融合YOLO检测的多目标跟踪算法  

A multi-target tracking algorithm based on YOLO detection

作　　者：李星辰 柳晓鸣[1] 成晓男 LI Xing-chen;LIU Xiao-ming;CHENG Xiao-nan(College of Information Science and Technology,Dalian Maritime University,Dalian 116026,China)

机构地区：[1]大连海事大学信息科学技术学院,辽宁大连116026

出　　处：《计算机工程与科学》2020年第4期665-672,共8页Computer Engineering & Science

基　　金：福建海事局项目(2018Z0093)。

摘　　要：针对目前视频多目标跟踪过程中的遮挡问题,提出了一种融合YOLO v3的多目标检测和跟踪算法,选定基于检测跟踪的框架作为跟踪的整体框架,使用YOLO v3来实现对目标信息的检测工作,在选定某一检测类别的基础上,使用本文提出的跟踪算法,通过数据关联完成对此类别的多目标跟踪,并针对跟踪过程中的目标遮挡问题以及因目标遮挡而引起的轨迹跟踪异常的问题,提出了修正算法。测试视频中被遮挡的大部分目标都能准确地跟踪,但在背景移动时也会发生一部分目标身份互换的情况。所提出的算法在解决多目标跟踪中的遮挡问题时具有一定的准确性和实时性。Aiming at the occlusion problem in the current video multi-target tracking process, a multi-target detection and tracking algorithm combining YOLO v3 is proposed. The framework based on detection tracking is selected as the overall framework for tracking, and YOLO v3 is used to detect the target information. Based on the selected detection category, the proposed tracking algorithm is used to complete the multi-target tracking of this category through data association. Aiming at the problems of target occlusion in the tracking process and abnormal trajectory tracking caused by target occlusion, a correction algorithm is proposed. Most of the occluded targets in the test video can be accurately tracked in the experiment, but some target identity swaps will occur when the background moves. The proposed algorithm has certain accuracy and real-time performance in solving the occlusion problem in multi-target tracking.

关 键 词：YOLO V3 遮挡 数据关联 轨迹跟踪异常 多目标跟踪 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]