【摘要】 目的:交通标志的检测是车载辅助系统的关键环节之一,针对YOLO V3检测算法得到的检测结果存在目标框不精确的问题,提出改进交通标志目标检测算法。方法:YOLO V3是当前目标检测算法中检测召回率高且速度较优的算法,但在定位上不够准确。为解决该问题,本文采用流行排序算法对得到的检测框进行二次修正,从而使得目标定位精度提升。结果:通过结合YOLO V3和流行排序算法使目标检测框的交并比提升了3%～9%。结论:通过YOLO V3和Ranking Saliency的结合能够使得目标检测的定位精度提高。更多还原

【Abstract】 Aims:The detection algorithm is the key part of a vehicle-assisted system.Aiming at the problem of inaccurate detection target frame obtained by YOLO V3 detection algorithm,an algorithm for improving traffic sign target detection was proposed.Methods:YOLO V3 has high recall rate and the fastest speed in the current target detection algorithm,but the positioning is not accurate.In order to solve this problem,this paper proposed to use the Ranking Saliency algorithm to correct the predicted position of the target.Results:By combining the YOLO V3 and Ranking Saliency algorithms,the IoU of the target prediction box increased by 3%-9%.Conclusions:The experiments show that the proposed algorithm can improve the target positioning accuracy.更多还原