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Full-Text Articles in Engineering
Multi-View Human Action Recognition Based On Deep Neural Network, Zhao Ying, Lu Yao, Zhang Jian, Qidi Liang, Long Wei
Multi-View Human Action Recognition Based On Deep Neural Network, Zhao Ying, Lu Yao, Zhang Jian, Qidi Liang, Long Wei
Journal of System Simulation
Abstract: A novel deep neural network named CNN+CA(Convolutional Neural Network plus Context Attention) model is constructed and a new recognition algorithm based on sequence matching is presented to improve the recognition accuracy of MVHAR (Multi-view Human Action Recognition). A CNN(Convolutional Neural Network) is designed to automatically learn multi-view fusion features; the CA (Context Attention) module is introduced to selectively focus on the parts of the features that are relevant for the recognition task; the proposed recognition algorithm based on sequence matching is used to realize MVHAR. The experimental results on the IXMAS dataset and the i3DPost dataset …
An Adversarial Framework For Open-Set Human Action Recognition Usingskeleton Data, Özge Özti̇mur Karadağ
An Adversarial Framework For Open-Set Human Action Recognition Usingskeleton Data, Özge Özti̇mur Karadağ
Turkish Journal of Electrical Engineering and Computer Sciences
Human action recognition is a fundamental problem which is applied in various domains, and it is widelystudied in the literature. Majority of the studies model action recognition as a closed-set problem. However, in real-life applications it usually arises as an open-set problem where a set of actions are not available during training butare introduced to the system during testing. In this study, we propose an open-set action recognition system, humanaction recognition and novel action detection system (HARNAD), which consists of two stages and uses only 3D skeletoninformation. In the first stage, HARNAD recognizes a given action and in the second …