrix setting up how many images need to be merged together with a number of preset or custom settings allowing the images to be processed exactly as required. These pieces of software can also compensate for slight movement between the recording of the multiple images. The resulting images can then be saved as either .hdr (Radiance) or .exr (OpenEXR) file formats which record the HDR information.

Batch processing of images within Photomatrix

Batch processing of images within Photomatrix

Benefits
HDR photography can record more information in both photographs and photogrammetry models. By using open Source HDR software it can be free. Many cameras allow multiple bracketed photographs to be be taken automatically only adding a few seconds to the recording process.

It is also possible in some of the software to open a folder full of images and have the software batch process it without any user intervention once the preset settings have been loaded.

Drawbacks
Among the drawbacks are the fact that as the camera is taking multiple photographs it is difficult to stabilize the camera by hand, otherwise there will be movement between the photographs. Although movement between photographs can be corrected if you are bracketing shots and using software the automatic HDR setting on the camera will probably result in a blurry image.

UAV HDR Photogrammetry

UAV HDR Photogrammetry is an area I will be studying in the future. It has great potential for recording but will require a careful balance of UAV hovering, a steady gimbal, fast shutter speed and an adequate depth of field. It will be discussed in a future blog.

Sources
Guidi, G., S. Gonizzi, and L. L. Micoli. “Image pre-processing for optimizing automated photogrammetry performances.” ISPRS Annals of The Photogrammetry, Remote Sensing and Spatial Information Sciences 2.5 (2014): 145-152.

Kontogianni, G., and A. Georgopoulos. “Investigating the effect of HDR images for the 3D documentation of cultural heritage.” World Cultural Heritage Conference 2014 – Euromed 2014 – International Conference on Cultural Heritage Documentation, Preservation and Protection. (2014)

Ntregkaa, A., A. Georgopoulosa, and M. Santana Quinterob. “Photogrammetric Exploitation of HDR Images for Cultural Heritage Documentation.” ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences 5 (2013): W1.

Wheatley, D. “High dynamic range imaging for archaeological recording.” Journal of Archaeological Method and Theory 18, no. 3 (2011): 256-271.

Mirror-less Cameras and UAVs

UAV (Unmanned Aerial Vehicle) photography and photogrammetry has long been a balance between weight and the quality of the camera equipment carried.

Cameras

Low cost camera solutions such as the GoPro can be carried on almost all UAVs because they are small and lightweight, but these benefits are also drawbacks because limited size/fish eye lenses and small image sensors reduce the quality of the photographs they take, together with this the lack of control of many of the camera settings is a drawback.

High quality DSLR (Digital Single Lens Reflex) cameras have superior quality lenses and image sensors together with the fact that they have extensive control of the camera settings meaning that they take much better photographs. But they can only be carried by much higher power/cost octo and hexo-copter systems.

One solution is the lightweight point-and-shoot camera/compact camera used in some mapping solutions, such as those provided by 3DRobotics (Canon PowerShot S100). Although these cameras provide a better quality solution than the GoPro, and may be all that is required for mapping exercises; they are still limited in their optics and higher megapixel sensors which are much more important in the recording of complicated structures and photogrammetry work.

Changes in the camera industry due to competition from the phone industry has enhanced development of a different solution. This is the MILC (Mirrorless Interchangeable-lens camera) or DSLM (Digital Single Lens Mirrorless) Camera. These cameras don’t have the mirror reflex optical viewfinder of a DSLR camera, and the associated weight, replacing it with a LCD screen or with an app on a mobile device which controls the camera. As a result they have the capability to carry high quality interchangeable lenses without the weight associated with DSLR cameras. The system comes in two different forms; the first resembles a standard digital SLR camera, while the second resembles just a lens with all control being provided by an app on a mobile device.

Camera Comparison
Camera Type Megapixel Weight Cost
Canon EOS 5D Mark III Digital SLR 22.3 Approx 950g £2,544
Nikon D5300 Digital SLR 24.2 Approx 840g £549.99
Sony A5000 DSLM Digital SLM 20.1 Approx 388g £250
Sony ILCE-QX1 Lens Style Camera 20.1 Approx 332g £250
Canon PowerShot S100 Compact Camera 12.1 Approx 198g £195
GoPro Hero3+ Black Sports Camera 12 74/136g (with housing) £349.99
Canon EOS 5D Mark III

Canon EOS 5D Mark III

Nikon D5300

Nikon D5300

α5000 E-mount Camera

α5000 E-mount Camera

ILCE-QX1 Lens-Style Camera

ILCE-QX1 Lens-Style Camera

3DRobotics UAV Mapping Solutions, discussed in another blog entry, carry the Canon PowerShot S100 digital compact camera.

Canon PowerShot S100

Canon PowerShot S100

GoPro Hero3+ Black

GoPro Hero3+ Black

UAVs

UAVs come in a number of different configurations and increase in price with a higher level of complexity and ability to carry heavier loads.

UAV Comparison
UAV Type Payload Capacity Price (Without Gimbal)
3D Robotics Iris+ Quadcopter 400g £599
3D Robotics X8+ Octocopter 800g – 1Kg with reduced flight time £880
Spreading Wings S900 Hexacopter 4.7 – 8.2Kg £1,291-£1,540
DJI Spreading Wings S1000+ Octocopter 11Kg £1,750-£2,057
3D Robotics Iris+ Quadcopter

3D Robotics Iris+ Quadcopter

3D Robotics X8+ octocopter

3D Robotics X8+ Octocopter

Gimbals

Gimabls are an important element in stabilizing cameras during photography and video recording, as well as providing a motorized solution to move the camera to a desired angle during flight. They can add significantly to both the weight and price of any UAV solution depending on the camera equipment they are carrying.

Gimbal Price Comparison
Gimbal Camera Weight (Camera excluded) Cost
DJI Zenmuse H4-3D GoPro 168g £249
DYS 3 axis brushless gimbal Sony NEX size camera 388g £231.95 – £299.94
DJI Zenmuse Z15-A7 Sony α7s and α7r 1.3Kg £1,915
DJI Zenmuse Z15-5D III (HD) Canon EOS 5D DSLR 1.53Kg £2,831

Solutions

The 3DRobotics Iris+ Quadcopter has a payload capacity of 400g which would allow a rather small 15g for a mount to attach a Sony A5000 DSLM or 68g to attach a Sony QX1 Lens-Style Camera without weighing too much, although the system could be flown with excess weight reducing the flight time. A downward facing 3D Printed Sony A5000 Mapping Mount  is available for both the Iris+ Quadcopter and X8+ Octocopter, it weighs 36g.

Although the X8+ is a octocopter by definition, it gets over the intrinsic problems of size, weight and cost caused by eight separate arms by having two rotors on each arm, one pointing up and the other downwards. With a maximum payload of 1KG it can carry a Sony A5000 DSLM camera (388g) together with a gimbal such as the DYS 3 Axis Brushless Gimbal for Sony NEX size cameras (609g) to support and move it, the gimbal is designed for the NEX range of cameras, but they are almost identical to the A5000 in design. Although a lighter mount could be used.

3 Axis Brushless Gimbal for Sony NEX size cameras

3 Axis Brushless Gimbal for Sony Nex size cameras

Conclusions

The mirror-less camera would seem to provide a solution to the problem of how to carry a high specification camera capable of capturing high quality images on a fairly low-cost UAV solution.

Sources

http://en.wikipedia.org/wiki/Mirrorless_interchangeable-lens_camera

http://www.dummies.com/how-to/content/gopro-cameras-understand-the-cameras-limitations.html

http://www.japantimes.co.jp/news/2013/12/30/business/mirrorless-cameras-offer-glimmer-of-hope-to-makers/

Quadcopter vs Hexacopter vs Octocopter: The Pros and Cons

Cloud UAV Photogrammetry Processing

Online photogrammetry processing systems such as Autodesk’s 123D Catch (which now forms part of a whole suite of software designed to do everything from 3D capturing to 3D model creation through to 3D printing) have been around for a number of years and are available on platforms including iOS, Android and Windows. But they are aimed at the amateur with limited settings and low quality results.

Recent developments in Cloud Photogrammetry Processing have brought developing technologies that can potentially save a lot of time and money in processing photographs taken on site and in the office having the abilities of commercial desktop software solutions as well as producing high quality results.

Commercial Solutions

The DroneMapper company are one of a number of ventures aimed at the processing of UAV (Unmanned Aerial Vehicle) photographs for a number of industries including archaeology. Rather than using existing photogrammetry solutions they have developed their own custom in-house photogrammetry software package.

Images or a RAR archive file can be uploaded to their server using either their web interface, FTP (File Transfer Protocol) interface or a Dropbox account. Their current processing costs are between $20 and $100 USD.

While the REDCatch company provides processing of ground based and object processing as well as UAV photographs ; costing anything from 290€ to over a 1000€

Open Source Solutions

An Open Source alternative to this is Open Drone Map, this system uses a number of previously developed SFM (Structure from motion) solutions to automate the processing of photographs into 3D models, orthophotos and Digital Elevation Models (DEM) for GIS (Geographic Information Systems) applications. Although free for non-commercial purposes a license needs to he purchased to use it in commercial circumstances.

OpenDroneMap running on Ubuntu Linux

OpenDroneMap running on Ubuntu Linux

The code can be downloaded from Github and includes detailed written instructions and YouTube videos on how to install if on Ubuntu Linux. This means that it can be simply installed on Ubuntu running on many internet hosting services.

It uses both Clustering Views for Multi-view Stereo (CMVS) and Patch-based Multi-view Stereo Software
(PMVS)
developed by Yasutaka Furukawa and Jean Ponce; as well as Bundler: Structure from Motion (SfM) for Unordered Image Collections developed by Noah Snavely.

hall-all

CMVS

teaser

PMVS

Colosseum

Bundler

The VisualSFM GUI developed by Changchang Wu includes the same software combined into a single computer program.

Potential
As we can see there is great potential for the cloud processing of photogrammetry models, whether by commercial companies or with open source software. This can remove the need for expensive photogrammetry software and the expertise to use it. Photographs can be uploaded as they are taken, or shortly afterwards and the processing begun before the person recording leaves the site. This obviously saves the time it would take to return to the office and download the photographs.

Limitations
One current limitation of the open source system is the fact that it is solely aimed at photogrammetric vertical mapping recording, meaning that there is no need to mask the photographs in the software. There is however a requirement for the masking of photographs within the photogrammetric recording of standing structures and objects where elements of the photographs need to be masked out in order to get the best results.

Bibliography
Agarwal, Sameer, Noah Snavely, Steven M. Seitz, and Richard Szeliski. “Bundle adjustment in the large.” In Computer Vision–ECCV 2010, pp. 29-42. Springer Berlin Heidelberg, 2010.

Agarwal, Sameer, Yasutaka Furukawa, Noah Snavely, Ian Simon, Brian Curless, Steven M. Seitz, and Richard Szeliski. “Building rome in a day.” Communications of the ACM 54, no. 10 (2011): 105-112.

Furukawa, Yasutaka, Brian Curless, Steven M. Seitz, and Richard Szeliski. “Towards internet-scale multi-view stereo.” In Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conference on, pp. 1434-1441. IEEE, 2010.

Furukawa, Yasutaka, and Jean Ponce. “Accurate, dense, and robust multiview stereopsis.” Pattern Analysis and Machine Intelligence, IEEE Transactions on 32, no. 8 (2010): 1362-1376.

Wu, Changchang, Sameer Agarwal, Brian Curless, and Steven M. Seitz. “Multicore bundle adjustment.” In Computer Vision and Pattern Recognition (CVPR), 2011 IEEE Conference on, pp. 3057-3064. IEEE, 2011.

Wu, Changchang. “Towards linear-time incremental structure from motion.” In 3D Vision-3DV 2013, 2013 International Conference on, pp. 127-134. IEEE, 2013.

UAV (Unmanned Aerial Vehicle) Archaeological and Cultural Heritage Recording

Introduction

Recent developments in a number of technical areas has allowed the development of battery powered UAV (Unmanned Aerial Vehicles) systems which has allowed recording technologies to become airborne easily with extensive control over what is being recorded.

Many of these low cost UAV solution come ready to fly out of the box with some even coming with a camera. These systems have allowed archaeology and cultural heritage to be recorded in whole new innovative ways.

There are basically two types of UAV systems that are employed, each with their benefits and drawbacks:

  • Fixed wing systems use less power and can spend longer flying, but don’t have the ability to hover in one place or change direction quickly. They are also designed for mapping so carry cameras that only point downwards.
    The 3DRobitics Aero-M fixed-wing drone

    The 3DRobitics Aero-M fixed-wing drone

  • Multi-rotor systems use more power as their multiple rotors are turning all of the time they are in the air, so they can spend less time flying and recording. They have the ability to hover and change direction and altitude quickly.
    X8-M

    The 3DRobotics X8-M hexacopter

Recent developments have seen UAVs which combine the two systems, such as the SkyProwler Kickstarter Project. This is a system that can be fixed wing, fixed wing with rotors or just rotors. The rotors are retractable which can be deployed when required while in the fixed wing configuration.

Krossblade SkyProwler

Krossblade SkyProwler

UAV Technological developments

A number of technological developments have led to the recent proliferation of UAV systems being used in different industries and hobbies.

Batteries

The development of the LiPo (Lithium Polymer) battery brought a number of improvements over the previous NiMH (Nickel-metal hydride) battery technology used in Radio Control (RC) Vehicles. They:

  • Have a larger capacity and last longer.
  • Are more powerful.
  • Are smaller and lighter.
  • Are cheaper.

This means that a UAV system can fly for longer, further and faster with a battery that weighs less.

Brushless Motors

The brushless motor has taken over from the brushed motor in the RC (Radio Control) industry with their:

  • Superior power.
  • Higher efficiency.
  • Greater reliability.
  • Higher accuracy.
  • Reduced noise.
  • Lower susceptibility to mechanical wear.
  • Longer lifetime.
  • Smaller size.

A brushed motor works by controlling the polarity of an electromagnet (coil of wires) between two magnets of different poles. The brushes in the brushed motor carry the electric current to the armature (electromagnet) of the motor by being in constant contact with it as it rotates. This causes wear to the brushes and at higher speeds friction, reducing torque and creating heat.

The brushed motor works in the opposite way, by having the coils of wire on the outside, with the magnet in the middle. It removes the need of the brushes but complicates the process as the position of the rotor needs to be sensed and the coils controlled in phase by an electronic speed controller (ESC). Although they are mechanically more complicated and cost more than brushed motors, their other benefits outweigh those of the brushed motor.

Brushed and brushless motors (http://www.eskyhelicopters.com/)

Brushed and brushless motors (http://www.eskyhelicopters.com/)

Brushless Gimbal

Linked intrinsically with the Brushless Motor is the Brushless Gimbal, this is a system which both; holds a camera steadily and level in a single position while the UAV moves around it thereby removing camera shake, and it also can be panned up and down and side to side in more expensive systems.

Camera gimbal pitch, yaw and roll. (http://science.howstuffworks.com/)

Camera gimbal pitch, yaw and roll. (http://science.howstuffworks.com/)

UAV brushless camera gimbals come in two types:

  1. 2-axis. This has two brushless motors which control the camera pitch and roll. This system relies upon filming in the direction that the UAV is pointing and is generally available on the cheaper UAV systems. These have legs which would be in the way if the camera was able to yaw.

    DJI Zenmuse H3-2D Gimbal

    DJI Zenmuse H3-2D Gimbal

  2. 3-axis. This has three brushless motors which control the camera pitch, yaw and roll. This allows cinematography to be conducted from UAV platform with the movement of the camera almost completely removed from the movement of the UAV. And in many cases a separate person can control the camera. These more expensive systems generally have retractable legs allowing the camera to pan left and right.

    DJI Zenmuse Z15-5D III (HD) Gimbal

    DJI Zenmuse Z15-5D III (HD) Gimbal

Gimbals can also be constructed using technology and how-to guides readily available on the internet. A number of Brushless Gimbal Controler Boards are available (including the V3 Martinez Board) as well as gimbal kits and brushless motors.

V3 Martinez Brushless Gimbal Controller Board

V3 Martinez Brushless Gimbal Controller Board

GPS (Global Positioning System)

GPS has a number of applications within the UAV industry:

  1. It is used to make flight easier by using the GPS signal to hold the UAV in one place by calculating if it is moving.
  2. It can be used together with an autopilot to automatically control the flight path of the system.
  3. The GPS co-ordinates at which each photograph is taken can be used within photogrammetry software to help with the locating and aligning of the photographs.
3DR uBlox GPS with Compass

3DR uBlox GPS with Compass

Mast

Mast

The GoPro

The lightweight GoPro series of camera was another enabling factor in the development of the UAV market. Many UAVs are in fact developed with the GoPro camera in mind. Not only are the GoPro series of cameras a lightweight powerful system but they also have wireless communication allowing the camera to be controlled, and the display to be viewed remotely.

Although there are now a number of different sports cameras the majority of low cost UAV systems, particularly those on the Kickstarter and Indiegogo crowdfunding platforms are designed with carrying the GoPro in mind.

Autopilot Systems

Autopilot systems can be very beneficial in the recording of different aspects of Archaeology and Cultural Heritage.

  • They can be used to plan a flight path for the UAV to take over the subject matter.
  • They can be used to create a grid pattern flight path as part of a mapping operation.
Mission Planner

Setting a flight path within Autopilot software

3DRobotics

3DRobtics is a personal drone manufacturing company which also manufactures open source autopilot systems that are the most popular in the world. They are used on many of the Kickstarter systems available.

The company produce two Autopilot systems:

  • The APM 2.6 System is based on the Arduino micro controller. It includes a 3-axis gyro, 6 DoF (Degree of Freedom) accelerometer, high-performance barometric pressure sensor and automatic datalogging.

    APM 2.6 Autopilot

    APM 2.6 Autopilot

  • The Pixhawk is an advanced autopilot system designed by the PX4 open-hardware project and manufactured by 3D Robotics, it includes a 3-axis 16-bit gyroscope, 3-axis 14-bit accelerometer/magnetometer, 3-axis accelerometer/gyroscope and a barometer. A digital airspeed sensor and GPS and compass can be purchased with the system and plugged into the Pixhawk board.

    Pixhawk Autopilot

    Pixhawk Autopilot

NAVIO

The NAVIO is an Indigogo project to build a Raspberry Pi based autopilot which attaches to the top of the credit-card sized computer allowing the construction and control of a UAV system with the powerful small computer system.

NAVIO Autopilot

NAVIO Autopilot

Follow Me Technology

A recently developed technology which is becoming increasingly popular in the drone industry is the ‘Follow Me’ technology where the drone will follow some sort of controller, whether a mobile phone / tablet / laptop or a specially designed piece of technology such as the AirLeash which comes with the AirDog drone. These systems use autopilots systems combined with GPS technology in the controller to control the direction and speed of the UAV system.

The ‘Follow Me’ technology is designed for the extreme sports industry where the drone can follow the user, filming as it flies, whether they are on a motorbike/mountain bike, surf board or other sports equipment. As well as controlling the flight path of the drone following the user it also controls the gimbal that holds the camera keeping the user in shot at all times. In some systems a number of pre-determined video filming techniques are made available with the control app which add to the abilities of the system.

Within Archaeology and Cultural Heritage the system has the potential for filming site tours, where the person giving the tour is tracked by the ‘Follow Me’ system, they would also have a digital audio recording system attached to them to record the dialogue which could be matched with the video in post-production. It would allow one person to do all of the production of the video.

Object tracking and following

Object tracking and following is an expansion of the ‘Follow Me’ technology where rather than following a GPS enabled device an object is selected within an interface and the system visually tracks the object. The UAV follows the tracked object with the camera being locked onto it.

Shift

The Shift has been developed by Perceptiv Labs, it attaches to existing UAV systems, such as those designed by DJI and 3DRobotics, as well as custom systems created with a number of different flight control systems and autopilot systems.

shift

Shift Object Tracking System

Shift Object Tracking System

Through the use of a Shift Eye video camera (attached to the camera of the UAV system) and a Shift Processor computer which plugs into the autopilot it provides standard UAV systems with the ability to track up to four subjects and follow and record them in flight. The subjects are selected using an app available on Android devices.

shift3

shift4

This could add to the site tours potential of the ‘Follow Me’ technology by selection the tour guide within the app when they are walking around, then also selecting the area under study when appropriate. This would be done best by having a second person controlling the app by watching the video, selecting the areas of interest when required and moving back to the tour guide when needed.

Autonomous

Development in autonomous flight of UAVs has a number of benefits for recording where a UAV could record the progress of an excavation at intervals, or record a standing building without any need for control by the pilot.

A number of simple autonomous technologies have already been integrated within commercial UAV technology.

Ultrasonic distance sensors

Ultrasonic distance sensors calculate distance by sending an ultrasonic wave and calculating the time it takes to receive the wave back.

MB1240 XL-MaxSonar®-EZ4™ High Performance Ultrasonic Range Finder

MB1240 XL-MaxSonar®-EZ4™ High Performance Ultrasonic Range Finder

They can be used in obstacle avoidance systems for UAVs, with the ultrasonic beam bouncing off objects in the UAVs path. The ultrasonic sensor is attached to the autopilot which can alter the path of the UAV when an obstacle is detected. With the APM autopilot the sensor it is enabled and calibrated within the Mission Planner Software.

Sonar_Setup

Optical Flow Technology

Optical flow technology is a technique where multiple images from a sensor are compared to determine movement, recent developments in technology mean that this can now be done in real time. It can be used in combination with Autopilot systems to stabilise the flight position of a UAV by detecting movement between photograph and altering the flight accordingly.

The PlexiDrone Indiegogo crowfunding project even comes with the technology demonstrating the growing availability and cheapness of the technology.

The PlexiDrone Indiegogo crowfunding project even comes with the technology demonstrating the growing availability and cheapness of the technology.

The Parrot Bebop Drone comes with Optical Flow Technology integrated into its design (8), with an image of the ground being taken every 16 milliseconds and then compared with the previous one.

Plexidrone

Plexidrone

The PlexiDrone Indiegogo crowfunding project also comes with the technology demonstrating the growing availability and cheapness of the technology in crowdfunding projects.

As well as being integrated into in some UAV technology the sensors themselves can be purchased separately; in UAV technology they come in two distinct types:

    • Mouse Based. The mouse based sensor is based upon the technology of optical computer mice.
3DRobotics Optical Flow Sensor Board with ADNS3080 mouse sensor

3DRobotics Optical Flow Sensor Board with ADNS3080 mouse sensor

  • CMOS Based. The CMOS based sensor uses a CMOS camera chip to capture the images.
    PX4FLOW KIT with MT9V034 machine vision CMOS sensor with global shutter

    3DRobotics PX4FLOW KIT with MT9V034 machine vision CMOS sensor with global shutter

    Vision Positioning System

    The Vision Positioning System present in the DJI Inspire 1 uses a combination of Ultrasonic sensors and Optical Flow Technology to control the position of the UAV in environments where GPS signals cannot reach. It can hold its position and stop when the RC controls are released.

    DJI Inspire 1 Vision Positioning System – [1] Two sonar sensors [2] One binocular camera.

    DJI Inspire 1 Vision Positioning System – [1] Two sonar sensors [2] One binocular camera.

    Intel RealSense

    The Intel RealSense is a new depth-capturing camera technology designed to be incorporated into the latest laptop and tablet technology. It has the ability, thanks to its specialised lens array, to alter the focus of photographs after they have been taken, like the Lytro Illum. It can also track hand gestures to control the computer systems and 3D scan real world objects.

    The new Astech Trinity Autopilot system incorporates 6 Intel RealSense cameras enabling 360˚ motion capture and obstacle avoidance . 
    The Astech Trinity Autopilot will be incorporated into the AscTec Firefly later this year.

    Asctec  Trinity

    Asctec Trinity Autopilot – http://www.theverge.com/

    Swarm Technology

    A lot of technical development has gone into the idea of drone swarms where multiples drones fly together in cooperation. Amongst the applications considered for their use are search and rescue, crop pollination, surveillance, monitoring traffic and as a distributed computing and communications network in disaster areas. Work at the GRASP (General Robotics, Automation, Sensing & Perception) Lab at the University of Pennsylvania has included navigating obstacles, Simultaneous Localization and Mapping (SLAM) using a Microsoft Kinnect and Laser Rangefinder, flying formation by monitoring each other’s position and co-operation in building structures.

    Within Archaeological and Cultural Heritage recording this has the potential for a swarm of UAVs to record areas in co-operation reducing the time taken, as well as the potential of using different technologies to record at the same time.

    Recording Technologies

    Introduction

    A UAV can act as a platform for a number of different recording technologies that can be employed in the recording of Archaeology and Cultural Heritage.

    Photogrammetry

    Photogrammetry is a technique for taking measurements from photographs and can be used to create a number of different results.

    The type of camera system used depends on the type of UAV system employed, the more powerful the system the heavier and more powerful the camera that it can carry.

    Weight is an important consideration; cheaper UAV systems are designed to only carry the GoPro or another extreme sports camera. While the more expensive/powerful systems can carry higher powered digital SLR cameras which record in much higher levels of detail and without lens distortion. The better quality the camera the more details are recorded.

    A number of 360° camera systems have been released which can be attached to the bottom of UAV systems. These have the potential to record many more photos than a single camera, this could potentially speed up photogramemtric recording as well as providing immersive experiences using VR (Virtual Reality) technology such as the Oculus Rift.

    360Heros 360° GoPro mount

    360Heros 360° GoPro mount

    Archaeological Mapping

    UAVs are used for mapping within a number of industries, and have already begun to be used in the mapping of archaeological sites. They provide an ideal platform for the creation of DTM (Digital Terrain Model) and DSM (Digital Surface Model) models which can be used in GIS (Geographical Information Systems) applications.

    This is the ideal project for a fixed wing UAV which can be deployed to fly over the area under study with a downward facing camera. The major benefits of such a systems is the stability, the amount of time that they can fly and hence the amount of recording that they can do in one flight.

    Using autopilot systems and software for programming the autopilot, such as Mission Planner, the flight plan for the UAV can be programmed.

    MP-FP-Screen

    Setting out a UAV light pattern in the Mission Planner Software

    Such software has the ability to create a grid flight pattern using the study area selected in the map interface, the altitude flown, the image overlap and the characteristics of the camera being used. Any alteration in the altitude, image overlap or camera specification (such as lens used) will alter the grid pattern to accommodate the alterations.

    Grid

    Setting out a grid UAV flight pattern in the Mission Planner software

    A grid of circular paper targets can be set up on the ground with each target being surveyed in using a GPS (Global Positioning System) which both increased the accuracy of the photogrammetry model and georeferences the results so they can incorporated with other data within a GIS system

    Standing Building Recording

    Photogrammetry has a long history in standing building recording which has be enhanced by the ability of the Total Station to survey points accurately. Limitations of ground based photogrammetry include the ability to record information high above the ground or masked from view. Traditionally this has been solved by using scaffolding, but his is an expensive and time consuming system which can also be dangerous.

    Another option is to use standard building photogrammetric recording techniques to record structures in high detail using a UAV to fly the camera at set heights parallel to the structure. This would mean that high quality imagery could be created using standard methods. The UAV can act as a mobile camera platform/tripod which has the ability to take to camera to heights not easily accessible by other means. Certain points on the building surface would need surveying in using a total station to georeference the 3D model created by the photogrammetry process and to make it more accurate. Orthophotos (geometrically corrected images) can be created from the images taken which are an important element in building recording.

    Increasing development in autonomous flight can be used to automate the flight patterns having the UAV automatically record buildings.

    HDR (High Dynamic Range)

    High Dynamic Range photography is a technique where multiple images are taken with different exposures (bracketing), these are then merged together using computer software to form an image with all of the detail from the images. Many modern digital camera have an auto-exposure bracketing (AEB) setting which allows this to set up on the camera to be done automatically. There are also dedicated HDR cameras. It provides images which are close to what the human eye can see and with more information than standard photographs.

    The problem with using UAVs for this technology is that the images need to be taken while the camera is perfectly still, and even with a camera gimbal a UAV is likely to move slightly between the photographs being taken.

    HDR photographs can also be used in photogrammetry.

    Video

    The video capabilities of most cameras that UAVs carry mean that they can record videos. As we have already seen the ‘Follow-Me’ technology has the potential within archaeology or cultural heritage to record a site tour, filming the tour guide as they walk around site, with a separate digital recording system recording the audio which can later be combined with the video footage in post-production. The Hexo+ UAV Director’s Toolkit allows different filming scenarios such as crane; pan, tilt, crab, dolly, 360° around you, and far-to-close/close-to-far.

    The UAV has the potential to create immersive fly through videos of sites thanks to the recent introduction of multi-camera systems or systems with multi-lens cameras, this can aid in public interaction and interest.

    Archaeological Prospection

    Lidar (Light Detection And Ranging)

    LIDAR is a technology which has already proved useful in Archaeology and Cultural Heritage, it works by firing a pulsed laser beam at the ground and recording the returned beams, the time it takes for the beam to return is recorded and this is used to determine the distance. It is tied to the flight instruments of the light aircraft carrying the LIDAR and accurately records the 3D position and height of the results creating a dense point-cloud of the topography being recorded. The resulting LIDAR point data can be loaded in GIS systems.

    It has the potential to discover archaeological remain under woodland by removing points from the LIDAR point-cloud leaving only the points that hit the ground between the forest cover.

    Although not a cheap technology a number of LIDAR systems have recently been developed which can be carried as a payload on UAV systems. This includes the Phoenix Aerial Systems AL3 S1000 Copter which combines a DJI S1000 Octocopter with their AL3 technology which includes the Velodyne HDL-32 high definition LiDAR sensor.

    AL3 S1000 Copter

    Phoenix Aerial Systme – AL3 S1000 Copter

    If the UAV system recorded high quality photographs as well, these could be recorded in a separate flight using the same flight path, these could be used to overlay the LIDAR data.

    LIDAR can be analysed with a number of computer tools enabling more information to be visualised.

    LiDAR Data with Multiple Hillshades and with Principal Component Analysis (PCA).

    LiDAR Data with Multiple Hillshades and with Principal Component Analysis (PCA).

    Multi-Spectral and Hyper-Spectral Imaging

    Multi-Spectral and Hyper-Spectral imaging involves the recording of the electromagnetic spectrum outside the visible spectrum, this includes the infrared which can detect differences in ground moisture helping to determine what is below the ground level.

    Traditionally this has been done using satellites but spectral imagers are also available for UAV platforms.

    Comparative multispectral imagery of prehistoric field systems near Stonehenge © Historic England.NMR; Source Environment Agency

    Comparative multispectral imagery of prehistoric field systems near Stonehenge © Historic England.NMR; Source Environment Agency

    Ground Penetrating Radar (GPR)

    Ground Penetrating Radar is a technology that is used within field archaeology to discover buried features, it works by recording reflected radio waves that have been transmitted into the ground. GPR can be used on areas such as concrete, stone and tarmac where other geophysical techniques won’t work.

    MSc students from the University of Southampton carrying out a GPR survey in the vicinity of the Episcopio, between Portus and the Isola Sacra, Italy (https://kdstrutt.wordpress.com)

    The potential of having UAVs carry Ground Penetrating Radar recording equipment has already been tested in a number of fields including the detection of IEDs (Improvised Explosive Devices) and mines and the characterization of soil properties. But studies, including one at the University of Leicester, are looking into the potential of GPR carrying UAVs in archaeological recording.

    Bibliography

    Amiri, Amin, Kenneth Tong, and Kevin Chetty. “Feasibility study of multi-frequency Ground Penetrating Radar for rotary UAV platforms.” (2012): 92-92.

    Eisenbeiß, Henri. UAV photogrammetry. Zurich, Switzerland: ETH, 2009. http://www.igp-data.ethz.ch/berichte/Blaue_Berichte_PDF/105.pdf

    Gray, S. UAV Survey: A Guide to Good Practice, 2014. Part 1: http://www.jiscdigitalmedia.ac.uk/infokit/3d/uav-survey Part 2: http://guides.archaeologydataservice.ac.uk/g2gp/AerialPht_UAV

    Jacobs, Axel. “High dynamic range imaging and its application in building research.” Advances in building energy research 1, no. 1 (2007): 177-202.

    Li, Zhe, Yan Li, and Nankai Tian Jin. “Photogrammetric recording of ancient buildings by using unmanned helicopters-cases in China.” International Archives of the Photogrammetry, Remote (2011).

    Michael, Nathan, Shaojie Shen, Kartik Mohta, Yash Mulgaonkar, Vijay Kumar, Keiji Nagatani, Yoshito Okada et al. “Collaborative mapping of an earthquake‐damaged building via ground and aerial robots.” Journal of Field Robotics 29, no. 5 (2012): 832-841.

    Ntregkaa, A., A. Georgopoulosa, and M. Santana Quinterob. “Photogrammetric Exploitation of HDR Images for Cultural Heritage Documentation.” ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences 5 (2013): W1.

    Saleri, Renato, Nocerino Erica, Fabio Remondino, and Fabio Menna. “ACCURACY AND BLOCK DEFORMATION ANALYSIS IN AUTOMATIC UAV AND TERRESTRIAL PHOTOGRAMMETRY-LESSON LEARNT.” In International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. 2, pp. 203-208. 2013.