Recognizing complex events using large margin joint low-level event model

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 7575 LNCS, Issue PART 4, 2012, Pages 430-444

  Izadinia, Hamid ^a   Shah, Mubarak ^a  

^a UNIVERSITY OF CENTRAL FLORIDA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BASELINE METHODS; COMPLEX EVENTS; DATA SETS; DETECTION TASKS; DISCRIMINATIVE MODELS; EVENT MODEL; HIDDEN VARIABLE; MULTIMEDIA EVENT DETECTIONS; PRESENCE/ABSENCE; VIDEO CLIPS;

DETECTORS;

COMPUTER VISION;

EID: 84867889550     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-33765-9_31     Document Type: Conference Paper

References (26)

1. Schuldt, C., Laptev, I., Caputo, B.: Recognizing human actions: a local svm approach. In: ICPR (2004)
2. Rodriguez, M., Ahmed, J., Shah, M.: Action mach a spatio-temporal maximum average correlation height filter for action recognition. In: CVPR (2008)
3. Ucf50 action dataset, http://vision.eecs.ucf.edu/data/UCF50.rar
4. Kuehne, H., Jhuang, H., Garrote, E., Poggio, T., Serre, T.: HMDB: a large video database for human motion recognition. In: ICCV (2011)
5. Le, Q., Zou, W., Yeung, S., Ng, A.: Learning hierarchical invariant spatio-temporal features for action recognition with independent subspace analysis. In: CVPR (2011)
6. Wang, H., Kläser, A., Schmid, C., Cheng-Lin, L.: Action recognition by dense trajectories. In: CVPR (2011)
7. Jiang, Y.G., Yang, J., Ngo, C.W., Hauptmann, A.G.: Representations of keypoint-based semantic concept detection: A comprehensive study. IEEE Trans. Multimedia 12(1), 42-53 (2010)
8. Merler, M., Huang, B., Xie, L., Hua, G., Natsev, A.: Semantic model vectors for complex video event recognition. IEEE Trans. Multimedia 14(1), 88-101 (2012)
9. Natarajan, P., et al.: Bbn viser trecvid 2011 multimedia event detection system. In: NIST TRECVID Workshop (2011)
10. Farhadi, A., Endres, I., Hoiem, D., Forsyth, D.: Describing objects by their attributes. In: CVPR (2009)
11. Ferrari, V., Zisserman, A.: Learning visual attributes. In: NIPS (2007)
12. Wang, Y., Mori, G.: A Discriminative Latent Model of Object Classes and Attributes. In: Daniilidis, K., Maragos, P., Paragios, N. (eds.) ECCV 2010, Part V. LNCS, vol. 6315, pp. 155-168. Springer, Heidelberg (2010)
13. Lampert, C., Nickisch, H., Harmeling, S.: Learning to detect unseen object classes by between-class attribute transfer. In: CVPR (2009)
14. Siddiquie, B., Feris, R., Davis, L.: Image ranking and retrieval based on multiattribute queries. In: CVPR (2011)
15. Liu, J., Kuipers, B., Savarese, S.: Recognizing human actions by attributes. In: CVPR (2011)
16. Gaidon, A., Harchaoui, Z., Schmid, C.: Actom sequence models for efficient action detection. In: CVPR (2011)
17. Niebles, J.C., Chen, C.-W., Fei-Fei, L.: Modeling Temporal Structure of Decomposable Motion Segments for Activity Classification. In: Daniilidis, K., Maragos, P., Paragios, N. (eds.) ECCV 2010, Part II. LNCS, vol. 6312, pp. 392-405. Springer, Heidelberg (2010)
18. Tang, K., Fei-Fei, L., Koller, D.: Learning latent temporal structure for complex event detection. In: CVPR (2012)
19. Laptev, I.: On space time interest points. IJCV 64 (2005)
20. Dollar, P., Rabaud, V., Cottrell, G., Belongie, S.: Behavior recognition via sparse spatio-temporal features. In: IEEE International Workshop on VS-PETS (2005)
21. Oliva, A., Torralba, A.: Modeling the shape of the scene: A holistic representation of the spatial envelope. IJCV 42, 145-175 (2001)
22. Lowe, D.G.: Distinctive image features from scale-invariant keypoints. IJCV 60(2) (2004)
23. Rabiner, L., Juang, B.H.: Fundamentals of Speech Recognition. Prentice Hall (1993)
24. Do, T.M.T., Artières, T.: Large margin training for hidden markov models with partially observed states. In: ICML (2009)
25. Trecvid multimedia event detection track (2011), http://www.nist.gov/itl/ iad/mig/med11.cfm
26. Everingham, M., Gool, L., Williams, C.K., Winn, J., Zisserman, A.: The pascal visual object classes (voc) challenge. IJCV 88, 303-338 (2010)