positioning in time and space – cost-effective
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1. ISPRS Annals of the Photogrammetry Remote Sensing and Spatial Information Sciences Volume II 5 W1 2013 XXIV International CIPA Symposium 2 6 September 2013 Strasbourg France calculate the yaw values from the APM 2 0 it is at this stage not possible to properly determine the yaw difference between the camera and APM 2 0 CRS 4 PRACTICAL EXAMPLE Since it was the aim to compare a standard geocoding approach in terms of accurate orientation values as well as post processing workflow with the solution presented here a rig was built with a Nikon D300 and a Nikon D300s The former was equipped with the APM 2 0 based solution while a commercially available geocoding solution the Solmeta Geotagger Pro 2 was mounted on the D300s Using the built in timer both cameras were synchronised and programmed to take an image every ten seconds While alternatingly walking around and standing still 33 photographs were obtained from the previously mentioned network of control points located on a building s outer facade Besides the comparison of both GNSS IMU solutions the images also allowed to calculate the mounting calibration of the APM 2 0 based solution described in section 3 4 1 Solmeta Geotagger Pro 2 solution Based on the same chipset as the APM 2 0 i e MediaTek MT3329 the latest product from Solmeta is a very small and light 50 g WAAS EGNOS enabled GNSS receiver Solmeta Technology 2012 The Geotagger Pro 2 fea2. 3D orientation of the sensing platform Combining a GNSS and IMU also allows for the direct georeferencing of aerial photographs which means image georeferencing can be executed without the need for ground control points However the low cost IMU that has been applied here is certainly not the most accurate and stable one in terms of drift rate Further developments of the post processing workflow should partly remedy this Besides the straightforward strap down processing of IMU data it might be necessary to use a more advanced approach that combines all the sensor measurements GNSS IMU magnetometer An example could be the procedure described by Wendel in which a Kalman filter is developed for a GNSS IMU combination of a MEMS IMU and code based GNSS receiver to calculate accurate position velocity orientation and IMU drift bias values Wendel 2007 In addition to the improved post processing algorithms future tests will also incorporate a far more expensive and accurate IMU Comparing the processed output and drift of the sensors will subsequently allow to decide if archaeologists should select the cost effective option presented here or if the advantages of the more expensive solution are essential for the subsequent image management and georeferencing workflows So far this solution has only been used for terrestrial applications in which the camera operator is walking around Even in such a low dynamic situation the achieve
3. APM 2 0 after mounting calibration and Geotagger as well as those estimated for the photographs using the imaged control points while Figure 5 displays a zoom of the roll angle graph of Figure 4 It is clearly visible that there is not a big difference in the angles obtained from the photograph with PhotoScan green dots and the angles computed by the strap down algorithm using the continuously logged APM 2 0 raw sensor data The standard deviations of those differences equal 1 3 for pitch and 0 8 for roll angle with maximum deviations of 3 and 1 5 respectively The mean difference between both measurements was 0 as one would expect after a mounting calibration Even though the algorithm for the strap down calculations is rather simple and stable different filter lengths applied on the raw data can cause changes in the calculated orientation exceeding half a degree Consequently highly accurate orientation results necessitate access to the raw data output of the GNSS IMU sensors As the Solmeta Geotagger Pro 2 is a black box there is no access to the raw sensor data while the update rate is limited to 1 Hz This resulted in standard deviations of 7 4 for pitch and 12 5 for roll angle between the Geotagger output and the images from the camera on which it was mounted after the estimation of the mounting calibration for the Solmeta device Quantifying standard deviations by a more robust metric such as the median absolute deviatio
4. peer reviewed The double blind peer review was conducted on the basis of the full paper 313 ISPRS Annals of the Photogrammetry Remote Sensing and Spatial Information Sciences Volume II 5 W1 2013 XXIV International CIPA Symposium 2 6 September 2013 Strasbourg France Finally hardware based geocoding is also possible This is a very straightforward approach since the camera s software i e firmware takes care of all the rest Several compacts e g Sony Cyber shot DSC HX30V and Canon PowerShot S100 bridge e g Nikon Coolpix P510 and Sony Cyber shot DSC HX100V or Single Lens Reflex SLR cameras e g Sony SLT A99 and Canon EOS 6D already feature a built in GNSS receiver More common is the option to physically link a separate GNSS receiver onto a digital camera Until a few years ago only the high end Nikon digital SLR cameras such as the D2X s D2Hs D1X D1H and D200 together with the Fuji S5 Pro supported this flexible way of geocoding Currently several Canon and Pentax SLR models also offer this as an option while Samsung Canon Leica and Nikon even included the option to attach a manufacturer specific GNSS receiver onto one or more of their mirrorless cameras Using any of the hardware software or hybrid workflows the end result is a so called geocoded image an image that was assigned a geographic identifier in its metadata a geocode to pinpoint its location somewhere on the Earth Since this is generally done
5. sparkfun com products 9530 14 April 2013 Verhoeven G 2008 Digitally Cropping the Aerial View On the Interplay between Focal Length and Sensor Size Ar cheologia Aerea Studi di Aerotopografia Archeologica 3 pp 195 210 Verhoeven G Doneus M Briese C Vermeulen F 2012 Mapping by matching a computer vision based approach to fast and accurate georeferencing of archaeological aerial photographs Journal of Archaeological Science 39 7 pp 2060 2070 Wendel J 2007 Integrierte Navigationssysteme Sensordaten fusion GPS und Inertiale Navigation Oldenbourg Miin chen x 336 Wilson D 1975 Photographic Techniques in the Air in Wilson D R Ed Aerial reconnaissance for archaeol ogy Research Report Series 12 The Council for British Archaeology London pp 12 31 Wilson D 2000 Air photo interpretation for archaeologists 2nd ed Tempus Stroud 256 pp Wolf P Dewitt B 2000 Elements of photogrammetry with applications in GIS 3rd ed McGraw Hill Boston XIII 624 7 ACKNOWLEDGEMENTS This research is being carried out with the financial support of the Austrian Science Fund FWF P24116 N23 The Ludwig Boltzmann Institute for Archaeological Prospection and Virtual Archaeology archpro lbg ac at is based on an international cooperation of the Ludwig Boltzmann Gesellschaft A the University of Vienna A the Vienna University of Technology A the Austrian Central Instit
6. ISPRS Annals of the Photogrammetry Remote Sensing and Spatial Information Sciences Volume II 5 W1 2013 XXIV International CIPA Symposium 2 6 September 2013 Strasbourg France POSITIONING IN TIME AND SPACE COST EFFECTIVE EXTERIOR ORIENTATION FOR AIRBORNE ARCHAEOLOGICAL PHOTOGRAPHS Geert Verhoeven Martin Wieser Christian Briese Michael Doneus VIAS Vienna Institute for Archaeological Science University of Vienna Franz Klein Gasse 1 1190 Vienna Austria geert verhoeven michael doneus univie ac at LBI for Archaeological Prospection and Virtual Archaeology Franz Klein Gasse 1 1190 Vienna Austria christian briese archpro lbg ac at Department of Geodesy and Geoinformation Vienna University of Technology Gusshausstrasse 27 29 1040 Wien Austria e0626234 student tuwien ac at KEY WORDS Aerial image Archaeology Direct georeferencing Exterior orientation Geocoding GNSS INS ABSTRACT Since manned airborne aerial reconnaissance for archaeological purposes is often characterised by more or less random photographing of archaeological features on the Earth the exact position and orientation of the camera during image acquisition becomes very important in an effective inventorying and interpretation workflow of these aerial photographs Although the positioning is generally achieved by simultaneously logging the flight path or directly recording the camera s position with a GNSS receiver this appro
7. ach does not allow to record the necessary roll pitch and yaw angles of the camera The latter are essential elements for the complete exterior orientation of the camera which allows together with the inner orientation of the camera to accurately define the portion of the Earth recorded in the photograph This paper proposes a cost effective accurate and precise GNSS IMU solution image position 2 5 m and orientation 2 both at 1o to record all essential exterior orientation parameters for the direct georeferencing of the images After the introduction of the utilised hardware this paper presents the developed software that allows recording and estimating these parameters Furthermore this direct georeferencing information can be embedded into the image s metadata Subsequently the first results of the estimation of the mounting calibration i e the misalignment between the camera and GNSS IMU coordinate frame are provided Furthermore a comparison with a dedicated commercial photographic GNSS IMU solution will prove the superiority of the introduced solution Finally an outlook on future tests and improvements finalises this article 1 INTRODUCTION 1 1 Oblique archaeological reconnaissance To date the common practise of archaeological aerial photographic reconnaissance is quite straightforward and seems not to have significantly changed over the past century In general images are acquired from the cabin of a low flying aircr
8. aft preferably a high wing aeroplane using a small or medium format hand held photographic still frame camera equipped with a lens that is typically uncalibrated Wilson 1975 Once airborne the archaeologist flies over targeted areas and tries to detect possible archaeologically induced crop and soil marks Once an archaeological feature is detected it is orbited and documented from various positions generally from an oblique point of view This type of aerial photographic reconnaissance has been the workhorse of all archaeological remote sensing techniques since it is one of the most cost effective methods for site discovery and the non invasive approach yields easily interpretable imagery with abundant spatial detail Wilson 2000 Due to the fact that flying paths and photo locations are never predefined in this oblique reconnaissance approach and accurate mapping and photo interpretation necessitates knowledge about the part of the Earth s surface covered by the aerial image the latter information should ideally be recorded during photo acquisition If not the subsequent image management and interpretation workflow becomes very time consuming and certain questions are difficult to answer e g Where was this photograph taken or Which pictures cover that area In the worst case scenario retrieving the exact location of a specific aerial image might even prove impossible 1 2 Geocoding Generally embedding geog
9. by writing geographical coordinates into some pre defined Exif metadata tags of that particular photograph location stamping or geotagging are often used synonyms for this type of image geocoding 1 3 Exterior orientation When applying any of the aforementioned geocoding methods the Exif tags will only represent the position of the camera photographer at the moment of image creation This is by no means an accurate way of describing the specific spot on Earth that is captured in the aerial image To achieve this additional information is needed An airborne camera is always placed at a certain location in the air but it is also pointed into a specific direction and has a particular diagonal Field of View FOV the angle in object space over which objects are recorded in a camera The camera location is defined by the projection centre O with three coordinates Xo Yo Zo while the direction is defined by three rotation angles roll pitch g and yaw x around X Y and Z Figure 1 Together these six parameters establish the so called exterior outer orientation Kraus 2007 Synonyms often used in the field of computer vision are camera extrinsics or camera pose When and equal zero or maximally deviate by 3 from the vertical to the Earth s surface the result is a perfect nadir vertical photo When the optical axis of the imager intentionally deviates more than 3 from the vertical the images are said to be oblique in
10. ction as our benchmark in the tests described in section 4 Secondly only Nikon s semi pro and pro level digital SLRs store the sub second timing as metadata tags at least to the authors knowledge Most cameras use a temporal resolution of one second since the date time fields in the original Exif 2 3 specification are defined this way Camera amp Imaging Products Association 2010 2012 Although there are Exif fields that provide sub second information i e SubSecTime SubSecTimeOriginal SubSecTimeDigitized they are often 00 or always have identical values Also the GPSTimeStamp Exif field only has one second resolution Camera amp Imaging Products Association 2010 2012 Although appropriate in most cases it can be crippling for scientific aerial This contribution has been peer reviewed The double blind peer review was conducted on the basis of the full paper 314 ISPRS Annals of the Photogrammetry Remote Sensing and Spatial Information Sciences Volume II 5 W1 2013 XXIV International CIPA Symposium 2 6 September 2013 Strasbourg France photography that requires exact synchronisation with GNSS and IMU data As expected testing showed that the recorded date and time by the Nikon cameras were those of data acquisition irrespective of the moment the image file was written onto the memory card However photographic sequences with disabled automatic exposure and autofocus indicated that there was no identically dig
11. d accuracy is already reported to be better than 2 in roll and pitch Once the post processing of the yaw angle is optimised airborne tests will be executed and enable a true assessment of this APM 2 0 solution in a real aerial survey environment Finally the development of a small tool that calculates the exact footprint of the aerial image out of the acquired exterior orientation values and the given inner orientation is also in progress This footprint can afterwards automatically be stored in a GIS system for an improved spatial management of aerial archaeological images 6 REFERENCES Adobe Systems Incorporated 2013 Extensible Metadata Plat form XMP http www adobe com products xmp 14 April 2013 Agisoft LLC 2012 Agisoft PhotoScan User Manual Profes sional Edition Version 0 9 0 http downloads agisoft ru pdf photoscan pro 0 9 0 en pdf 13 February 2013 Camera amp Imaging Products Association 2010 2012 Ex changeable image file format for digital still cameras Exif Version 2 3 CIPA JEITA Tokyo 185 pp http www cipa jp english hyoujunka kikaku pdf DC 008 2012_E pdf 6 April 2013 Creative Commons 3 0 2012 ardupilot mega https code google com p ardupilot mega 6 April 2013 Glira P 2012 Direkte georeferenzierung von bildern eines un bemannten luftfahrzeuges mit lowcost sensoren Diplo marbeit Harvey P 2013 ExifTool Read Write and Edit Meta Infor mation http www sno phy queens
12. enna University of Technology was imaged the complete test procedure is described in more detail in section 4 as the acquisition of the mounting calibration images was part of a more encompassing comparison test As soon as the images are acquired 33 in this calibration procedure they were automatically oriented using the Structure from Motion SfM algorithm embedded in PhotoScan Professional from Agisoft LLC Agisoft LLC 2012 Since an SfM approach computes the exterior orientations of the images by default in a local CRS and equivalent to the real world scene up to a global scaling rotation and translation Verhoeven et al 2012 the fa ade control points were inserted as constraints in the SfM solution This way the real world orientation vales of all images were obtained and described by the rotation matrix Rk Mt The rotation matrix of the APM 2 0 at the moment of image acquisition is denoted Ripy and computed using the aforementioned strap down calculation At this stage both resulting orientation matrices are expressed in the same local horizontal CRS which is mathematically defined by equations 1 and 2 while the final rotation matrices are denoted X 4y and Xipmt Since the CRS of the APM 2 0 and the camera are initially not defined in the same direction see Figure 3 equation 2 features an additional flip matrix To generate the rotational difference between Xam and X ame equation 3 was applied The result is Ryo
13. es the translation and rotation between the camera s coordinate reference system CRS and the APM 2 0 CRS often also called misalignment see Figure 3 hereby enabling a reliable coordinate transformation between both systems In other words a mounting calibration is essential if one wants to transfer the APM 2 0 observed exterior orientation values to the aerial image Since the GNSS positional accuracy is many times bigger than the displacement between the APM 2 0 and the camera the translation component is negligible Being the only remaining parameter the rotation between APM 2 0 and camera can be computed when both their exterior orientation is known not all six parameters have to be known but only the three rotation angles The camera s rotation angles can be extracted by means of control points measured in the image while the APM 2 0 s exterior orientation again limited to only the three rotation angles is given by its IMU and magnetometer measurements The final mounting matrix Ryoyyr can be computed once the rotation angles of both CRSs are known APM 2 0 CRS APM 2 0 box cement Ze Camera CRS lens camer pos Figure 3 Misalignment between the digital still camera CRS Xe Yes Ze and the CRS of the APM 2 0 Xmu Yiwu Zimu In order to calculate the mounting calibration of the test setup a Nikon D300 and the APM 2 0 a dense network of accurately measured control points fixed on a fa ade of the Vi
14. h a coaxial PC Prontor Compur 3 5 mm connector is also implemented for synchronisation Similar to the ten pin connector this PC sync cord features a locking thread for a reliable and sturdy connection Every time a photograph is taken a perfect 0 5 V square pulse can be detected This pulse lasts for the complete duration of the exposure and can be observed by an interrupt handle of the microcontroller APM 2 0 Since this sync terminal provides a highly accurate time stamp and the generated pulse is very clear it allows to distinguish every individual photograph The PC cord functions thus as the primary connection for data synchronisation while the ten pin cable is used to power the APM 2 0 and additionally serves as a synchronisation back up However all this would be useless if it remained impossible to log the GNSS IMU data that are needed for the estimation of the external orientation of the acquired images To this end the standard software on the APM 2 0 was replaced and just a part of the software modules of the ArduPilot Creative Commons 3 0 2012 are used to log all parameters of interest These are the moment of photo acquisition as well as the GNSS and IMU values over the entire time span of the image acquisition all with accurate time relations The IMU data are recorded with 200 Hz while the GNSS receiver features a 5 Hz update rate upgradable to 10 Hz Saving the entire data stream is enabled by a small logger which
15. ilt with three accelerometers and three gyroscopes which are placed orthogonal on three axes Both sensor types are based on MEMS Micro Electro Mechanical Systems technology InvenSense 2012 To get the correct orientation values a strap down calculation is performed as described by Wendel Wendel 2007 Therefore just the gyroscopes data are used Due to the high bias drift of MEMS IMUs the orientation has to be updated with pitch and roll angle values which are estimated by the accelerometers and the yaw angle given by the magnetometer and GNSS receiver These updates are just allowed under certain circumstances Accelerometers for example can only be used to update pitch and roll angle in conditions without acceleration e g static or with a constant movement In such a condition the Earth gravity vector is the only remaining acceleration and therefore can be used to calculate roll and pitch angle of the IMU Glira 2012 Pfeifer et al 2012 On the other hand the GNSS heading information can only support the yaw angle when the user is in motion 2 4 Combination of data streams Once orientation and position are calculated they have to be linked with the image file To this end two workflows have been developed The first method uses Phil Harvey s ExifTool This contribution has been peer reviewed The double blind peer review was conducted on the basis of the full paper 315 ISPRS Annals of the Photogrammetry Remote Sen
16. is more extensive than the default 4 MB logging capability of the APM 2 0 board The new serial data logger called OpenLog holds up to 16 GB microSD cards SparkFun Electronics 2012b As a result we have ample of space to log all necessary data for hours Moreover the data access is straightforward only a simple MicroSD card reader is needed This whole sensor package is housed in a simple plastic box and mounted on the hot shoe on top of the camera see Figure 2 To establish the accurate position and orientation of this box and its contained GNSS and IMU components a mounting calibration was performed section 3 2 3 GNSS IMU post processing Although the hardware solution was at this stage more or less fixed some further software issues had to be solved before a working solution was achieved that acquired the correct positional and orientation values The time dependent position is directly obtained from the GNSS receiver To this end the small displacement of around 10 cm between the perspective centre of the lens and the GNSS receiver is neglected since the observed precision of the MT3329 GNSS chipset is approximately 2 5 meter at lo when using a Satellite Based Augmentation System such as WAAS Wide Area Augmentation System or EGNOS European Geostationary Navigation Overlay Service MediaTek Incorporated 2010 The actual orientation parameters are calculated from the IMU data stream The InvenSense s MPU 6000 is bu
17. itised sub second interval between subsequent frames which brings up the question on the final accuracy of this sub second digitisation although this can also be due to the inaccurate frames per second feature This issue will be studied in the near future 2 2 GNSS IMU hardware A cost effective GNSS IMU solution is provided by the ArduPilot Mega 2 0 APM 2 0 Creative Commons 3 0 2012 an open source autopilot system featuring an integrated MediaTek MT3329 GNSS chipset MediaTek Incorporated 2010 a three axis magnetometer and the InvenSense s MPU 6000 a six axis gyro and accelerometer device InvenSense 2012 In a first stage the synchronisation between the APM 2 0 and the camera had to be established using a hardware based solution The idea was to connect the APM 2 0 directly to the Nikon ten pin remote terminal Figure 2 After testing various Nikon ten pin cables we found that the Nikon N10 cable of the Phottix GPS provided all the necessary ports Using this cable we can now power the APM 2 0 board with the camera battery so we do not need to rely on additional batteries although it is always possible see Figure 2 Moreover the camera cable transfers a signal which indicates whether the camera button is pressed or not Flash syne terminal ia Ten pin z remote Z terminal indication of the two terminals used cables are not connected Besides the Nikon ten pin cable a standard flash sync cord wit
18. n parameters from the GNSS IMU solution with the focal length f of the lens in more general terms the inner camera orientation unequivocally defines the position and orientation of the aerial image Finally the complete FOV can be calculated from the combined play between both the physical size of the camera s sensor and the focal length of the lens attached Verhoeven 2008 More exactly one should say principal distance instead of focal length as it is the distance measured along the optical axis from the perspective centre of the lens to the image plane Mikhail et al 2001 However since the lens is typically focused at infinity in aerial imaging the principal distance equals the focal length of the lens Wolf and Dewitt 2000 2 HARD AND SOFTWARE SOLUTION 2 1 Digital still camera The aim of our research was to link a digital camera with a cost effective GNSS IMU solution to achieve all exterior orientation parameters at the moment of image acquisition So far only semi professional Nikon digital SLR cameras have been used Although this choice was determined by the availability of the Nikon cameras they also offer several other advantages Nikon was to the knowledge of the authors the first to enable easy GNSS connections with their digital SLR cameras As a result many commercial GNSS solutions for hardware based geotagging can be found One of the more advanced products the Solmeta Geotagger Pro 2 will fun
19. n yields much lower values 2 9 for pitch and 2 0 for roll angle pointing to rather big outliers which are almost absent in the APM 2 0 based solution Just as the APM 2 0 based solution the provided yaw angles are much less accurate sometimes standard deviations up to 12 were observed In contrast to the here presented solution the commercial Geotagger does not allow to achieve higher accuracy of these rotational values in post processing T T T 1000 1050 1090 Elapsed time sec Figure 5 Detailed view on the roll angles orange Solmeta Geotagger Pro 2 blue APM 2 0 green dot photograph 5 SUMMARY AND OUTLOOK In terms of positioning and orientation hardware several new technologies and devices have been developed the past decades In the last years both the cost and dimensions of many of these solutions have been decreasing GNSS sensors are nowadays found in many electronic devices and their integration with digital cameras became a common approach Furthermore the developments in the design of IMUs currently allow a stable This contribution has been peer reviewed The double blind peer review was conducted on the basis of the full paper 317 ISPRS Annals of the Photogrammetry Remote Sensing and Spatial Information Sciences Volume II 5 W1 2013 XXIV International CIPA Symposium 2 6 September 2013 Strasbourg France quite accurate and high frequent several hundred hertz estimation of the
20. nature Schneider 1974 Z roll co Figure 1 Three axes and rotations of a digital still camera The rotation angles of the camera can be obtained by a so called Inertial Measurement Unit IMU or Inertial Reference Unit IRU which consists of accelerometers and gyroscopes Accelerometers measure acceleration in m s or G force g which can be static e g gravity and dynamic i e suddenly slowing down or speeding up Since an accelerometer can measure the amount of static acceleration due to gravity its orientation toward the Earth s surface can be computed Hence accelerometers are often used for tilt sensing SparkFun Electronics 2012a This fact is exploited by all modern digital photo cameras to inform the user if the image was shot in portrait or landscape mode Gyroscopes measure angular velocity i e the speed by which something is spinning around its axis in rotations per minute rpm or degrees per second s Since gyros are not affected by gravity they perfectly complement accelerometers The I IMU s gyros and accelerometers which are rigidly mounted to a common base to maintain the same relative orientation are often complemented by a magnetometer to know the exact direction with respect to magnetic North Often the term Inertial Navigation System INS is coined as it consists of an IMU supplemented with supporting electronics and one or more navigational computers Combining all exterior orientatio
21. raphic coordinates into aerial imagery can be executed using three possible approaches a software a hardware and a hybrid approach In its most simple form i e the software approach the user has to manually or semi automatically input coordinates extracted from Google Earth or any other spatial dataset This approach takes however place after the flight maybe supported by a flight protocol but is not advised for the previously mentioned reasons More handy and accurate is the hybrid soft and hardware solution which tags the photographs with the locations stored in the continuous track log of any external handheld Gobal Navigation Satellite System GNSS receiver or more dedicated GNSS data loggers such as Qstarz s BT Q1000XT Travel Recorder Sony s GPS CSIKA or the GiSTEQ PhotoTrackr Mini After the aerial sortie many commercial or freely available software packages can synchronise both data sources by comparing the time stamped GNSS track with the time of image acquisition stored in the Exif Exchangeable image file format metadata fields of the aerial image Subsequently the coordinates of the corresponding GNSS point commonly called waypoint are written as new location data into the image file or in a separate xmp sidecar file which features the same name as the image file and stores the metadata using Adobe s eXtensible Metadata Platform XMP data model Adobe Systems Incorporated 2013 This contribution has been
22. sing and Spatial Information Sciences Volume II 5 W1 2013 XXIV International CIPA Symposium 2 6 September 2013 Strasbourg France Harvey 2013 to write the complete exterior orientation information directly into the image s metadata Because the Exif 2 3 specification supports GPSImageDirection i e yaw the values for pitch and roll are also written in metadata tags of the GNSS attribute section although they are provided by the IMU APM 2 0 or a magnetic based compass Solmeta Geotagger Pro 2 see section 4 and have nothing to do with the GNSS signal The second method creates an additional XMP sidecar file with the same name as the image file and the xmp extension Both methods have pros and cons e g the first method does not create additional files but only a small number of software packages can read all embedded and non standard metadata tags Since both approaches are implemented in the presented post processing software different image processing workflows can be accommodated 3 MOUNTING CALIBRATION Due to the fact that the APM 2 0 is mounted on the camera s hot shoe the exact position and orientation of its sensors is not the same as for the camera Figure 3 Additionally the attitude relationship between the APM 2 0 and the camera will most likely slightly change every time the sensors are mounted on top of the camera A camera mounting calibration also called boresight calibration mathematically describ
23. tures a three axis electronic compass enabling the recording of a more or less accurate heading 2 is quoted while also the roll and the pitch can be stored both accurate to circa 5 in a range of 80 Solmeta Technology 2012 The unit delivers an NMEA 0183 stream a communication standard set by the National Marine Electronics Association which thanks to the physical connection with a ten pin connector enables direct geocoding of the images by embedding image direction as well as geographical latitude longitude and altitude in the appropriate Exif tags Besides the standard hardware based geotagging the Geotagger Pro 2 can log about 5 million waypoints at 1 Hz This log file does not only enable the aforementioned hybrid geocoding approach but is also essential when the user needs the camera s pitch and roll values since these cannot be directly embedded into the image metadata 90 T T T T T T T T T Solmeta Geotagger Pro 2 APM 2 0 a Image m h tease il he 4 Pitch oa a 1 4 1 1 n 1 750 800 850 900 950 1000 1050 1100 1150 1200 Elapsed time sec j A na ELA oe Yl 90 i f 1 i f i f 1 750 800 850 900 950 1000 1050 1100 1150 1200 Elapsed time sec Figure 4 Pitch and roll angles obtained from the Solmeta Geotagger Pro 2 orange APM 2 0 blue and photographs green dots 4 2 First test results Figure 4 depicts the roll and pitch angles that were acquired by the
24. u ca phil exiftool 6 February 2013 InvenSense 2012 MPU 6000 and MPU 6050 Product Specifi cation Revision 3 3 Sunnyvale 54 pp http www invensense com mems gyro documents PS MPU 6000A pdf 18 March 2013 Kraus K 2007 Photogrammetry Geometry from images and laser scans 2nd English ed Walter de Gruyter Berlin New York 459 pp MediaTek Incorporated 2010 MEDIATEK 3329 Datasheet Rev A03 66 channel GPS Engine Board Antenna Module with MTK Chipset http inmotion pt documentation diydrones MediaTek_MT 3329 mediatek_3329 pdf 14 April 2013 Mikhail E M Bethel J S McGlone J C 2001 Introduction to modern photogrammetry Wiley New York ix 479 CD ROM Pfeifer N Glira P Briese C 2012 Direct georeferencing with on board navigation components of light weight UAV platforms in M R Shortis W Wagner J Hyypp Eds Proceedings of the XXII ISPRS Congress Technical Commission VII ISPRS pp 487 492 Schneider S 1974 Luftbild und Luftbildinterpretation Lehr buch der allgemeinen Geographie 11 Walter de Gruyter Berlin New York 530 pp Solmeta Technology 2012 Geotagger Pro 2 Solmeta Technol ogy http www solmeta com Product show id 14 18 March 2013 SparkFun Electronics 2012b Accelerometer Gyro and IMU Buying Guide SparkFun Electronics https www sparkfun com pages accel_gyro_guide 15 October 2012 SparkFun Electronics 2012 OpenLog https www
25. ute for Meteorology and Geodynamic A the office of the provincial government of Lower Austria A Airborne Technologies GmbH A RGZM Romano Germanic Central Museum in Mainz D RAA Swedish National Heritage Board S IBM VISTA University of Birmingham GB and NIKU Norwegian Institute for Cultural Heritage Research N This contribution has been peer reviewed The double blind peer review was conducted on the basis of the full paper 318
26. uynrt a mounting rotation matrix computed for every individual image By averaging the rotation angles of all 33 Rmounr matrices a final mounting rotation matrix Rygyyr Was obtained Finally an image wise multiplication of the estimated mounting matrix with the rotation matrix from the APM 2 0 at the moment of image acquisition yields the orientation angles of the image itself equation 4 Xipmt T R pm t x X PM 0 Xam Ream xS a XCM 2 Ruount t R I RE S 3 f Lt CAM t L pL APM cT XCamt Rapmt Ruount X S 4 where Xhout APM 2 0 in the local horizontal CRS Ripa Rotation matrix from APM 2 0 to the local horizontal CRS AEM Point in the CRS of the APM 2 0 Xk Mt Flipped camera in the local horizontal CRS Ream Rotation matrix from camera to the local horizontal CRS S Flip matrix which rotates the camera s CRS to the APM 2 0 CRS see Figure 3 XCAM Point in the CRS of the camera Ruounrt Mounting matrix based on an individual image R amp M Transposed version of Ripy t Ruyounr Final mounting matrix T Transposed version of S The mounting calibration i e the angles of the final mounting rotation matrix Rygyyr resulted in 0 9 for the roll and 1 4 for the pitch angle Since more work is needed to overcome the limited accuracy of the magnetometer and therefore accurately This contribution has been peer reviewed The double blind peer review was conducted on the basis of the full paper 316
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