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[184] G. Hager and P. Belhumeur. Real-time tracking of image regions with changes in geom-
etry and illumination. In IEEE Computer Society Conference on Computer Vision and
Pattern Recognition (CVPR) , 1996.
[185] O. Hall-Holt and S. Rusinkiewicz. Stripe boundary codes for real-time structured-light
range scanning of moving objects. In IEEE International Conference on Computer Vision
(ICCV) , 2001.
[186] C. Harris and M. Stephens. A combined corner and edge detector. In Alvey Vision
Conference , 1988.
[187] R. Hartley. Theory and practice of projective rectification. International Journal of
Computer Vision , 35(2):115-27, Nov. 1999.
[188] R. Hartley and A. Zisserman. Multiple View Geometry in Computer Vision . Cambridge
University Press, 2nd edition, 2004.
[189] R. I. Hartley and P. Sturm. Triangulation. Computer Vision and Image Understanding ,
68(2):146-57, Nov. 1997.
[190] N. Hasler, B. Rosenhahn, T. Thormahlen, M. Wand, J. Gall, and H.-P. Seidel. Marker-
less motion capture with unsynchronized moving cameras. In IEEE Computer Society
Conference on Computer Vision and Pattern Recognition (CVPR) , 2009.
[191] J. Hays and A. A. Efros. Scene completion using millions of photographs. In ACM
SIGGRAPH (ACM Transactions on Graphics) , 2007.
[192] K. He, J. Sun, and X. Tang. Fast matting using large kernel matting Laplacian matrices. In
IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR) ,
2010.
[193] X. He and P. Niyogi. Locality preserving projections. In Advances in Neural Information
Processing Systems , 2003.
[194] L. Herda, P. Fua, R. Plänkers, R. Boulic, and D. Thalmann. Using skeleton-based tracking
to increase the reliability of opticalmotioncapture. HumanMovement Science , 20(3):313-
41, June 2001.
[195] L. Herda, R. Urtasun, and P. Fua. Hierarchical implicit surface joint limits to constrain
video-based motion capture. In European Conference on Computer Vision (ECCV) , 2004.
[196] C. Hernandez, G. Vogiatzis, and R. Cipolla. Multiview photometric stereo. IEEE Transac-
tions on Pattern Analysis and Machine Intelligence , 30(3):548-54, Mar. 2008.
[197] A. Hertzmann, C. E. Jacobs, N. Oliver, B. Curless, and D. H. Salesin. Image analogies. In
ACM SIGGRAPH (ACM Transactions on Graphics) , 2001.
[198] V. Hiep, R. Keriven, P. Labatut, and J.-P. Pons. Towards high-resolution large-scale
multi-view stereo. In IEEE Computer Society Conference on Computer Vision and Pattern
Recognition (CVPR) , 2009.
[199] P. Hillman, J. Hannah, and D. Renshaw. Semi-automatic foreground/background seg-
mentation of motion picture images and image sequences. IEE Proceedings on Vision,
Image, and Signal Processing , 152(4):387-97, Aug. 2005.
[200] H. Hirschmüller and D. Scharstein. Evaluation of stereo matching costs on images with
radiometric differences. IEEE Transactions on Pattern Analysis andMachine Intelligence ,
31(9):1582-99, Sept. 2009.
[201] M. Holden. A review of geometric transformations for nonrigid body registration. IEEE
Transactions on Medical Imaging , 27(1):111-28, Jan. 2008.
[202] R. Horaud and G. Csurka. Self-calibration and Euclidean reconstruction using motions
of a stereo rig. In IEEE Computer Society Conference on Computer Vision and Pattern
Recognition (CVPR) , 1998.
[203] B. K. Horn and B. G. Schunck. Determining optical flow. Artificial Intelligence , 17(1-
3):185-203, Aug. 1981.
[204] E. Horn and N. Kiryati. Toward optimal structured light patterns. In International
Conference on 3-D Digital Imaging and Modeling (3DIM) , 1997.
[205] M.-K. Hu. Visual pattern recognition by moment invariants. IRE Transactions on
Information Theory , 8(2):179-87, Feb. 1962.
[206] P. S. Huang, C. Zhang, and F.-P. Chiang. High-speed 3-D shape measurement based on
digital fringe projection. Optical Engineering , 42(1):163-8, Jan. 2003.
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