Video event detection by inferring temporal instance labels

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

Volumn , Issue , 2014, Pages 2251-2258

  Lai, Kuan Ting ^a,b   Yu, Felix X ^c   Chen, Ming Syan ^a,b   Chang, Shih Fu ^c  

^a NATIONAL TAIWAN UNIVERSITY   (Taiwan)

^b ACADEMIA SINICA   (Taiwan)

^c Department of Earth and Environmental Sciences   (United States)

Author keywords

Multiple Instance Learning; Proportion SVM; Video Event Detection

Indexed keywords

LARGE DATASET; SUPPORT VECTOR MACHINES;

CLASSIFICATION MODELS; MULTIPLE INSTANCE LEARNING; OPTIMAL SOLUTIONS; POSITIVE INSTANCES; PROPORTION SVM; TEMPORAL INTERVALS; TRADITIONAL APPROACHES; VIDEO EVENT DETECTIONS;

PATTERN RECOGNITION;

EID: 84911413388     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2014.288     Document Type: Conference Paper

References (27)

1. S. Andrews, I. Tsochantaridis, and T. Hofmann. Support vector machines for multiple-instance learning. In NIPS, 2002.
2. S. Bhattacharya, F. X. Yu, and S.-F. Chang. Minimally needed evidence for complex event recognition in unconstrained videos. In ICMR, 2014.
3. L. Cao, Y. Mu, A. Natsev, S.-F. Chang, G. Hua, and J. R. Smith. Scene aligned pooling for complex video recognition. In ECCV. 2012.
4. Y. Chen, J. Bi, and J. Z. Wang. Miles: Multiple-instance learning via embedded instance selection. PAMI, 28(12):1931-1947, 2006.
5. Y. Chen and J. Z. Wang. Image categorization by learning and reasoning with regions. JMLR, 5:913-939, 2004.
6. N. Dalal and B. Triggs. Histograms of oriented gradients for human detection. In CVPR, 2005.
7. T. G. Dietterich, R. H. Lathrop, and T. Lozano-Pérez. Solving the multiple instance problem with axis-parallel rectangles. Artificial Intelligence, 89(1):31-71, 1997.
8. R.-E. Fan, K.-W. Chang, C.-J. Hsieh, X.-R. Wang, and C.-J. Lin. LIBLINEAR: A library for large linear classification. JMLR, 9:1871-1874, 2008.
9. Y.-G. Jiang, S. Bhattacharya, S.-F. Chang, and M. Shah. High-level event recognition in unconstrained videos. IJMIR, pages 1-29, 2012.
10. Y.-G. Jiang, G. Ye, S.-F. Chang, D. Ellis, and A. C. Loui. Consumer video understanding: A benchmark database and an evaluation of human and machine performance. In ICMR, 2011.
11. W. Li, Q. Yu, A. Divakaran, and N. Vasconcelos. Dynamic pooling for complex event recognition. In ICCV, 2013.
12. D. G. Lowe. Distinctive image features from scale-invariant keypoints. IJCV, 60(2):91-110, 2004.
13. O. Maron and A. L. Ratan. Multiple-instance learning for natural scene classification. In ICML, 1998.
14. P. Mermelstein. Distance measures for speech recognition, psychological and instrumental. PAMI, 116:374-388, 1976.
15. P. Over, G. Awad, M. Michel, J. Fiscus, G. Sanders, W. Kraaij, A. F. Smeaton, and G. Quenot. Trecvid 2013-an overview of the goals, tasks, data, evaluation mechanisms and metrics. In Proceedings of TRECVID 2013. NIST, 2013.
16. S. Rüeping. SVM classifier estimation from group probabilities. In ICML, 2010.
17. A. Shilton, M. Palaniswami, D. Ralph, and A. C. Tsoi. Incremental training of support vector machines. IEEE Transactions on Neural Networks, 16(1):114-131, 2005.
18. J. Sivic and A. Zisserman. Video google: A text retrieval approach to object matching in videos. In ICCV, 2003.
19. K. Tang, L. Fei-Fei, and D. Koller. Learning latent temporal structure for complex event detection. In CVPR, 2012.
20. L. Torresani, M. Szummer, and A. Fitzgibbon. Efficient object category recognition using classemes. In ECCV. 2010.
21. A. Vedaldi and A. Zisserman. Efficient additive kernels via explicit feature maps. PAMI, 34(3):480-492, 2012.
22. H. Wang, A. Klaser, C. Schmid, and C.-L. Liu. Action recognition by dense trajectories. In CVPR, 2011.
23. J. Yang. Mill: A multiple instance learning library, 2009.
24. J. Yang, K. Yu, Y. Gong, and T. Huang. Linear spatial pyramid matching using sparse coding for image classification. In CVPR, 2009.
25. F. X. Yu, D. Liu, S. K., T. Jebara, and S.-F. Chang. ∝SVM for learning with label proportions. In ICML, 2013.
26. D. Zhang, J. He, L. Si, and R. D. Lawrence. Mileage: Multiple instance learning with global embedding. In ICML, 2013.
27. Q. Zhang, S. A. Goldman, W. Yu, and J. E. Fritts. Content-based image retrieval using multiple-instance learning. In ICML, 2002.