摘要
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 repre- sentation 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.
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 repre- sentation 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.
