Visual Attention Based Temporally Weighting Method for Video Hashing

The video hash derived from the temporally representative frame (TRF) has attracted increasing interests recently. A temporally visual weighting (TVW) method based on visual attention is proposed for the generation of TRF in this paper. In the proposed TVW method, the visual attention regions of each frame are obtained by combining the dynamic and static attention models. The temporal weight for each frame is defined as the strength of temporal variation of visual attention regions and the TRF of a video segment can be generated by accumulating the frames by the proposed TVW method. The advantage of the TVW method is proved by the comparison experiments. The video hashes used for comparison are derived from the TRFs, which are generated based on the proposed TVW method and other existing weighting methods respectively. The experimental results show that the TVW method is helpful to enhance the robustness and discrimination of video hash.