A Traffic Surveillance Multi-Scale Vehicle Detection Object Method Base on Encoder-Decoder
Feng Hong, Changhua Lu, Chun Liu, Ruru Liu, Wei Ju
Abstract
Aiming at the problem that it is difficult for traffic monitoring videos to detect multi-scale vehicle targets, especially small vehicle targets in complex scenarios, a codec-based vehicle detection algorithm is proposed. This algorithm is based on YOLOv3. In order to solve the multi-scale vehicle target detection problem, a new multi-level feature pyramid structure added with the codec module to detect vehicle targets of different scales. The experimental results on the KITTI dataset and UA-DETRAC dataset confirm that the algorithm in this paper has achieved good detection results for vehicle targets in various environments and at various scales in the surveillance video, especially for small vehicle targets, which can better meet the actual application demand.