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Alternative TitleTwo-person interaction recognition based on multi-stream spatio-temporal fusion network
裴晓敏1; 范慧杰2; 唐延东2
Source Publication红外与激光工程
Indexed ByEI ; CSCD
EI Accession number20202408811925
Contribution Rank2
Funding Organization国家自然科学基金(61401455) ; 辽宁省自然科学基金(2019ZD0066)
Keyword双人交互行为 卷积神经网络 长短时记忆网络 时空融合网络 多通道


Other Abstract

Two-person interaction recognition based on multi-stream spatio-temporal fusion was proposed. Firstly, a method to describe two-person’s skeleton which invariable with angle of view was proposed. Then a two-layer spatio-temporal fusion network model was designed. In the first layer, the spatial correlation features were obtained based on one-dimensional convolutional neural network (1DCNN) and bi-directional long short term memory(BiLSTM). In the second layer, the spatio-temporal fusion features were obtained based on LSTM. Finally, the multi-stream spatio-temporal fusion network was used to obtain the multi-stream fusion features, which learned one kind of feature by one stream and fusion features for all streams together at last. The weights for each stream was shared, and every stream had the same structure. After features were fusion for all streams, it could be used for interaction recognition. By applying this algorithm to NTU-rgbd datasets, the accuracy for two person interaction recognition for cross-subject could reach 96.42%, and the accuracy of two person interaction recognition for cross-view could reach 97.46%. Compared with the state of art methods in this field, this method performed best in two person interaction recognition.

Citation statistics
Document Type期刊论文
Corresponding Author裴晓敏
Recommended Citation
GB/T 7714
裴晓敏,范慧杰,唐延东. 多通道时空融合网络双人交互行为识别[J]. 红外与激光工程,2020,49(5):1-6.
APA 裴晓敏,范慧杰,&唐延东.(2020).多通道时空融合网络双人交互行为识别.红外与激光工程,49(5),1-6.
MLA 裴晓敏,et al."多通道时空融合网络双人交互行为识别".红外与激光工程 49.5(2020):1-6.
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