计算机科学 ›› 2023, Vol. 50 ›› Issue (4): 77-87.doi: 10.11896/jsjkx.220300173
伍瀚1, 聂佳浩1, 张照娓1, 何志伟1,2, 高明煜1,2
WU Han1, NIE Jiahao1, ZHANG Zhaowei1, HE Zhiwei1,2, GAO Mingyu1,2
摘要： 多目标跟踪(MOT)旨在从给定视频序列中输出所有目标的运动轨迹并维持各目标的身份。近年来,由于其在学术研究和实际应用中具有巨大潜力,因此受到越来越多的关注并成为计算机视觉的热点研究方向。当前主流的跟踪方法将MOT任务拆分为目标检测、特征提取以及数据关联3个子任务,这种思路已经得到了良好的发展。然而,由于实际跟踪过程中存在遮挡和相似物体干扰等挑战,保持鲁棒跟踪仍是当前的研究难点。为了满足在复杂场景下对多个目标准确、鲁棒、实时跟踪的要求,需要对MOT算法作进一步研究与改进。目前已有关于MOT算法的综述,但仍存在总结不够全面及缺少最新研究成果等问题。因此,首先介绍了MOT的原理及挑战;其次,通过总结最新的研究成果对MOT算法进行了归纳和分析,根据各类算法为完成3个子任务所采用的跟踪范式将其分为三大类,即分离检测与特征提取、联合检测与特征提取及联合检测和跟踪,并且详细说明了各类跟踪算法的主要特征;然后,将所提算法与当前主流算法在常用数据集上进行了对比分析,讨论了当前算法的优缺点及发展趋势,展望了未来的研究方向。
中图分类号:
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