Proceedings, XXth congress: Proceedings, XXth congress

Altan, M. Orhan

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Multivolume work

Persistent identifier:: 1663674213

Title:: Proceedings, XXth congress

Sub title:: Istanbul, 12 - 23 July 2004

Year of publication:: 2004

Place of publication:: Istanbul

Publisher of the original:: [Verlag nicht ermittelbar]

Identifier (digital):: 1663674213

Language:: English

Additional Notes:: Erscheinungsdatum des Originals ist aus dem Copyrightjahr ermittelt.; Auch bezeichnet als XXth International Congress for Photogrammetry and Remote Sensing

Editor:: Altan, M. Orhan

Corporations:: International Society for Photogrammetry and Remote Sensing, Congress, 20., 2004, Istanbul; International Society for Photogrammetry and Remote Sensing, Commission Primary Data Acquisition

Adapter:: International Society for Photogrammetry and Remote Sensing, Congress, 20., 2004, Istanbul; International Society for Photogrammetry and Remote Sensing, Commission Primary Data Acquisition

Founder of work:: International Society for Photogrammetry and Remote Sensing, Congress, 20., 2004, Istanbul; International Society for Photogrammetry and Remote Sensing, Commission Primary Data Acquisition

Other corporate:: International Society for Photogrammetry and Remote Sensing, Congress, 20., 2004, Istanbul; International Society for Photogrammetry and Remote Sensing, Commission Primary Data Acquisition

Document type:: Multivolume work

Volume

Persistent identifier:: 166368779X

Title:: Proceedings, XXth congress

Scope:: IV, 226 Seiten

Year of publication:: 2004

Place of publication:: Istanbul

Publisher of the original:: [Verlag nicht ermittelbar]

Identifier (digital):: 166368779X

Illustration:: Illustrationen, Diagramme

Signature of the source:: ZS 312(35,B8)

Language:: English

Additional Notes:: Erscheinungsdatum des Originals ist aus dem Copyrightjahr ermittelt.

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

Editor:: Altan, M. Orhan

Corporations:: International Society for Photogrammetry and Remote Sensing, Congress, 20., 2004, Istanbul; International Society for Photogrammetry and Remote Sensing

Adapter:: International Society for Photogrammetry and Remote Sensing, Congress, 20., 2004, Istanbul; International Society for Photogrammetry and Remote Sensing

Founder of work:: International Society for Photogrammetry and Remote Sensing, Congress, 20., 2004, Istanbul; International Society for Photogrammetry and Remote Sensing

Other corporate:: International Society for Photogrammetry and Remote Sensing, Congress, 20., 2004, Istanbul; 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:: EFFICIENT LINE MATCHING BY IMAGE SEQUENTIAL ANALYSIS FOR URBAN AREA MODELLING Y. Kunii, H. Chikatsu

Document type:: Multivolume work

Structure type:: Chapter

International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B-YF. Istanbul 2004 3.1 Line Extraction Line extraction was performed by Canny operator with 2 threshold values which called the height and reliability of edge. The height of edge is a variation of the gray level around at a interest point, and the reliability is an index for representing influence of noise. The height # and the reliability = are calculated by following equation. (1) (2) where, h,h y : variation of gray level for each direction (x.y) x,y : image coordinate of interest point €, : variance of gray level around at interest point These threshold values were set as h = 10 and r = 0.1 in this paper. Furthermore, both ends of these extracted edges were connected by straight lines. Figure 2 shows the extracted lines by the method for the first image (277 lines). Figure 2. Line extraction 3.2 Optical Flow Estimation In order to perform line matching, both ends for each extracted line were tracked by optical flow. Although many optical flow estimation methods have been proposed, Lucas-Kanade method (Lucas and Kanade, 1981) which is capable of correct and fast procedure was adopted in this paper. The optical flow by Lucas-Kanade method (, v) is calculated by following equation and estimated optical flow is shown in Figure 3. 9L 7(p)-1(p}] w Oy x. 2 .(p)- 1o) Ox ary where, 1(p)=1(x. 1), gd or 25) J(p)= Hx, y.t + ôt) VS ; (3 222 up eec a Ung qM, M uL s A ’ | Me pe cs : | Es ‘ x : x ERN wr Et Jd E e: lL Fl uv QUE as WIR a (MIA PAS : al M rns est n els ais to LM VB eer Doha hi 3 " Jil. D cM : Vat vA Nu hy gt | ja AN yd y a EN ASH NE aee Lo 11r v Age p La en RO i HE E ws ad. il E es F Figure 3. Optical flow estimation 4. LINE MATCHING BY TRIFOCAL TENSOR The unmatched lines by the optical flow estimation were corrected by trifocal tensor in this paper. Details of the line matching by trifocal tensor are as follows. Trifocal tensor is geometric relation of 3 images which contained the same objects from different perspectives. The trifocal tensor is expressed by 3 square matrixes (3x3), these 3 matrixes are T;, T; and T5, components of these matrixes are #;, /5;j and /3;, and image coordinates of matched points for these 3 images are (x), yy, 21), (x2, v2, 22) and (x3, 3, z3). Thus, following equations are obtained by the geometric relation. —25218» + Z,V38 23 + Va238 3 m Y3J3i83; = 0 £48: 72484573584 tJFX 98570 —-ZEG T7 XESTXQE,-0 T 2273811 + Z8 re X2375831 7 X2ME33 = 0 where, gy; Xf t Yi t zf 163 These 4 equations are generated by one conjugated point of these 3 images. The trifocal tensor has 27(73x3x3) unknown parameters which can be calculated by more than the same number of equations. Therefore, more than 7 points needed to be conjugated between these 3 images for acquisition of the trifocal tensor. Consequently, the unmatched points in the third image are calculated by the above equation. 5. RESULTS OF LINE MATCHING In order to evaluate performance of the proposal line matching method, line matching in general stereo matching methods such as LSM (Gruen, 1985), probabilistic relaxation (Rosenfeld, et al, 1976) and area correlation (Schenk, 2001) was also investigated, and performance of the proposal method was compared with these general methods. Table 2 shows results of line matching by each method. The line matching by proposal method could be performed efficiently more than other general methods. Consequently, the optical flow estimation and the trifocal tensor is useful method for line matching by image sequences. Figure 4 shows result of line matching by the proposal method. In pr ne ur th re us m: pa or pe ep Fu ep ab We ste Ta for

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