Computer Science ›› 2018, Vol. 45 ›› Issue (2): 84-89.doi: 10.11896/j.issn.1002-137X.2018.02.014

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Robust Video Hashing Algorithm Based on Short-term Spatial Variations

YU Xiao, NIE Xiu-shan, MA Lin-yuan and YIN Yi-long   

  • Online:2018-02-15 Published:2018-11-13

Abstract: A robust video hashing algorithm based on short-term spatial variations was proposed to detect near-duplicate videos in the Internet.Feature extraction and feature quantization are key steps in this algorithm.In the feature extraction phase,compared to the existing feature extraction methods based on temporal and spatial information fusion,the innovation of the proposed algorithm is to make full use of short-time variations of local spatial information between adjacent frames (referred to “short-term spatial variations”).In the proposed algorithm,inscribed spheres of the video are constructed first,and then a series of spherical tori are obtained by partitioning the inscribed spheres with the center of the sphere as the starting point to capture short-term changes in spatial information between adjacent frames.After that,the decomposition coefficients by non-negative matrix factorization of spherical tori are used as the feature representation of the video.In the feature quantization phase,to map the feature representation into binary hash sequences,the optimized Manhattan hashing strategy is adopted which better reserves the neighborhood structure in the original data space,and thus improves the accuracy of quantization.Experiments were carried out on a video dataset to evaluate the performance of the proposed video hashing method.Experimental results show that the proposed algorithm has good performance.

Key words: Video hashing,Spatio-temporal information,Nonnegative matrix factorization,Near-duplicate video detection,Manhattan hashing

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