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Content based Video Copy Detection Using Spatio-Temporal Ordinal Measure  

Jeong, Jae-Hyup (Dept. of Electronic Engineering, Inha University)
Kim, Tae-Wang (Dept. of Electronic Engineering, Inha University)
Yang, Hun-Jun (Dept. of Electronic Engineering, Inha University)
Jin, Ju-Kyong (Dept. of Electronic Engineering, Inha University)
Jeong, Dong-Seok (Dept. of Electronic Engineering, Inha University)
Publication Information
Journal of the Institute of Electronics Engineers of Korea SP / v.49, no.2, 2012 , pp. 113-121 More about this Journal
Abstract
In this paper, we proposed fast and efficient algorithm for detecting near-duplication based on content based retrieval in large scale video database. For handling large amounts of video easily, we split the video into small segment using scene change detection. In case of video services and copyright related business models, it is need to technology that detect near-duplicates, that longer matched video than to search video containing short part or a frame of original. To detect near-duplicate video, we proposed motion distribution and frame descriptor in a video segment. The motion distribution descriptor is constructed by obtaining motion vector from macro blocks during the video decoding process. When matching between descriptors, we use the motion distribution descriptor as filtering to improving matching speed. However, motion distribution has low discriminability. To improve discrimination, we decide to identification using frame descriptor extracted from selected representative frames within a scene segmentation. The proposed algorithm shows high success rate and low false alarm rate. In addition, the matching speed of this descriptor is very fast, we confirm this algorithm can be useful to practical application.
Keywords
content-based video retrieval; motion descriptor; video matching; near-duplicate retrieval;
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