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02-03-2018

Video Copy Detection Based on Deep CNN Features and Graph-Based Sequence Matching

Authors: Xin Zhang, Yuxiang Xie, Xidao Luan, Jingmeng He, Lili Zhang, Lingda Wu

Published in: Wireless Personal Communications | Issue 1/2018

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Abstract

This paper introduces a novel content-based video copy detection method using the deep CNN features. An efficient deep CNN feature is employed to encode the image content while retaining the discrimination capability. Taking advantage of the extremely fast Euclidean distance similarity of deep CNN features, a keyframe-based copy retrieval method that exhaustively searches the copy candidates from the large keyframe database without indexing is proposed. Moreover, a graph-based sequence matching algorithm is employed to obtain the copy clips and accurately locate the video segments. The experimental evaluation has been performed to show the efficacy of the proposed deep CNN features. The promising results demonstrate the effectiveness of our proposed approach.

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Title: Video Copy Detection Based on Deep CNN Features and Graph-Based Sequence Matching
Authors: Xin Zhang
Yuxiang Xie
Xidao Luan
Jingmeng He
Lili Zhang
Lingda Wu
Publication date: 02-03-2018
Publisher: Springer US
Published in: Wireless Personal Communications / Issue 1/2018
Print ISSN: 0929-6212
Electronic ISSN: 1572-834X
DOI: https://doi.org/10.1007/s11277-018-5450-x

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