A visual saliency based video hashing algorithm

Jing Wang, Jiande Sun, Ju Liu, Xiushan Nie, Hua Yan

Abstract: A novel video hashing algorithm is proposed, which takes account of visual saliency during hash generation. In the proposed algorithm, the video hash is fused by two hashes, which are spatio-temporal hash (ST-Hash) and visual hash (V-Hash). The ST-Hash is generated based on the ordinal feature, which is formed according to the intensity difference between adjacent blocks of the temporally informative representation image (TIRI). At the same time, the representative saliency map (RSM) is constructed by the visual saliency maps in video segments. The V-Hash is formed according to the intensity difference between adjacent blocks of the RSM, and used to modulate the ST-Hash to form the final video hash. Experiments on different kinds of videos with different kinds of attacks verify that the proposed algorithm has better performance on robustness and discrimination.