关键词: 边界特征, 运动特征, 前景区域, 行人目标检测, 灰度值

Abstract: Under the thermal infrared video surveillance, in order to solve the problem of the gray value inversion in thermal infrared image caused by the changes in ambient temperature, this paper proposes a method of extracting the foreground area of pedestrian objects by the fusion of boundary feature and motion feature in the thermal infrared images. First, the boundary feature of the pedestrian objects are extracted by using the significant differences existing between the pedestrian objects and the surrounding environment, and then the extracted boundary feature is subjected to area filling, which is followed by the elimination of the false detection objects by using thermal infrared pedestrian objects classifier, thus obtaining the final boundary feature extraction results. Second, the motion feature of the pedestrian objects are obtained by using the motion information between adjacent frames, and then the resulting motion feature is subjected to the morphological processing, which is followed by the elimination of the false detection objects by using thermal infrared pedestrian objects classifier, thus obtaining the final motion feature extraction results. Finally, the final boundary feature extraction results and the final motion feature extraction results are fused to obtain the final detection results. Our experiments show that the proposed method can effectively reduce the adverse effects brought about by the changes in ambient temperature, and further improve the extraction accuracy of foreground area of the pedestrian objects on the OSU and LSI thermal infrared image pedestrian objects detection dataset.

Key words: boundary feature, motion feature, foreground area, pedestrian objects detection, gray value