Kullback-Leilber情報量を用いた審美的な構図評価によるロボットの自律的視点選択

抄録

In this paper, we propose an optimal viewpoint selection system for monitoring robots to search for the optimal viewpoint of a scene with the highest aesthetic property. We first put forward a novel aesthetic evaluation method by the use of Kullback-Leilber divergence, considering the directional information of each target according to some famous composition rules in the field of photography. Then based on the evalution results, we propose a viewpoint selection method by Kullback-Leilber Divergence Minimization. At last, the effectiveness of our optimal viewpoint selection system is confirmed with experiments.