A compressed sensing approach for query by example video retrieval

被引：0
作者：
Sujuan Hou
Shangbo Zhou
Muhammad Abubakar Siddique
机构：
[1] Chongqing University,College of Computer Science
[2] Chongqing University,Key Laboratory of Dependable Service Computing in Cyber Physical Society, Ministry of Education
来源：
Multimedia Tools and Applications | 2014年 / 72卷
关键词：
Video retrieval; Video signal processing; Compressed sensing; Similarity measure;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Recently, compressed Sensing (CS) has theoretically been proposed for more efficient signal compression and recovery. In this paper, the CS based algorithms are investigated for Query by Example Video Retrieval (QEVR) and a novel similarity measure approach is proposed. Combining CS theory with the traditional discrete cosine transform (DCT), better compression efficiency for spatially sparse is achieved. The similarity measure from three levels (frame level, shot level and video level, respectively) is also discussed. For several different kinds of natural videos, the experimental results demonstrate the effectiveness of system by the proposed method.
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页码：3031 / 3044
页数：13
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