Occlusion Boundary Detection for Video Sequences Based on Unsupervised Online Learning

Zhang Shihui; Wang Ruiyu; He Huan

doi:10.3788/aos201535.1215001

[1] A S Ogale, C Fermüller, Y Aloimonos. Motion segmentation using occlusions[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2005, 27(6): 988-992.

[2] D Feldman, D Weinshall. Motion segmentation and depth ordering using an occlusion detector[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2008, 30(7): 1171-1185.

[3] Wang Wei, Yu Zhijing, Guo Yin, et al.. Study on the occlusion problem in dynamic space intersection measurement with multi-camera systems[J]. Acta Optica Sinica, 2014, 34(4): 0415003.

[4] A N Stein, M Hebert. Local detection of occlusion boundaries in video[J]. Image and Vision Computing, 2009,27(5):514-522.

[5] N Apostoloff, A Fitzgibbon. Learning spatiotemporal T-junctions for occlusion detection[C]. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. IEEE, 2005: II553-II559.

[6] A N Stein, M Hebert. Occlusion boundaries from motion: Low-level detection and mid-level reasoning[J]. International Journal of Computer Vision, 2009, 82(3): 325-357.

[7] M E Sargin, L Bertelli, B S Manjunath, et al.. Probabilistic occlusion boundary detection on spatio-temporal lattices[C]. Proceedings of the IEEE International Conference on Computer Vision. IEEE, 2009: 560-657.

[8] X He, A Yuille. Occlusion boundary detection using pseudo-depth[C]. Proceedings of the European Conference on Computer Vision. Springer, 2010: 539-552.

[9] D Chen, Z Yuan, G Zhang, et al.. Detecting occlusion boundaries via saliency network[C]. Proceedings of International Conference on Pattern Recognition. IEEE, 2012: 2569-2572.

[10] N Jacobson, Y Freund, T Q Nguyen. An online learning approach to occlusion boundary detection[J]. IEEE Transactions on Image Processing,2012,21(1):252-261.

[11] A Ayvaci, M Raptis, S Soatto. Sparse occlusion detection with optical flow[J]. International Journal of Computer Vision, 2012, 97(3): 322- 338.

[12] L Xu, J Jia, Y Matsushita. Motion detail preserving optical flow estimation[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2012, 34(9): 1744-1757.

[13] D Sun, S Roth, M Black. Secrets of optical flow estimation and their principles[C]. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, IEEE. 2010: 2432-2439.

[14] B K P Horn, B G Schunck. Determining optical flow[J]. Artificial Intelligence, 1981, 17(1-3): 185-203.

[15] A Bruhn, J Weickert. Towards ultimate motion estimation: Combining highest accuracy with real-time performance[C]. Proceedings of the IEEE International Conference on Computer Vision, IEEE. 2005: 749-755.

[16] Y Freund, R E Schapire, Y Singer, et al.. Using and combining predictors that specialize[C]. Proceedings of the Annual ACM Symposium on Theory of Computing. ACM, 1997: 334-343.

[17] N C Oza. Online bagging and boosting[C]. IEEE International Conference on Systems, Man and Cybernetics. IEEE, 2005: 2340-2345.

[18] H Grabner, H Bischof. On-line boosting and vision[C]. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. IEEE, 2006: 260-267.

[19] P Sundberg, T Brox, M Maire, et al.. Occlusion boundary detection and figure/ground assignment from optical flow[C]. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. IEEE, 2011: 2233-2240.