Compressed spatio-temporal descriptors for video matching and retrieval

被引:3
|
作者
Alatas, O [1 ]
Javed, O [1 ]
Shah, M [1 ]
机构
[1] Univ Cent Florida, Sch Comp Sci, Orlando, FL 32816 USA
关键词
D O I
10.1109/ICPR.2004.1334669
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The contents of a video can be described in terms of appearance and motion of the scenes. In this paper we propose a compressed spatio-temporal descriptor that is suitable for video matching and retrieval tasks. We use a modified wavelet based compression technique that exploits the temporal redundancy of the data using optical flow. In order to achieve a compact flow representation, a spline based technique is used The optical flow field gives the directions along which the gray levels have regular variations in time. Wavelet decomposition along these directions results in fewer coefficients and thus higher compression. We demonstrate that the wavelet coefficients and flow parameters can be efficiently used for 1) video retrieval and matching, and 2) calculating spatio-temporal similarity between articulated objects. The results are demonstrated on several sequences.
引用
收藏
页码:882 / 885
页数:4
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