Discriminative space-time voting for joint recognition and localization of actions

SSPW'10 - Proceedings of the 2010 ACM Social Signal Processing Workshop, Co-located with ACM Multimedia 2010

Volumn , Issue , 2010, Pages 11-16

  Oikonomopoulos, Antonios ^a   Patras, Ioannis ^b   Pantic, Maja ^a,c  

^a IMPERIAL COLLEGE LONDON   (United Kingdom)

^b QUEEN MARY UNIVERSITY OF LONDON   (United Kingdom)

^c UNIVERSITY OF TWENTE   (Netherlands)

Author keywords

Action detection; Space time voting

Indexed keywords

ACTION DETECTION; ACTIVITY DETECTION; CODEBOOKS; CODEWORD; DATA SETS; FEATURE DESCRIPTORS; HUMAN ACTIVITIES; IMAGE SEQUENCE; IMPLICIT REPRESENTATION; MEAN SHIFT; MODE ESTIMATION; REFERENCE POINTS; SPATIAL POSITIONS; TEMPORAL POSITION; TIME VOTING; VOTING SCHEMES;

SIGNAL DETECTION; SIGNAL PROCESSING;

MULTIMEDIA SIGNAL PROCESSING;

EID: 78650907516     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1878116.1878122     Document Type: Conference Paper

References (20)

1. Poppe, R.: A survey on vision-based human action recognition. Image and Vision Computing Journal 28 (2010) 976-990.
2. Pantic, M., Pentland, A., Nijholt, A., Huang, T.: Human computing and machine understanding of human behavior: A survey. LNAI 4451 (2007) 47-71.
3. Laptev, I., Lindeberg, T.: Space-time Interest Points. In: IEEE Conf. on Computer Vision and Pattern Recognition. (2003) 432 - 439.
4. Dollar, P., Rabaud, V., Cottrell, G., Belongie, S.: Behavior recognition via sparse spatio-temporal features. VS-PETS (2005) 65- 72.
5. Bregonzio, M., Gong, S., Xiang, T.: Recognising action as clouds of space-time interest points. In: IEEE Conf. on Computer Vision and Pattern Recognition. (2009) 1-8.
6. Oikonomopoulos, A., Patras, I., Pantic, M.: Spatiotemporal Salient Points for Visual Recognition of Human Actions. IEEE Trans. Systems, Man and Cybernetics Part B 36 (2006) 710 - 719. (Pubitemid 43811326)
7. Lowe, D.: Distinctive image features from scale-invariant keypoints. Int. Journal of Computer Vision 60 (2004) 91 - 110.
8. Jhuang, H., Serre, T., Wolf, L., Poggio, T.: A Biologically Inspired System for Action Recognition. In: Proc. IEEE Int. Conf. Computer Vision. (2007) 1-8.
9. Ning, H., Hu, Y., Huang, T.: Searching human behaviors using spatial-temporal words. In: Proc. IEEE Int. Conference on Image Processing. Volume 6. (2007) 337-340.
10. Marszalek, M., Laptev, I., Schmid, C.: Actions in context. In: IEEE Conf. on Computer Vision and Pattern Recognition. (2009) 2929-2936.
11. Leibe, B., Leonardis, A., Schiele, B.: Combined object categorization and segmentation with an implicit shape model. ECCV'04 Workshop on Statistical Learning in Computer Vision (2004) 17-32.
12. Mikolajczyk, K., Uemura, H.: Action recognition with motion-appearance vocabulary forest. In: IEEE Conf. on Computer Vision and Pattern Recognition. (2008) 1-8.
13. Sivic, J., Russell, B., Efros, A., Zisserman, A., Freeman, W.: Discovering Objects and their Location in Images. In: Proc. IEEE Int. Conf. Computer Vision. Volume 1. (2005) 370 - 377.
14. Boiman, O., Irani, M.: Detecting irregularities in images and in video. In: Proc. IEEE Int. Conf. Computer Vision. Volume 1. (2005) 462-469.
15. Shechtman, E., Irani, M.: Matching local self-similarities across images and videos. In: IEEE Conf. on Computer Vision and Pattern Recognition. (2007) 1-8.
16. Cheng, Y.: Mean shift, mode seeking, and clustering. IEEE Trans. Pattern Analysis and Machine Intelligence 17 (1995) 790 - 799.
17. Tipping, M.: The Relevance Vector Machine. Advances in Neural Information Processing Systems (1999) 652 - 658.
18. Friedman, J., Hastie, T., Tibshirani, R.: Additive logistic regression: a statistical view of boosting. Stanford University Technical Report (1993).
19. Bar-Shalom, Y., Fortmann, T.: Tracking and Data Association. Academic Press (1988).
20. Vinciarelli, A., Dielmann, A., Favre, S., Salamin, H.: Canal9: A database of political debates for analysis of social interactions. In: Proc. IEEE Int. Conf. Affective Computing and Intelligent Interfaces. Volume 2. (2009) 96-99.