基于视觉的目标检测与跟踪综述  

Vision-based Object Detection and Tracking: A Review

作　　者：尹宏鹏[1,2] 陈波[2] 柴毅[2] 刘兆栋[2] YIN Hong-Peng CHEN Bo CHAI Yi LIU Zhao-Dong(Key Laboratory of Dependable Service Computing in Cyber Physical Society （Chongqing University）, Ministry of Education, Chongqing 400030 College of Automation, Chongqing Uni- versity, Chongqing 400044)

机构地区：[1]信息物理社会可信服务计算教育部重点实验室(重庆大学),重庆400030 [2]重庆大学自动化学院,重庆400044

出　　处：《自动化学报》2016年第10期1466-1489,共24页Acta Automatica Sinica

基　　金：国家自然科学基金(61203321);重庆市基础科学与前沿研究技术专项重点项目(cstc2015jcyj B0569);中央高校基本科研业务专项基金(106112016CDJZR175511;106112015CDJXY170003);重庆市研究生科研创新项目(CYB14023)资助~~

摘　　要：基于视觉的目标检测与跟踪是图像处理、计算机视觉、模式识别等众多学科的交叉研究课题,在视频监控、虚拟现实、人机交互、自主导航等领域,具有重要的理论研究意义和实际应用价值.本文对目标检测与跟踪的发展历史、研究现状以及典型方法给出了较为全面的梳理和总结.首先,根据所处理的数据对象的不同,将目标检测分为基于背景建模和基于前景建模的方法,并分别对背景建模与特征表达方法进行了归纳总结.其次,根据跟踪过程有无目标检测的参与,将跟踪方法分为生成式与判别式,对基于统计的表观建模方法进行了归纳总结.然后,对典型算法的优缺点进行了梳理与分析,并给出了其在标准数据集上的性能对比.最后,总结了该领域待解决的难点问题,对其未来的发展趋势进行了展望.Vision-based object detection and tracking is an active research topic in image processing, computer vision,pattern recognition, etc. It finds wide applications in video surveillance, virtual reality, human-computer interaction,autonomous navigation, etc. This survey gives a detail overview of the history, the state-of-the-art, and typical methods in this domain. Firstly, object detection is divided into background-modeling-based methods and foreground-modelingbased methods according to the different data objects processed. Background modeling and feature representation are further summarized respectively. Then, object tracking is divided into generative and discriminative methods according to whether the detection process is involved. Statistical based appearance modeling is presented. Besides, discussions are presented on the advantages and drawbacks of typical algorithms. The performances of different algorithms on benchmark datasets are given. Finally, the outstanding issues are summarized. The future trends of this field are discussed.

关 键 词：计算机视觉 目标检测 目标跟踪 背景建模 表观建模 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]