Information based hybrid performance evaluation criterion for panorama refreshing in robotic tele-observation

In wide environment surveillance systems, panoramas are widely used to display environmental information. Because of the diversity of environment, refreshing the environment uniformly is unscientific. This paper presents a hybrid performance evaluation criterion based on information entropy. In the definition of this criterion, the effective degree of information, the importance of information and refresh demand degree are taken into account. Using the performance evaluation criterion proposed in this paper, a refresh path can be found to refresh the panorama with different importance harmoniously and keep the panorama with higher information entropy. It is beneficial for surveillance systems to find the interested target. The experiment results show that the probability of target acquisition is increased by 24.7% and the mean acquisition time is shortened by 37.7%. Compared with the typical zigzag path method, the performance evaluation criterion is scientific and practical.

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