Lve Chen, C. Deqiang, Kou Qiqi, Zhuang Huandong, Liu Haixiang
{"title":"基于YOLOv3和asm的目标跟踪算法","authors":"Lve Chen, C. Deqiang, Kou Qiqi, Zhuang Huandong, Liu Haixiang","doi":"10.12086/OEE.2021.200175","DOIUrl":null,"url":null,"abstract":"In order to solve the problem of loss when the target encounters occlusion or the speed is too fast during the automatic tracking process, a target tracking algorithm based on YOLOv3 and ASMS is proposed. Firstly, the target is detected by the YOLOv3 algorithm and the initial target area to be tracked is determined. After that, the ASMS algorithm is used for tracking. The tracking effect of the target is detected and judged in real time. Reposi-tioning is achieved by quadratic fitting positioning and the YOLOv3 algorithm when the target is lost. Finally, in order to further improve the efficiency of the algorithm, the incremental pruning method is used to compress the algorithm model. Compared with the mainstream algorithms, experimental results show that the proposed algorithm can solve the lost problem when the tracking target is occluded, improving the accuracy of target detection and tracking. It also has advantages of low computational complexity, time-consuming, and high real-time performance.","PeriodicalId":39552,"journal":{"name":"光电工程","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Target tracking algorithm based on YOLOv3 and ASMS\",\"authors\":\"Lve Chen, C. Deqiang, Kou Qiqi, Zhuang Huandong, Liu Haixiang\",\"doi\":\"10.12086/OEE.2021.200175\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to solve the problem of loss when the target encounters occlusion or the speed is too fast during the automatic tracking process, a target tracking algorithm based on YOLOv3 and ASMS is proposed. Firstly, the target is detected by the YOLOv3 algorithm and the initial target area to be tracked is determined. After that, the ASMS algorithm is used for tracking. The tracking effect of the target is detected and judged in real time. Reposi-tioning is achieved by quadratic fitting positioning and the YOLOv3 algorithm when the target is lost. Finally, in order to further improve the efficiency of the algorithm, the incremental pruning method is used to compress the algorithm model. Compared with the mainstream algorithms, experimental results show that the proposed algorithm can solve the lost problem when the tracking target is occluded, improving the accuracy of target detection and tracking. It also has advantages of low computational complexity, time-consuming, and high real-time performance.\",\"PeriodicalId\":39552,\"journal\":{\"name\":\"光电工程\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-02-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"光电工程\",\"FirstCategoryId\":\"1087\",\"ListUrlMain\":\"https://doi.org/10.12086/OEE.2021.200175\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Engineering\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"光电工程","FirstCategoryId":"1087","ListUrlMain":"https://doi.org/10.12086/OEE.2021.200175","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Engineering","Score":null,"Total":0}
Target tracking algorithm based on YOLOv3 and ASMS
In order to solve the problem of loss when the target encounters occlusion or the speed is too fast during the automatic tracking process, a target tracking algorithm based on YOLOv3 and ASMS is proposed. Firstly, the target is detected by the YOLOv3 algorithm and the initial target area to be tracked is determined. After that, the ASMS algorithm is used for tracking. The tracking effect of the target is detected and judged in real time. Reposi-tioning is achieved by quadratic fitting positioning and the YOLOv3 algorithm when the target is lost. Finally, in order to further improve the efficiency of the algorithm, the incremental pruning method is used to compress the algorithm model. Compared with the mainstream algorithms, experimental results show that the proposed algorithm can solve the lost problem when the tracking target is occluded, improving the accuracy of target detection and tracking. It also has advantages of low computational complexity, time-consuming, and high real-time performance.