In computer vision, many systems for video surveillance have been studied and developed. Finding appropriate features is very important especially for robust object tracking. This paper proposes a new system employing an evolutionary technique to track moving objects such as pedestrian effectively. In the proposed system, a number of agents are generated for each object, and independently search and move to the predicted position from features of local region. Each agent can select the appropriate feature relevant for the scene and the object to track by an evolutionary method using two values of feature effectiveness: normality and separateness. We carried out experiments using some scenes in an outside parking. The proposed system showed much better performance compared with the conventional system and a system using particle filter.
|ジャーナル||Transactions of the Japanese Society for Artificial Intelligence|
|出版ステータス||Published - 2010 8 30|
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