Recognising human interaction from videos by a discriminative model
Recognising human interaction from videos by a discriminative model
复制标题
通过判别模型从视频中识别人类互动
DOI：
10.1049/iet-cvi.2013.0042
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发表时间：
2014
影响因子：
1.7
通讯作者：
Jia Yunde
中科院分区：
文献类型：
--
作者：
Kong Yu;Liang Wei;Dong Zhen;Jia Yunde
This study addresses the problem of recognising human interactions between two people. The main difficulties lie in the partial occlusion of body parts and the motion ambiguity in interactions. The authors observed that the interdependencies existing at both the action level and the body part level can greatly help disambiguate similar individual movements and facilitate human interaction recognition. Accordingly, they proposed a novel discriminative method, which model the action of each person by a large‐scale global feature and local body part features, to capture such interdependencies for recognising interaction of two people. A variant of multi‐class Adaboost method is proposed to automatically discover class‐specific discriminative three‐dimensional body parts. The proposed approach is tested on the authors newly introduced BIT‐interaction dataset and the UT‐interaction dataset. The results show that their proposed model is quite effective in recognising human interactions.
