Abstract
Pedestrian detection plays an important role in unmanned technology. Because of the high efficiency and robustness of the deformable part model, it has been widely applied to the field of pedestrian detection. At present, how to effectively reduce the risk of partial screening of pedestrians has been based on the pattern recognition of pedestrian detection technology in the hot spots. Aiming at this problem, after analyzing the deformable part model deeply, this paper creatively proposes a pedestrian detection method with improved deformable part model. By training the two-pedestrian deformable part model, the method is adopted to reduce the pedestrian detection in the pedestrian detection by matching the image sub-region and matching the matching result. It is shown that the method can improve the detection efficiency while ensuring the detection efficiency, while ensuring the effectiveness of the whole algorithm to meet the real-time requirements of unmanned technology.
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