Action recognition method based on attention mechanism of convolution recurrent neural network
A technology of recursive neural network and convolutional neural network, which is applied in the field of computer vision action recognition, can solve problems such as the inability to effectively extract salient areas, and achieve the effect of improving accuracy
Active Publication Date: 2017-10-20
DALIAN UNIV OF TECH
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Abstract
The present invention belongs to the field of computer vision action recognition, and proposes an action recognition method based on the attention mechanism of the convolution recurrent neural network, in order to solve the problem that the obvious region cannot be effectively extracted in the action recognition and to improve the accuracy of classification. The method comprises: using the convolution neural network to extract the feature of the action video automatically; using the spatial transformation network to realize the attention mechanism based on the feature map, and extracting the obvious feature region by using the attention mechanism to generate the target feature map; and inputting the target feature map into the convolutional recurrent neural network to produce the final action recognition result. Experiments show that the proposed method has achieved good results on the benchmark action video test set such as UCF-11, HMDB-51, and the like, and improves the accuracy of action recognition.
Application Domain
Character and pattern recognitionNeural architectures
Technology Topic
Activity recognitionConvolution +9
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