Pedestrian Detection Based on YOLOv2 with Skip Structure in Underground Coal Mine
Pedestrian detection is an important topic in object detection.Compared with other object detectors,YOLOv2 achieves high accuracy and fast speed for general object detection,however it degrades accuracy when detecting crowed pedestrians.In this paper,combining with the skip structure of FCN,we tailor the YOLOv2 network to improve the accuracy in detecting small pedestrians which appear in groups in underground coal mine.In this way,we propose two modified versions of YOLOv2 which are YWSSv1 and YWSSv2.Compared with YOLOv2,YWSSv1 slightly improves 0.1 mAP but keeps the same fast speed.YWSSv2 significantly gains 12 mAP higher than YOLOv2 but sacrifices its speed at just 5 FPS.
Object detection Pedestrian detection YOLOv2 FCN
Lin Wang Weishan Li Yuliang Zhang Chen Wei
College of Communication and Information Technology Xian University of Posts & Telecommunications X College of Economics and Management Xian University of Posts & Telecommunications Xian,China
国际会议
重庆
英文
1216-1220
2017-10-03（万方平台首次上网日期，不代表论文的发表时间）