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.

• Type: Conference
• Year: 1999
• Where: ICIP
• Authors: Qiong Liu, Yong Rui, Thomas S. Huang, Stephen E. Levinson
• Keywords: Dynamic Self-Organizing Map, ICIP 1999, Image Processing, Video Sequence Learning, Video Sequence Processing