HMM based action recognition with projection histogram features

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

Volumn 6388 LNCS, Issue , 2010, Pages 286-293

  Vezzani, Roberto ^a   Baltieri, Davide ^a   Cucchiara, Rita ^a  

^a UNIVERSITY OF MODENA AND REGGIO EMILIA   (Italy)

Author keywords

Action Classification; HMM; Projection Histograms

Indexed keywords

ACTION CLASSIFICATION; ACTION RECOGNITION; AUTOMATIC FEATURE SELECTION; DATA SETS; EMISSION PROBABILITIES; FEATURE SETS; GLOBAL ACTIONS; HMM; KEY ISSUES; MIXTURE OF GAUSSIANS; PROJECTION HISTOGRAMS; TEMPORAL EVOLUTION; TRAINING SETS; ACTION CLASSIFICATIONS;

GRAPHIC METHODS; HIDDEN MARKOV MODELS; SIGNAL PROCESSING; SPEECH RECOGNITION; FEATURE EXTRACTION; MARKOV PROCESSES; PATTERN RECOGNITION; TRELLIS CODES;

FEATURE EXTRACTION; HIDDEN MARKOV MODELS;

EID: 78650843230     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-17711-8_29     Document Type: Conference Paper

References (15)

1. Laptev, I., Lindeberg, T.: Space-time interest points. In: IEEE Int. Conf. on Computer Vision (ICCV 2003), Nice, France (2003)
2. Cucchiara, R., Grana, C., Prati, A., Vezzani, R.: Probabilistic posture classification for human behaviour analysis. IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans 35, 42-54 (2005)
3. Ke, Y., Sukthankar, R., Hebert, M.: Spatiotemporal shape and flow correlation for action recognition. In: Proc. of IEEE Intl Conference on Computer Vision and Pattern Recognition, pp. 1-8 (2007)
4. Shechtman, E., Irani, M.: Space-time behavior-based correlation -or- how to tell if two underlying motion fields are similar without computing them? IEEE Transactions on Pattern Analysis and Machine Intelligence 29, 2045-2056 (2007)
5. Rabiner, L.R.: A tutorial on hidden markov models and selected applications in speech recognition. Proc. of the IEEE 77, 257-286 (1989)
6. Turaga, P., Chellappa, R., Subrahmanian, V., Udrea, O.: Machine recognition of human activities: A survey. IEEE Trans. on Circuits and Systems for Video Technology 18, 1473-1488 (2008)
7. Yamato, J., Ohya, J., Ishii, K.: Recognizing human action in time-sequential images using hidden markov model. In: Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 379-385 (1992)
8. Umeda, M.: Recognition of multi-font printed chinese. characters. In: Proc. of 6th International Conference on Pattern Recognition, pp. 793-796 (1982)
9. Li, X.: Hmm based action recognition using oriented histograms of optical flow field. Electronics Letters 43, 560-561 (2007)
10. Martinez-Contreras, F., Orrite-Urunuela, C., Herrero-Jaraba, E., Ragheb, H., Velastin, S.: Recognizing human actions using silhouette-based hmm. In: Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2009, pp. 43-48 (2009)
11. Vezzani, R., Cucchiara, R.: Ad-hoc: Appearance driven human tracking with occlusion handling. In: First International Workshop on Tracking Humans for the Evaluation of their Motion in Image Sequences (THEMIS 2008), Leeds, UK (2008)
12. Cucchiara, R., Grana, C., Piccardi, M., Prati, A.: Detecting moving objects, ghosts and shadows in video streams. IEEE Transactions on Pattern Analysis andMachine Intelligence 25, 1337-1342 (2003)
13. Vezzani, R., Piccardi, M., Cucchiara, R.: An efficient bayesian framework for online action recognition. In: Proceedings of the IEEE International Conference on Image Processing, Cairo, Egypt (2009)
14. Chen, C.C., Ryoo, M.S., Aggarwal, J.K.: UT-Tower Dataset: Aerial View Activity Classification Challenge (2010), http://cvrc.ece.utexas.edu/SDHA2010
15. Gorelick, L., Blank, M., Shechtman, E., Irani, M., Basri, R.: Actions as space-time shapes. IEEE Trans. on Pattern Analysis and Machine Intelligence 29, 2247-2253 (2007)