|
References [1] C.-F. Juan, C.-M. Chang, J.-R. Wu, and D. Lee, “Computer vision based human body segmentation and posture estimation,” IEEE Trans. Syst., Man, Cybern. A, Syst., Humans, vol. 39, no. 1, pp. 119–133, Jan. 2009. [2] R. Cucchiara, C. Grana, A. Prati, and R. Vezzani, “Probabilities posture classification for human-behavior analysis,” IEEE Trans. Syst., Man, Cybern. A, Syst., Humans, vol. 35, no. 1, pp. 42–54, Jan. 2005. [3] J. Shi and J. Malik, “Normalized cuts and image segmentation,” IEEE Trans. on PAMI, 22(8):888–905, 2000. [4] D. Comaniciu and P. Meer, “Mean shift: A robust approach toward feature space analysis,” IEEE Trans. on PAMI, 24:603–619, 2002. [5] D. Martin, C. Fowlkes, and J. Malik, “Learning to detect natural image boundaries using local brightness, color, and texture cues,” IEEE Trans. on PAMI, 26(5):530–549, 2004. [6] Y. Boykov and M.-P. Jolly, “Interactive graph cuts for optimal boundary & region segmentation of objects in n-d images,” In ICCV, 2001. [7] X. Bai and G. Sapiro, “A geodesic framework for fast interactive image and video segemntation and matting,” In ICCV, 2007. [8] L. Grady, “Random walks for image segmentation,” PAMI, 28(11):1768–1783, 2006. [9] T. H. Kim, K. M. Lee and S. U. Lee, “Nonparametric Higher-Order Learning for Interactive Segmentation, ” In CVPR, 2010. [10] Inmar E. Givoni and Brendan J. Frey, “A Binary Variable Model for Affinity Propagation,” Neural Computation, Vol. 21, issue 6, pp 1589-1600, June 2009. [11] S. Maji, Alexander C. Berg, J. Malik, “Classification using Intersection Kernel SVMs is Efficient,” In CVPR, 2008. [12] Shapiro, Linda G.; Stockman, George C. Computer Vision. Upper Saddle River, NJ: Prentice Hall. ISBN 0130307963, 2001. [13] C. Carson, P. H. Torr, H. Greenspan, and J. Malik, “Blob world: Image Segmentation Using EM and Its Application to Image Querying,” IEEE Trans. PAMI, 24(8): 1026-1038, 2002. [14] Olsen, O. and Nielsen, M. ”Multi-scale gradient magnitude watershed segmentation,” Proc. of ICIAP 97, Florence, Italy, Lecture Notes in Computer Science, pages 6–13. Springer Verlag, September 1997. [15] S. Osher and N. Paragios. “Geometric Level Set Methods in Imaging Vision and Graphics, “Springer Verlag, ISBN 0387954880, 2003. [16] Y. Boykov and M.-P. Jolly, “Interactive graph cuts for optimal boundary & region segmentation of objects in n-d images,” In ICCV, 2001. [17] C. Rother, V. Kolmogorov, and A. Blake, “Grabcut-interactive foreground extraction using iterated graph cuts,” In SIGGRAPH, 2004. [18] A. Criminisi, T. Sharp, and A. Blake, “GeoS: Geodesic image segmentation,” In ECCV, 2008. [19] T. H. Kim, K. M. Lee, and S. U. Lee, “Nonparametric Higher-Order Learning for Interactive Segmentation,” In CVPR, 2010. [20] Z. Lin, and L.S. Davis, “Shape-Based Human Detection and Segmentation via Hierarchical Part-Template Matching,” IEEE Trans. PAMI, 32(4): 0162-8828, 2010. [21] Z. Lin, L.S. Davis, D. Doermann, and D. DeMenthon, “Hierarchical Part-Template Matching for Human Detection and Segmentation,” Proc. IEEE ICCV, pp. 1-8, 2007. [22] W. Gao, H. Ai, and S. Lao, “Adaptive Contour Features in Oriented Granular Space for Human Detection and Segmentation,” In CVPR, 2009. [23] P. Viola, M. Jones, and D. Snow, “Detecting pedestrians using pattern of motion and appearance,” In ICCV, 2003. [24] R. Schapire and Y. Singer, “Improved boosting algorithms using confidence-rated predictions,” Machine Learning, 37: 0885-6125, 2004. [25] Z. Lin, L. S. Davis, D. Doermann, and D. DeMenthon, “An Interactive Approach to Pose-Assisted and Appearance-based Segmentation of Humans,” In ICCV, 2007. [26] L. Zhao and L. S. Davis, “Iterative Figure-Ground Discrimination,” In ICPR, 2004. [27] R. Courant and D. Hilbert, “Methods of Math. Physics,” vol. 2. John Wiley and Sons, 1989. [28] R. Merris, Laplacian matrices of graphs: A survey. Linear Algebra and its Applications, 197, 198:143–176, 1994. [29] MIT-CBCL Pedestrian Dataset http://cbcl.mit.edu/cbcl/software-datasets/ PedestrianData .html. [30] INRIA Person Dataset, http://pascal.inrialpes.fr/data/human/. [31] ViSOR Video Surveillance Online Repository, http://www.openvisor.org/. [32] USC Pedestrian Detection Test Set, http://iris.usc.edu/Vision-Users/OldUsers/ bowu/ DatasetWebpage/dataset.html. [33] Affinity Propagation Clustering, http://www.psi.toronto.edu/index.php?q= affinity%20propagation. [34] J. Shotton, J. Winn, C. Rother, and A. Criminisi, “TextonBoost: Joint Appearance, Shape and Context Modeling for Multi-Class Object Recognition and Segmentation,” in ECCV 2006. [35] B. Wu and R. Nevatia, “Simultaneous Object Detection and Segmentation by Boosting Local Shape Feature based Classifier,” in CVPR 2007.
|