Discriminative segment annotation in weakly labeled video

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Volumn , Issue , 2013, Pages 2483-2490

  Tang, Kevin ^a,b   Sukthankar, Rahul ^a   Yagnik, Jay ^a   Fei Fei, Li ^b  

^a GOOGLE INC   (United States)

^b Stanford University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

INTERNET CONTENT; INTERNET VIDEO; SEGMENTATION RESULTS; SUPERVISED ALGORITHM; TRADITIONAL APPROACHES; TRAINING DATA; VISION COMMUNITIES; VISUAL CONCEPT;

IMAGE SEGMENTATION; INTERNET; PATTERN RECOGNITION;

CRANES;

EID: 84887363653     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2013.321     Document Type: Conference Paper

References (33)

1. K. Ali, D. Hasler, and F. Fleuret. FlowBoost-Appearance learning from sparsely annotated video. In CVPR, 2011. 3
2. W. Brendel and S. Todorovic. Learning spatiotemporal graphs of human activities. In ICCV, 2011. 2
3. T. Brox and J. Malik. Object segmentation by long term analysis of point trajectories. In ECCV, 2010. 1, 2
4. R. Chaudhry et al. Histograms of oriented optical flow and Binet-Cauchy kernels on nonlinear dynamical systems for the recognition of human actions. In CVPR, 2009. 5
5. Y. Chen, J. Bi, and J. Wang. MILES: Multiple-instance learning via embedded instance selection. PAMI, 28(12), 2006. 2
6. T. Deselaers, B. Alexe, and V. Ferrari. Localizing objects while learning their appearance. In ECCV, 2010. 3
7. J. C. Duchi and Y. Singer. Boosting with structural sparsity. In ICML, 2009. 5
8. M. Everingham et al. The Pascal visual object classes (VOC) challenge. IJCV, 2010. 5
9. R.-E. Fan et al. LIBLINEAR: A library for large linear classification. JMLR, 9, 2008. 6
10. M. Grundmann, V. Kwatra, M. Han, and I. A. Essa. Efficient hierarchical graph-based video segmentation. In CVPR, 2010. 1, 2, 3
11. G. Hartmann, M. Grundmann, J. Hoffman, D. Tsai, V. Kwatra, O. Madani, S. Vijayanarasimhan, I. A. Essa, J. M. Rehg, and R. Sukthankar. Weakly supervised learning of object segmentations from web-scale video. In ECCV Workshop on Vision in Web-Scale Media, 2012. 1, 2, 4, 6, 7, 8
12. Y. Ke, R. Sukthankar, and M. Hebert. Event detection in crowded videos. In ICCV, 2007. 2
13. Y. Lee, J. Kim, and K. Grauman. Key-segments for video object segmentation. In ICCV, 2011. 2
14. C. Leistner et al. Improving classifiers with unlabeled weakly-related videos. In CVPR, 2011. 3
15. J. Lezama, K. Alahari, J. Sivic, and I. Laptev. Track to the future: Spatio-temporal video segmentation with long-range motion cues. In CVPR, 2011. 1, 2
16. J. C. Niebles, C.-W. Chen, and L. Fei-Fei. Modeling temporal structure of decomposable motion segments for activity classification. In ECCV, 2010. 1
17. J.-C. Niebles, B. Han, A. Ferencz, and L. Fei-Fei. Extracting moving people from internet videos. In ECCV, 2008. 2
18. T. Ojala, M. Pietikainen, and D. Harwood. Performance evaluation of texture measures with classification based on Kullback discrimination of distributions. In ICPR, 1994. 5
19. B. Ommer, T. Mader, and J. Buhmann. Seeing the objects behind the dots: Recognition in videos from a moving camera. IJCV, 83(1), 2009. 3
20. A. Prest, C. Leistner, J. Civera, C. Schmid, and V. Ferrari. Learning object class detectors from weakly annotated video. In CVPR, 2012. 1, 2, 5, 6, 8
21. D. Ramanan, D. Forsyth, and K. Barnard. Building models of animals from video. PAMI, 28(8), 2006. 3
22. C. Rother et al. GrabCut: interactive foreground extraction using iterated graph cuts. Trans. Graphics, 23(3), 2004. 7
23. P. Siva, C. Russell, and T. Xiang. In defence of negative mining for annotating weakly labelled data. In ECCV, 2012. 2, 3, 4, 5, 7
24. K. Tang et al. Shifting weights: Adapting object detectors from image to video. In NIPS, 2012. 5
25. K. Tang, L. Fei-Fei, and D. Koller. Learning latent temporal structure for complex event detection. In CVPR, 2012. 1
26. A. Vezhnevets, V. Ferrari, and J. M. Buhmann. Weakly supervised structured output learning for semantic segmentation. In CVPR, 2012. 3
27. S. Vicente, V. Kolmogorov, and C. Rother. Cosegmentation revisited: Models and optimization. In ECCV, 2010. 3
28. P. Viola, J. Platt, and C. Zhang. Multiple instance boosting for object detection. In NIPS, 2005. 2, 5
29. X. Wang, T. X. Han, and S. Yan. An HOG-LBP human detector with partial occlusion handling. In ICCV, 2009. 5
30. J. Xiao and M. Shah. Motion layer extraction in the presence of occlusion using graph cuts. PAMI, 27(10), 2005. 2
31. C. Xu, C. Xiong, and J. Corso. Streaming hierarchical video segmentation. In ECCV, 2012. 2
32. Z.-J. Zha et al. Joint multi-label multi-instance learning for image classification. In CVPR, 2008. 2
33. Z.-H. Zhou and M.-L. Zhang. Multi-instance multi-label learning with application to scene classification. In NIPS, 2007. 2