A sparse representation-based approach for video copy detection
A sparse representation-based approach for video copy detection
Jianmin LI(), Chen SUN, Bo ZHANG
State Key Laboratory of Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology (TNList), Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China
Content-based video copy detection becomes an active research field due to requirement of copyright protection, business intelligence, video retrieval, etc. Although it is assumed in the existing methods that reference database consists of original videos, these videos are difficult to be obtained in many practical cases. In this paper, a copy detection method based on sparse representation is proposed to make use of some imperfect prototypes of original videos maintained in the reference database. A query video is represented as a linear combination of all the videos in the database. Then we can determine that whether the query has sibling videos in the database based on distribution of coefficients and find them out based on reconstruction error. The experiments show that even with very limited dimensional feature, this method can achieve high performance.
Corresponding Author(s):
LI Jianmin,Email:lijianmin@mail.tsinghua.edu.cn
引用本文:
. A sparse representation-based approach for video copy detection[J]. Frontiers of Electrical and Electronic Engineering, 0, (): 208-215.
Jianmin LI, Chen SUN, Bo ZHANG. A sparse representation-based approach for video copy detection. Front Elect Electr Eng, 0, (): 208-215.
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