XXII ISPRS Congress 2012: Technical Commission VII

Bibliographic data

Multivolume work

Persistent identifier:: 1663813779

Title:: XXII ISPRS Congress 2012

Sub title:: Melbourne, Australia, 25 August-1 September 2012

Year of publication:: 2013

Place of publication:: Red Hook, NY

Publisher of the original:: Curran Associates, Inc.

Identifier (digital):: 1663813779

Language:: English

Additional Notes:: Kongress-Thema: Imaging a sustainable future

Corporations:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Adapter:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Founder of work:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Other corporate:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Document type:: Multivolume work

Volume

Persistent identifier:: 1663821976

Title:: Technical Commission VII

Scope:: 546 Seiten

Year of publication:: 2013

Place of publication:: Red Hook, NY

Publisher of the original:: Curran Associates, Inc.

Identifier (digital):: 1663821976

Illustration:: Illustrationen, Diagramme

Signature of the source:: ZS 312(39,B7)

Language:: English

Additional Notes:: Erscheinungsdatum des Originals ist ermittelt.; Literaturangaben

Usage licence:: Attribution 4.0 International (CC BY 4.0)

Corporations:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Adapter:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Founder of work:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Other corporate:: International Society for Photogrammetry and Remote Sensing, Congress, 22., 2012, Melbourne; International Society for Photogrammetry and Remote Sensing

Publisher of the digital copy:: Technische Informationsbibliothek Hannover

Place of publication of the digital copy:: Hannover

Year of publication of the original:: 2019

Document type:: Volume

Collection:: Earth sciences

Chapter

Title:: [VII/7, III/2, V/1, V/3, ICWG V/I: LOW-COST UAVS (UVSS) AND MOBILE MAPPING SYSTEMS]

Document type:: Multivolume work

Structure type:: Chapter

Chapter

Title:: AUTOMATIC EXTERIOR ORIENTATION PROCEDURE FOR LOW-COST UAV PHOTOGRAMMETRY USING VIDEO IMAGE TRACKING TECHNIQUE AND GPS INFORMATION T. Anai, T. Sasaki, K. Osaragi, M. Yamada, F. Otomo, H. Otani

Document type:: Multivolume work

Structure type:: Chapter

Figure 6. Example of OCM 2.4 Robust Common Feature Point Tracking Figure 7 show the flow of robust tracking procedure of common feature points. At the first, detection of common feature points on first high resolution still image is performed by OCR. The image coordinate of each detected common feature are converted to the image coordinates on synchronized video frame. The tracking of common feature points is performed on video image sequences until the next still image is detected. On the next still image, image coordinates of tracked common feature points are converted to next high resolution still image, and also the detection of common feature points is performed. This procedure is performed until the final still image. Detection of Common Feature Points on Still Image (OCR) Y Convert Image Coordinate on Synchronized video frame. v Matching of Common Feature Point on Video Image «— (OCM) y Detection of Outlier in Matching Result (computation of transform between each frame using LMeds) ef no | Convert Image Coordinate on Still Image. | Final Still Image ? yes Sub Pixel Matching on Still Image (LSM) Candidate of Pass Point Figure 7. Flow of Robust Tracking Procedure International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B7, 2012 XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia The matching of common feature points between each video frame is performed by OCM in this procedure. Therefore, almost points are matched correctly, but generally include some error as outlier in main transformation between each video frames. Therefore, detection of outlier in common feature points is necessary to perform. In this procedure, authors assume that the transformation between each video frame is approximated with affine transformation as following equation, WU; SAU; + Ay; + A (5) Via = au; + asv; + ac Where a;-ag:affine parameter, (u, v):image coordinate at frame i. The affine parameters a,-as are calculated using LMedS method and the outlier of matching is eliminated automatically. Finally, in order to perform the sub-pixel matching, Least Square Matching (LSM) of each common feature points on each still image is performed. In this LSM processing, forward and backward matching is performed for the checking of LSM result. This means that the result of forward (e.g. from left image to right image) matching and backward (e.g. from right image to left image) matching has large difference, the matching results of this point is removed as error correspondence. The good results of this sub-pixel matching procedure are used as the candidate of correct pass points in following procedures. 2.5 Tie Point Matching In order to perform adjusting between each flight line, tie point matching using candidate pass points is performed. Figure 8 shows the flow of tie point matching procedure. At the first, exterior orientation only using candidate pass points is performed. The candidate pass points that have large residual of image coordinate are removed in this step. As the result of this exterior orientation, 3D coordinate of each candidate pass points and exterior orientation parameter for each still image are obtained in arbitrarily position and scale. From this 3D geometry information, the 3D coordinate of each candidate pass point can perform back projection to 2D image coordinate on each still image. Therefore, the tie point matching is performed in the ROI that located around back projection 2D image coordinate of candidate pass points on still image by using LSM. Finally, exterior orientation is computed again using pass points and tie points. Exterior Orientation using Candidate Pass Points } Set ROI around Back Projection Coordinate i Tie Point Matching by LSM i Exterior Orientation using Pass Points and Tie Points Figure 8. Tie Point Matching Procedure

Access restriction

Copyright

fullscreen: Technical Commission VII (B7)

Multivolume work

Volume

Chapter

Chapter

Table of contents

Cite and reuse

Volume

Chapter

Image

Image fragment

Citation links

Citation recommendation