結論與未來發展 - 相機陣列影像縫合之快速校正技術

近年來相機校正技術因為需要輔助校正物且機器的精確性誤差的關係，因此影像縫合技術在相機校正領域佔有越來越重要的地位。於本篇論文所談到的 BUMS(Bottom-Up Maxima Selection) 和 PRSC(Polarized Random Sample Consensus)快速演算法，因為在擷取特徵點的時候由內外往外擴散慢慢刪除，並統、軍事系統、Scene Motion、透視圖等等，如圖 5-1。如圖 5-1(a)顯示利用相機陣列監視一片樹叢，圖 5-1(b)顯示使用相機陣列校正技術透視後面的影像，

圖 5-1.2 為一個多 sensor 的平台範例，每個刻度彼此之間相隔 30 度，並且在每個刻度之間嵌入一個 Sensor，透過這種方式使得彼此之間的關係固定，

達到我們想要的固定 H 關係，但因為 Sensor 彼此的相對高度上也會有有些微誤差，因此此平台仍然有改良的空間。圖 5-1.3 為用此平台所攝影的其中一組相片及其縫合影像。最後，在我們的演算法中仍然有少數 Pattern 是會縫合失敗的，

如圖 5-1.4。我們會發現兩張影像的縫合結果是成功的，但是三張影像的縫合結果是失敗的，會造成失敗的原因可能是因為相機與影像的焦距過近所導致，因為焦距很近時，把相機移動一點點就會使得影像的 Pixel 偏移很多，原本被擷取到的特徵點在相機移動後可能就變得不是特徵點了，這部份也是值得我們未來繼續探討的。

(a) (b)

(a)影像一 (b)影像二 (c)影像三

(d)成功縫合兩張影像 (e)失敗地縫合三張影像圖 5-1.4 焦距過近的縫合影像

參考文獻：

[1] C. Rother and S. Carlsson. Linear multi view reconstruction and camera recovery using a reference plane. International Journal of Computer Vision, 49(2/3):117–141, 2002.

[2] B. Bascle, A. Blake, and A. Zisserman. Motion deblurring and super-resolution from and image sequence. In Proceedings of the 4th European Conference on Computer Vision (ECCV96), pages 312–320. Springer-Verlag, 1996.

[3] D. Capel and A. Zisserman. Automated mosaicing with super-resolution zoom.

In Proceedings of the Interational Conference on Computer Vision and Pattern Recognition (CVPR98), pages 885–891, June 1998.

[4] J. Davis. Mosaics of scenes with moving objects. In Proceedings of the Interational Conference on Computer Vision and Pattern Recognition (CVPR98), pages 354–360, 1998.

[5] M. Uyttendaele, A. Eden, and R. Szeliski. Eliminating ghosting and exposure artifacts in image mosaics. In Proceedings of the Interational Conference on Computer Vision and Pattern Recognition (CVPR01), volume 2, pages 509–516, Kauai, Hawaii, December 2001.

[6] A. Agarwala, M. Dontcheva, M. Agarwala, S. Drucker, A. Colburn, B. Curless, D. Salesin, and M. Cohen. Interactive digital photomontage. In ACM Transactions on Graphics (SIGGRAPH’ 04), 2004.

[7] D. Brown. Close-range camera calibration. Photogrammetric Engineering, 37(8):855–866, 1971.

[8] D.B. Goldman and J.H. Chen. Vignette and exposurecalibation and compensation. In Proceedings of the 10th International Conference on Computer Vision (ICCV05), pages I: 899–906, 2005.

[9] P. Debevec and J. Malik. Recovering high dynamic range radiance maps from

photographs. Computer Graphics, 31:369–378, 1997.

[10] H. Seetzen, W. Heidrich, W. Stuerzlinger, G. Ward, L. Whitehead, M.

Trentacoste, A. Ghosh, and A. Vorozcovs. High dynamic range display systems.

In ACM Transactions on Graphics (SIGGRAPH’04), 2004.

[11] R. Szeliski and S. Kang. Direct methods for visual scene reconstruction. In IEEE Workshop on Representations of Visual Scenes, pages 26–33, Cambridge, MA, 1995.

[12] M. Irani and P. Anandan. About direct methods. In B. Triggs, A. Zisserman, and R. Szeliski, editors, Vision Algorithms: Theory and Practice, number 1883 in LNCS, pages 267–277. Springer-Verlag, Corfu, Greece, September 1999.

[13] H. Sawhney and R. Kumar. True multi-image alignment and its application to mosaicing and lens distortion correction. IEEE Transactions on Pattern Analysis and Machine Intelligence, 21(3):235–243, 1999.

[14] H. Shum and R. Szeliski. Construction of panoramic mosaics with global and local alignment.International Journal of Computer Vision,36(2):101–130, February 2000.

[15] I. Zoghlami, O. Faugeras, and R. Deriche. Using geometric corners to build a 2D mosaic from a set of images. In Proceedings of the International Conference on Computer Vision and Pattern Recognition, Puerto Rico. IEEE, June 1997.

[16] P. McLauchlan and A. Jaenicke. Image mosaicing using sequential bundle adjustment. Image and Vision Computing, 20(9-10):751–759, August 2002.

[17] R. Szeliski. Image Alignment and Stitching: A Tutorial1 Preliminary draft, September 27, 2004 Technical Report.MSR-TR-2004-92.

[18] Chen, S. E. QuickTime VR – an image-based approach to virtual environment navigation. Computer Graphics (SIGGRAPH’95), , 29–38. 1995.

[19] Szeliski, R. Image mosaicing for tele-reality applications. In IEEE Workshop on

Applications of Computer Vision (WACV’94), pages 44–53, IEEE Computer Society, Sarasota. 1994.

[20] Szeliski, R. Creating Full View Panoramic Image Mosaics and Environment Maps. Microsoft Research.

[21] irahu http://www.irahul.com/workzone/stitch/index.php

[22] P. Heckbert. Projective Mappings for Image WarpingRendering, 15-862 .26 Sept 1995.

[23] C. Harris and M.J. Stephens. A combined corner and edge detector. In Alvey Vision Conference, pages 147–152, 1988.

[24] H. Moravec. Obstacle avoidance and navigation in the real world by a seeing robot rover. Technical Report CMU-RI-TR-3, Carnegie-Mellon University, Robotics Institute, 1980.

[25] C. Schmid, R. Mohr, and C. Bauckhage. Evaluation of interest point detectors.

International Journal of Computer Vision, 37(2):151–172, June 2000.

[26] G. Derpanis. The Harris Corner Detector, October 27, 2004.

[27] M. Brown, R. Szeliski, and S. Winder. Multiimage matching using multi-scale oriented patches. In Proceedings of the Interational Conference on Computer Vision and Pattern Recognition (CVPR05), San Diego, June 2005.

[28] D. Lowe. Distinctive image features from scale-invariant keypoints.

International Journal of Computer Vision, 60(2):91–110, 2004.

[29] J. Shi and C. Tomasi. Good features to track. In Proceedings of the Interational Conference on Computer Vision and Pattern Recognition (CVPR94), Seattle, June 1994.

[30] Y. Ke1, R. Sukthankar. PCA-SIFT: A More Distinctive Representation for Local Image Descriptors. Intel Research Pittsburgh In Proceedings of the Interational Conference on Computer Vision and Pattern Recognition

(CVPR04).

[31] D. Lowe, "Object recognition from local scale-invariant features," International Conference on Computer Vision, Corfu, Greece (September 1999), pp.

1150-1157.

[32] D. Lowe, "Local feature view clustering for 3D object recognition," IEEE Conference on Computer Vision and Pattern Recognition, Kauai, Hawaii (December 2001), pp. 682-688.

[33] M. Fischler and R. Bolles. Random sample consensus: A paradigm for model fitting with application to image analysis and automated cartography.

Communications of the ACM, 24:381–395, 1981.

[34] P. Torr. Bayesian model estimation and selection for epipolar geometry and generic manifold fitting. International Journal of Computer Vision, 50(1):35–61, 2002.

[35] R. Hartley and A. Zisserman. Multiple View Geometry in Computer Vision.

Cambridge University Press, ISBN: 0521540518, second edition, 2004.

[36] M. Brown, D. Lowe. Automatic Panoramic Image Stitching using Invariant Features. International Journal of Computer Vision(ijcv),2007.

[37] M. Brown and D. Lowe. Recognising panoramas. In Proceedings of the 9th International Conference on Computer Vision (ICCV03), volume 2, pages 1218–1225, Nice, October 2003.

[38] J. Beis and D. Lowe. Shape indexing using approximate nearest-neighbor search in highdimensional spaces. In Proceedings of the Interational Conference on Computer Vision and Pattern Recognition (CVPR97), pages 1000–1006, 1997.

[39] P. Burt and E. Adelson. A multiresolution spline with application to image mosaics. ACM Transactions on Graphics, 2(4):217–236, 1983.

[40] ROGER Y. TSAI. A Versatile Camera Calibration Technique for 3D Machine

Vision. IEEE J. Robotics & Automation, RA-3, No. 4, August 1987, pp.

323-344.

[41] Zhengyou Zhang. A Flexible New Technique for Camera Calibration. December 2, 1998. Technical Report.MSR-TR-98-71.

[42] http://mpac.ee.ntu.edu.tw/~ck/project_panorama/#SIFTTutorial

[43] http://www.csie.ntu.edu.tw/~cyy/courses/vfx/05spring/assignments/proj2/

[44] B. Wilbum and N. Joshi. High Performance Imaging Using Large Camera Arrays.In ACM Transactions on Graphics, Vol 24, No 3, July 2005, pp. 765-776

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