Discriminative Human Action Recognition Using Semi-Markov Model and Large-margin
基于半马尔可夫和Large-margin的动作识别

Given an input video sequence of one person who conducted a sequence of continuous actions,we consider the problem of jointly segmenting and recognizing actions.To recognize the activities in videos,we propose a discriminative approach to this problem within a semi-Markov model framework,where we are able to define a set of features over input-output space that captures the characteristics on boundary frames,action segments and neighboring action segments,respectively.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.