Video Copy Detection Using Multiple Visual Cues and MPEG-7 Descriptors

Onur Kucuktunc, Muhammet Bastan, Ugur Gudukbay, Ozgur Ulusoy

Abstract - We propose a video copy detection framework that detects copy segments by fusing the results of three different techniques: facial shot matching, activity subsequence matching, and non-facial shot matching using low-level features. In facial shot matching part, a high-level face detector identifies facial frames/shots in a video clip. Matching faces with extended body regions gives the flexibility to discriminate the same person (e.g., an anchor man or a political leader) in different events or scenes. In activity subsequence matching part, a spatio-temporal sequence matching technique is employed to match video clips/segments that are similar in terms of activity. Lastly, the non-facial shots are matched using low-level MPEG-7 descriptors and dynamic-weighted feature similarity calculation. The proposed framework is tested on the query and reference dataset of CBCD task of TRECVID 2008. Our results are compared with the results of top-8 most successful techniques submitted to this task. Promising results are obtained in terms of both effectiveness and efficiency.

10.1016/j.jvcir.2010.07.001
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activity matching, content-based copy detection, face detection, mpeg-7, subsequence matching, time series analysis, video copy detection, visual ques

Fuzzy Color Histogram-based Video Segmentation

Onur Kucuktunc, Ugur Gudukbay, Ozgur Ulusoy

Abstract - We present a fuzzy color histogram-based shot-boundary detection algorithm specialized for content-based copy detection applications. The proposed method aims to detect both cuts and gradual transitions (fade, dissolve) effectively in videos where heavy transformations (such as cam-cording, insertions of patterns, strong re-encoding) occur. Along with the color histogram generated with the fuzzy linking method on L*a*b* color space, the system extracts a mask for still regions and the window of picture-in-picture transformation for each detected shot, which will be useful in a content-based copy detection system. Experimental results show that our method effectively detects shot boundaries and reduces false alarms as compared to the state-of-the-art shot-boundary detection algorithms.

10.1016/j.cviu.2009.09.008
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content-based copy detection, cut/gradual transition, fuzzy color histogram, shot boundary detection, video analysis, video segmentation

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