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1999
IEEE

Video Sequence Learning and Recognition Via Dynamic Som

10 years 4 months ago
Video Sequence Learning and Recognition Via Dynamic Som
Information contained in the video sequences is crucial for an autonomous robot or a computer to learn and respond to its surrounding environment. In the past, robot vision is mainly concentrated on still image processing and small "image cube" processing [1]. Continuous video sequence learning and recognition is rarely addressed in the literature due to its high requirement on dynamic processing. In this paper, we propose a novel neural network structure called Dynamic Self-Organizing Map (DSOM) for video sequence processing. The proposed technique has been tested on real data sets, and the results validate its learning /recognition ability.
Qiong Liu, Yong Rui, Thomas S. Huang, Stephen E. L
Added 25 Oct 2009
Updated 25 Oct 2009
Type Conference
Year 1999
Where ICIP
Authors Qiong Liu, Yong Rui, Thomas S. Huang, Stephen E. Levinson
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