Acousto-optic Multi-source Information Fusion Algorithm for Outdoor Pedestrian Detection

Abstract

Abstract The inefficiency of traditional rescue methods is a serious threat to the life and health of outdoor people in distress, so the research on pedestrian identification for outdoor rescue has important theoretical significance and application value. In order to solve the problem of low probability of recognition based on signal information in traditional methods, an outdoor pedestrian recognition model based on acousto-optic information fusion is constructed. Considering the characteristics of the information source, the directional gradient histogram of the infrared image and the Mel Cepstral Coefficients of the acoustic signal are selected as the factors affecting the recognition probability, and the pedestrian recognition probability correlation equation is deduced; Based on the improved D-S evidence theory of fuzzy system, a pedestrian recognition method based on infrared image and sound signal is proposed, and the mapping relationship between two kinds of information sources and detection probability is established to improve the pedestrian recognition probability. The hardware-in-the-loop simulation results show that the pedestrian recognition probability of fusion of infrared image and sound signal is higher than that of single information, which provides an efficient and reliable method for outdoor rescue.