【摘 要】
:
In order to recognize human actions from video sequences,local self-similarity of intensity and optical flow(LSS-IOF)is presented to describe actions.Our descriptor is based on the recently proposed l
【机 构】
:
Nanjing University of Aeronautics and Astronautics,China;Shenyang Aerospace University,China
【出 处】
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第三届先进计算智能与智能信息学国际研讨会(The Third International Workshop on Adv
论文部分内容阅读
In order to recognize human actions from video sequences,local self-similarity of intensity and optical flow(LSS-IOF)is presented to describe actions.Our descriptor is based on the recently proposed local self-similarity(LSS)for objection detection,by measuring the self-similarity of local patches intensity or color,the object can be detected from images.The difference between our descriptor LSS-IOF and LSS is that we combine optical flow feature into the measurement of local self-similarity.Then through feature selection,the novel descriptor can reflect a common underlying visual and motion property,for actions which belong to the same category,even if the scale,speed or the motion style vary significantly.The novel descriptor is discriminative to classify human actions using nearest neighbor classifier.Our experimental results show that our method is comparable to other state-of-the-art approaches in action recognition.
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