Multi-instance pedestrian detection algorithm based on improved Soft-NMS
In the task of pedestrian detection,the most important thing is to be able to quickly and accurately identify pedestrians in images or videos.Due to mutual occlusion among pedestri-ans in dense scenes,current pedestrian detection algorithms generally have problems of missed detection and false detection.In order to solve the above problems,this paper proposes a multi-instance pedestrian detection method based on the improved Soft-NMS algorithm.In order to reduce the inability of the detector to make accurate predictions due to the overlap between pe-destrians,a multi-instance detection method is introduced to make the detectors make relatively accurate predictions.And based on the Soft-NMS algorithm,the Set-Soft-NMS algorithm is im-proved to reduce the missed detection and false detection problems in pedestrian detection.The method proposed in this paper is tested on the public pedestrian detection data set,and the results show that the performance of the method proposed in this paper is better than other mainstream pedestrian detection algorithms.
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