Action and event recognition with fisher vectors on a compact feature set

Proceedings of the IEEE International Conference on Computer Vision

Volumn , Issue , 2013, Pages 1817-1824

  Oneata, Dan ^a   Verbeek, Jakob ^a   Schmid, Cordelia ^a  

^a INRIA   (France)

Author keywords

action localization; action recognition; bag of visual words; dense trajectories; evaluation; event recognition; Fisher vectors; uncontrolled realistic videos

Indexed keywords

COMPUTER SCIENCE; COMPUTERS; ELECTRICAL ENGINEERING;

ACTION LOCALIZATION; ACTION RECOGNITION; BAG-OF-VISUAL-WORDS; EVALUATION; EVENT RECOGNITION; FISHER VECTORS; UNCONTROLLED REALISTIC VIDEOS;

CLASSIFICATION (OF INFORMATION);

EID: 84898791167     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCV.2013.228     Document Type: Conference Paper

References (45)

1. W. Brendel and S. Todorovic. Activities as time series of human postures. In ECCV, 2010.
2. L. Cao, Y. Mu, A. Natsev, S.-F. Chang, G. Hua, and J. Smith. Scene aligned pooling for complex video recognition. In ECCV, 2012.
3. K. Chatfield, V. Lempitsky, A. Vedaldi, and A. Zisserman. The devil is in the details: an evaluation of recent feature encoding methods. In BMVC, 2011.
4. O. Duchenne, I. Laptev, J. Sivic, F. Bach, and J. Ponce. Automatic annotation of human actions in video. In ICCV, 2009.
5. M. Everingham, L. van Gool, C. Williams, J. Winn, and A. Zisserman. The pascal visual object classes (VOC) challenge. IJCV, 88(2):303-338, June 2010.
6. A. Gaidon, Z. Harchaoui, and C. Schmid. Actom sequence models for efficient action detection. In CVPR, 2011.
7. A. Gaidon, Z. Harchaoui, and C. Schmid. Recognizing activities with cluster-trees of tracklets. In BMVC, 2012.
8. A. Gupta, A. Kembhavi, and L. Davis. Observing humanobject interactions: using spatial and functional compatibility for recognition. PAMI, 31(10):1775-1789, 2009.
9. N. Ikizler-Cinbis and S. Sclaroff. Object, scene and actions: combining multiple features for human action recognition. In ECCV, 2010.
10. H. Izadinia and M. Shah. Recognizing complex events using large margin joint low-level event model. In ECCV, 2012.
11. M. Jain, H. J́egou, and P. Bouthemy. Better exploiting motion for better action recognition. In CVPR, 2013.
12. Y.-G. Jiang, Q. Dai, X. Xue, W. Liu, and C.-W. Ngo. Trajectory-based modeling of human actions with motion reference points. In ECCV, 2012.
13. A. Kl̈aser, M. Marszałek, C. Schmid, and A. Zisserman. Human focused action localization in video. In ECCV Workshop on Sign, Gesture, and Activity, 2010.
14. O. Kliper-Gross, Y. Gurovich, T. Hassner, and L. Wolf. Motion interchange patterns for action recognition in unconstrained videos. In ECCV, 2012.
15. J. Krapac, J. Verbeek, and F. Jurie. Modeling spatial layout with Fisher vectors for image categorization. In ICCV, 2011.
16. H. Kuehne, H. Jhuang, E. Garrote, T. Poggio, and T. Serre. HMDB: a large video database for human motion recognition. In ICCV, 2011.
17. I. Laptev, M. Marszałek, C. Schmid, and B. Rozenfeld. Learning realistic human actions from movies. In CVPR, 2008.
18. I. Laptev and P. Ṕerez. Retrieving actions in movies. In ICCV, 2007.
19. S. Lazebnik, C. Schmid, and J. Ponce. Beyond bags of features: spatial pyramid matching for recognizing natural scene categories. In CVPR, 2006.
20. Q. Le, W. Zou, S. Yeung, and A. Ng. Learning hierarchical invariant spatio-temporal features for action recognition with independent subspace analysis. In CVPR, 2011.
21. J. Liu, J. Luo, and M. Shah. Recognizing realistic actions from videos. In CVPR, 2009.
22. D. Lowe. Distinctive image features from scale-invariant keypoints. IJCV, 60(2):91-110, 2004.
23. M. Marszalek, I. Laptev, and C. Schmid. Actions in context. In CVPR, 2009.
24. S. Mathe and C. Sminchisescu. Dynamic eye movement datasets and learnt saliency models for visual action recognition. In ECCV, 2012.
25. P. Matikainen, M. Hebert, and R. Sukthankar. Representing pairwise spatial and temporal relations for action recognition. In ECCV, 2010.
26. S. McCann and D. Lowe. Spatially local coding for object recognition. In ACCV, 2012.
27. P. Natarajan, S. Wu, S. Vitaladevuni, X. Zhuang, S. Tsakalidis, U. Park, R. Prasad, and P. Natarajan. Multimodal feature fusion for robust event detection in web videos. In CVPR, 2012.
28. J. Niebles, C.-W. Chen, and F.-F. Li. Modeling temporal structure of decomposable motion segments for activity classification. In ECCV, 2010.
29. P. Over, G. Awad, M. Michel, J. Fiscus, G. Sanders, B. Shaw, W. Kraaij, A. F. Smeaton, and G. Quenot. TRECVID 2012-an overview of the goals, tasks, data, evaluation mechanisms and metrics. In Proceedings of TRECVID, 2012.
30. F. Perronnin, J. Śanchez, and Y. Liu. Large-scale image categorization with explicit data embedding. In CVPR, 2010.
31. A. Prest, V. Ferrari, and C. Schmid. Explicit modeling of human-object interactions in realistic videos. PAMI, 35(4):835-848, 2013.
32. L. Rabiner and R. Schafer. Introduction to digital speech processing. Foundations and Trends in Signal Processing, 1(1/2):1-194, 2007.
33. K. Reddy and M. Shah. Recognizing 50 human action categories of web videos. In Machine Vision and Applications Journal, 2012.
34. J. Śanchez, F. Perronnin, and T. de Campos. Modeling the spatial layout of images beyond spatial pyramids. Pattern Recognition Letters, 33(16):2216-2223, 2012.
35. J. Sanchez, F. Perronnin, T. Mensink, and J. Verbeek. Image classification with the Fisher vector: Theory and practice. IJCV, 105(3):222-245, June 2013.
36. M. Sapienza, F. Cuzzolin, and P. Torr. Learning discriminative space-time actions from weakly labelled videos. In BMVC, 2012.
37. C. Schuldt, I. Laptev, and B. Caputo. Recognizing human actions: a local SVM approach. In ICPR, 2004.
38. J. Sivic and A. Zisserman. Video Google: a text retrieval approach to object matching in videos. In ICCV, 2003.
39. C. Sun and R. Nevatia. Large-scale web video event classification by use of Fisher vectors. In WACV, 2013.
40. K. Tang, L. Fei-Fei, and D. Koller. Learning latent temporal structure for complex event detection. In CVPR, 2012.
41. H. Wang, A. Kl̈aser, C. Schmid, and C.-L. Liu. Dense trajectories and motion boundary descriptors for action recognition. IJCV, 2013.
42. H. Wang and C. Schmid. Action recognition with improved trajectories. In ICCV, 2013.
43. H. Wang, M. Ullah, A. Kl̈aser, I. Laptev, and C. Schmid. Evaluation of local spatio-temporal features for action recognition. In BMVC, 2009.
44. X. Wang, L. Wang, and Y. Qiao. A comparative study of encoding, pooling and normalization methods for action recognition. In ACCV, 2012.
45. Y. Yang and M. Shah. Complex events detection using datadriven concepts. In ECCV, 2012.