Enhanced Multiple-Object Tracking Using Delay Processing and Binary-Channel Verification

doi:10.3390/app9224771

CIOMP OpenIR

	Enhanced Multiple-Object Tracking Using Delay Processing and Binary-Channel Verification
	M.Y.Li; X.He; Z.H.Wei; J.Wang; Z.Y.Mu; A.Kuijper
	2019
发表期刊	Applied Sciences-Basel
卷号	9 期号:22 页码:19
摘要	Tracking objects over time, i.e., identity (ID) consistency, is important when dealing with multiple object tracking (MOT). Especially in complex scenes with occlusion and interaction of objects this is challenging. Significant improvements in single object tracking (SOT) methods have inspired the introduction of SOT to MOT to improve the robustness, that is, maintaining object identities as long as possible, as well as helping alleviate the limitations from imperfect detections. SOT methods are constantly generalized to capture appearance changes of the object, and designed to efficiently distinguish the object from the background. Hence, simply extending SOT to a MOT scenario, which consists of a complex scene with spatially mixed, occluded, and similar objects, will encounter problems in computational efficiency and drifted results. To address this issue, we propose a binary-channel verification model that deeply excavates the potential of SOT in refining the representation while maintaining the identities of the object. In particular, we construct an integrated model that jointly processes the previous information of existing objects and new incoming detections, by using a unified correlation filter through the whole process to maintain consistency. A delay processing strategy consisting of the three parts-attaching, re-initialization, and re-claiming-is proposed to tackle drifted results caused by occlusion. Avoiding the fuzzy appearance features of complex scenes in MOT, this strategy can improve the ability to distinguish specific objects from each other without contaminating the fragile training space of a single object tracker, which is the main cause of the drift results. We demonstrate the effectiveness of our proposed approach on the MOT17 challenge benchmarks. Our approach shows better overall ID consistency performance in comparison with previous works.
关键词	multiple object tracking,identity consistency,single object tracking,association,Chemistry,Engineering,Materials Science,Physics
DOI	10.3390/app9224771
URL	查看原文
收录类别	SCI
语种	英语
引用统计
文献类型	期刊论文
条目标识符	http://ir.ciomp.ac.cn/handle/181722/63262
专题	中国科学院长春光学精密机械与物理研究所
推荐引用方式 GB/T 7714	M.Y.Li,X.He,Z.H.Wei,et al. Enhanced Multiple-Object Tracking Using Delay Processing and Binary-Channel Verification[J]. Applied Sciences-Basel,2019,9(22):19.
APA	M.Y.Li,X.He,Z.H.Wei,J.Wang,Z.Y.Mu,&A.Kuijper.(2019).Enhanced Multiple-Object Tracking Using Delay Processing and Binary-Channel Verification.Applied Sciences-Basel,9(22),19.
MLA	M.Y.Li,et al."Enhanced Multiple-Object Tracking Using Delay Processing and Binary-Channel Verification".Applied Sciences-Basel 9.22(2019):19.

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