PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Discriminative Human Action Segmentation and Recognition using Semi-Markov Model
Qinfeng Shi, Li Wang, Li Cheng and Alex Smola
In: n IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 08), 22-28 June 2008, Anchorage, Alaska, US.


Given an input video sequence of one person conducting a sequence of continuous actions, we consider the problem of jointly segmenting and recognizing actions. We propose a discriminative approach to this problem under a semi-Markov model framework, where we are able to define a set of features over inputoutput space that captures the characteristics on boundary frames, action segments and neighboring action segments, respectively. In addition, we show that this method can also be used to recognize the person who performs in this video sequence. A Viterbi-like algorithm is devised to help efficiently solve the induced optimization problem. Experiments on a variety of datasets demonstrate the effectiveness of the proposed method.

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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Machine Vision
Learning/Statistics & Optimisation
ID Code:4163
Deposited By:Qinfeng Shi
Deposited On:07 September 2008