Video Skimming and Summarization Based on Principal Component Analysis

Dan Lelescu1 and Dan Schonfeld2

1Compression Science, Inc.,
901 Campisi Way, Campbell,Ca., U.S.A.
dan@compressionscience.com

2Universityof Illinois at Chicago,
851 S. Morgan St., Chicago, IL.,U.S.A.
ds@eecs.uic.edu

Abstract. An increasing number of applications such as content-based multimedia retrieval in a distributed system and low-bitrate video communications, require the efficient processing and transmission of video information. In content-based video retrieval, video segmentation produces video shots characterized by a certain degree of visual cohesiveness. The number of relevant video shots returned by the system can be very large, thereby requiring significant transmission bandwidth. In this paper, we present a new algorithm for the representation of visual information contained in video segments. The approach is based on Principal Component Analysis and takes advantage of the characteristics of the data in video shots, and the optimal energy compaction properties of the transform. The algorithm can use additional information about video sequences provided by a video analysis and retrieval system, such as a visual change estimator, and a video object tracking module.

LNCS 2216, p. 128 ff.

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Online publication: October 10, 2001
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