Accelerated local feature extraction in a reuse scheme for efficient action recognition
In this paper, we propose an accelerated local feature extraction in a reuse scheme for action recognition. Most local features of the previous frame could be reused due to the high correlation between successive frames. Feature extraction is only needed to be applied partially in the current frame. The full-frame features of the current frame are combined by features extracted at different times. Experimental results show that the proposed reuse scheme can achieve comparable performance to full-frame feature extraction while computational effort is reduced significantly.