The most cited papers in Computer Vision

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Transcription:

COMPUTER VISION, PUBLICATION The most cited papers in Computer Vision In Computer Vision, Paper Talk on February 10, 2012 at 11:10 pm by gooly (Li Yang Ku) Although it s not always the case that a paper cited more would be better, a highly cited paper usually indicates that something interesting have been discovered. There s usually no harm to take a further look at them. The following are the papers, which I known, cited most in Computer Vision. Cited by 14455 A theory for multiresolution signal decomposition: The wavelet representation SG Mallat Pattern Analysis and Machine Intelligence, IEEE, 1989 Cited by 13235 A computational approach to edge detection J Canny Pattern Analysis and Machine Intelligence, IEEE, 1986 Cited by 12841

Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images Geman and Geman - Pattern Analysis and Machine, 1984 Cited by 12801 + 4129 (Object recognition from local scale-invariant features) Distinctive image features from scale-invariant keypoints DG Lowe - International journal of computer vision, 2004 Cited by 12251 Snakes: Active contour models M Kass, A Witkin, Demetri Terzopoulos - International journal of computer, 1988 Cited by 9358 + 3206 (Face Recognition using Eigenfaces) Eigenfaces for Recognition Turk and Pentland, Journal of cognitive neuroscience Vol. 3, No. 1, Pages 71-86, 1991 (9358 citations) Cited by 6958 Determining optical flow B.K.P. Horn and B.G. Schunck, Artificial Intelligence, vol 17, pp 185-203, 1981 Cited by 6291 Scale-space and edge detection using anisotropic diffusion P Perona, J Malik Pattern Analysis and Machine Intelligence, IEEE Transactions on 12 (7), 629-639 Cited by 5632 An iterative image registration technique with an application to stereo vision B. D. Lucas and T. Kanade (1981), An iterative image registration technique with an application to stereo vision. Proceedings of Imaging Understanding Workshop, pages 121 130 Cited by 5626 + 3540 (Robust real time face detection) Rapid object detection using a boosted cascade of simple features P Viola, M Jones Computer Vision and Pattern Recognition, 2001. CVPR 2001. Proceedings of the Cited by 5476

Normalized cuts and image segmentation J Shi, J Malik Pattern Analysis and Machine Intelligence, IEEE Transactions on 22 (8), 888-905 Cited by 4004 The Laplacian pyramid as a compact image code Burt and Adelson, - Communications, IEEE Transactions on, 1983 Cited by 3897 Condensation conditional density propagation for visual tracking M Isard and Blake - International journal of computer vision, 1998 Cited by 3746 Good features to track Shi and Tomasi, 1994. Proceedings CVPR 94., 1994 IEEE, 1994 Cited by 3282 Neural network-based face detection HA Rowley, S Baluja, Takeo Kanade - Pattern Analysis and, 1998 Cited by 3009 Histograms of oriented gradients for human detection N Dalal 2005. CVPR 2005. IEEE Computer Society, 2005 Cited by 2647 Emergence of simple-cell receptive field properties by learning a sparse code for natural images BA Olshausen - Nature, 1996 Cited by 2588 Shape matching and object recognition using shape contexts S Belongie, J Malik, J Puzicha Pattern Analysis and Machine Intelligence, IEEE Transactions on 24 (4), 509-522 Cited by 2382

A performance evaluation of local descriptors K Mikolajczyk, C Schmid Pattern Analysis and Machine Intelligence, IEEE Transactions on 27 (10.. Cited by 2360 Fast approximate energy minimization via graph cuts Y Boykov, O Veksler, R Zabih Pattern Analysis and Machine Intelligence, IEEE Transactions on 23 (11. Cited by 2151 The structure of images JJ Koenderink - Biological cybernetics, 1984 Springer Cited by 2147 Shape and motion from image streams under orthography: a factorization method Tomasi and Kanade - International Journal of Computer Vision, 1992 Cited by 1889 Active appearance models TF Cootes, GJ Edwards Pattern Analysis and, 2001 Cited by 1819 Surf: Speeded up robust features H Bay, T Tuytelaars Computer Vision ECCV 2006, 2006 Cited by 1767 Scale & affine invariant interest point detectors K Mikolajczyk, C Schmid International journal of computer vision 60 (1), 63-86 Cited by 1764 Modeling and rendering architecture from photographs: A hybrid geometry-and imagebased approach PE Debevec, CJ Taylor, J Malik Proceedings of the 23rd annual conference on Computer graphics and Cited by 1648

Feature extraction from faces using deformable templates AL Yuille, PW Hallinan International journal of computer, 1992 Cited by 1647 Region competition: Unifying snakes, region growing, and Bayes/MDL for multiband image segmentation SC Zhu, A Yuille Pattern Analysis and Machine Intelligence, IEEE Transactions on 18 (9), 884-900 Cited by 1494 Beyond bags of features: Spatial pyramid matching for recognizing natural scene categories S Lazebnik, C Schmid, J Ponce Computer Vision and Pattern Recognition, 2006 IEEE Computer Society Cited by 1458 Object class recognition by unsupervised scale-invariant learning R Fergus, P Perona, A Zisserman Computer Vision and Pattern Recognition, 2003. Proceedings. 2003 IEEE Cited by 1417 Recovering high dynamic range radiance maps from photographs PE Debevec, J Malik ACM SIGGRAPH 2008 classes, 31 Cited by 1258 A comparison of affine region detectors K Mikolajczyk, T Tuytelaars, C Schmid, A Zisserman, J Matas, F Schaffalitzky International journal of computer vision 65 (1), 43-72 Cited by 1138 Efficient graph-based image segmentation PF Felzenszwalb International Journal of Computer, 2004 Cited by 1131

A bayesian hierarchical model for learning natural scene categories L Fei-Fei Computer Vision and Pattern, 2005 Note that the ones I listed are just the ones that came up to my mind, let me know if I missed any important publications; I would be glad to make the list more complete.