Spatio-temporal relationships and video object extraction

Yining Deng and B.S. Manjunath
Department of Electrical and Computer Engineering,
University of California, Santa Barbara, CA 93106-9560.
{deng, manj}


An object-based representation for video data can facilitate video search and content analysis. Detecting physical meaningful video object is a challenging open issue, and requires intelligent spatio-tempral segmentation and tracking. Normally,this is done through spatio- temporal segmentation and region tracking. In this work, some of the practical issues of segmentation and tracking problems are addressed. Due to the limitation of using low-level visual features in the segmentation, the tracked regions are more likely to be fragmented parts of some meaningful objects. However, if a collection of video shots that contain a particular object of interest are given, spatio-temporal correlations would exist between the neighboring regions of the object. A method of minig association rules is used to discover these patterns and thus to find possible objects in the scene. Initial experimental results of this approach are shown.
[PDF] [BibTex]
Y. Deng and B. S. Manjunath,
32nd Asilomar Conference on Signals, Systems and Computers, vol. 1, pp. 895-899, Pacific Grove, CA, Nov. 1998.
Node ID: 264 , DB ID: 60 , VRLID: 62 , Lab: VRL , Target: Proceedings
Subject: [Object-Based Retrieval] « Look up more