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CS766

Proficiency in the material covered in CS 766 is assumed even though the material is not explicitly listed in the reading list below. Content covered in 766 lectures will NOT be tested in separate questions, but knowledge of this material is important to understand the readings as well as to answer the qualifier questions.

Image Segmentation

• D. Comaniciu and P. Meer, Mean shift analysis and applications, Proc. 7th Int. Conf. Computer Vision, pp. 1197-1203, 1999.
• J. Shi and J. Malik, Normalized cuts and image segmentation, IEEE Trans. Pattern Analysis and Machine Intelligence, 22(8), pp. 888-905, 2000.
• M. Kass, A. Witkin, and D. Terzopoulos, Snakes: Active contour models, Int. J. Computer Vision, 1(4), pp. 321-331, 1988.

Optimization Methods in Vision

• V. Kolmogorov and R. Zabih, What energy can be minimized by graph cuts, IEEE Trans. Pattern Analysis and Machine Intelligence, 26(2), pp. 147-159, 2004.
• P. Felzenszwalb and D. Huttenlocher, Efficient belief propagation for early vision, Int. J. Computer Vision, 70(1), pp. 41-54, 2006.
• C. Stewart, Robust parameter estimation in computer vision, SIAM Review, 41(3), pp. 513-537, 1999.

Feature Extraction and Descriptors

• D. Lowe, Distinctive image features from scale-invariant keypoints, Int. J. Computer Vision, 60(2), pp. 91-110, 2004.
• P. Perona and J. Malik, Scale-space and edge detection using anisotropic diffusion, IEEE Trans. Pattern Analysis and Machine Intelligence, 12(7), pp. 629-639, 1990.
• Harris, C. and Stephens, M., A combined corner and edge detector. Proceedings of the 4th Alvey Vision Conference. pp. 147–151.
• N. Dalal and B. Triggs, Histograms of oriented gradients for human detection, Proc. IEEE Conf. Computer Vision and Pattern Recognition, Vol. I, pp. 886-893, 2005.

Object/Scene Recognition and Categorization

• P. Viola and M. Jones, Robust real-time face detection, Int. J. Computer Vision, 57(2), pp. 137-154, 2004.
• M. Turk and A. Pentland, Face recognition using eigenfaces, J. Cognitive Neuroscience, 3(1), pp. 71-86, 1991.
• J. Shotton, A. Fitzgibbon, M. Cook, T. Sharp, M. Finocchio, R. Moore, A. Kipman, and A. Blake, Real-time human pose recognition in parts from single depth images, Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 1297-1304, 2011.
• S. Lazebnik, C. Schmid, and J. Ponce, Beyond bags of features: Spatial pyramid matching for recognizing natural scene categories, Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 2169-2178, 2006.
• K. Grauman and T. Darrell, The pyramid match kernel: Discriminative classification with sets of image features, Proc. 10th Int. Conf. Computer Vision, Vol. 2, pp. 1458-1465, 2005.

Geometry, Shape and Tracking

• R. Hartley and A. Zisserman, Multiple View Geometry in Computer Vision, 2nd ed., Chapters 9, 18 and related background, Cambridge University Press, 2003.
• T. Cootes, G. Edwards, and C. Taylor, Active appearance models, IEEE Trans. Pattern Analysis and Machine Intelligence, 23(6), pp. 681-685, 2001.
• M. Isard and A. Blake, Condensation --- conditional density propagation for visual tracking, Int. J. Computer Vision, 29(1), pp. 5-28, 1998.

Registration, Stereo and Optical Flow

• S. Baker and I. Matthews, Lucas-Kanade 20 years on: A unifying framework, Int. J. Computer Vision, 56(3), pp. 221-255, 2004.
• A. Bruhn, J. Weickert, and C. Schnorr, Lucas/Kanade meets Horn/Schunck: Combining local and global optic flow methods, Int. J. Computer Vision, 61(3), pp. 211-231, 2005.
• V. Kolmogorov and R. Zabih, Multi-camera scene reconstruction via graph cuts, Proc. 7th European Conf. Computer Vision, pp. 82-96, 2002.