An efficient Bayesian framework for on-line action recognition
Abstract: On-line action recognition from a continuous stream of actionsis still an open problem with fewer solutions proposedcompared to time-segmented action recognition. The mostchallenging task is to classify the current action while findingits time boundaries at the same time. In this paper wepropose an approach capable of performing on-line actionsegmentation and recognition by means of batteries of HMMtaking into account all the possible time boundaries and actionclasses. A suitable Bayesian normalization is appliedto make observation sequences of different length comparableand computational optimizations are introduce to achievereal-time performances. Results on a well known actiondataset prove the efficacy of the proposed method
Citation:
Vezzani, Roberto; Piccardi, Massimo; Cucchiara, Rita "An efficient Bayesian framework for on-line action recognition" Proceedings of the IEEE International Conference on Image Processing, Cairo, egy, pp. 3553 -3556 , November 7-11, 2009, 2009 DOI: 10.1109/ICIP.2009.5414340
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- DOI: 10.1109/ICIP.2009.5414340