Abstract:
Aiming at the accuracy and speed problem of action recognition pre-procession under Two-Stream Temporal Segment Network (TSN), this paper is applied the deep learning solution of the optical flow to activity recognition. Appearance information is extracted from spatial convolution network with original RGB frame image as inputs, and motion information is extracted from time convolution network with optical-flow feature image as inputs which are obtained by calculating adjacent frames using deep learning algorithm. Appearance information and motion information are complemented with each other. The recognition results can be obtained after weighted fusion the outputs of the space convolution network and the time convolution network. The experimental results is demonstrated that the proposed algorithm can speed up the whole recognition process effectively while achieving excellent recognition performance.