A method for robust and quick video searching using probabilistic dither-voting

Abstract

We propose a quick and accurate search method for detecting a query signal from long video recordings The method is based on the time-series active search, which is a quick searching method for audio and video signals that we previously proposed. Time-series active search is based on a histogram matching scheme and an efficient pruning mechanism, and therefore, it was very quick. We found, however, that the accuracy sometimes deteriorates when it is applied to searches through long video archives that are composed of many similar video images or those containing feature distortions caused by video dubbing or low-bit-rate compression. The problem arises from (1) insufficient capability of representing features and (2) feature distortions. Thus, the method proposed here uses LBG-based VQ to improve the capacity to represent features and probabilistic dither-voting to improve robustness with respect to feature distortions. The experiments prove the effects of the proposed method.