Enhanced Multiple-Object Tracking Using Delay Processing and Binary-Channel Verification
文献类型：期刊论文
| 作者 | M.Y.Li; X.He; Z.H.Wei; J.Wang; Z.Y.Mu; A.Kuijper |
| 刊名 | Applied Sciences-Basel
 |
| 出版日期 | 2019 |
| 卷号 | 9期号:22页码:19 |
| 关键词 | multiple object tracking,identity consistency,single object tracking,association,Chemistry,Engineering,Materials Science,Physics |
| DOI | 10.3390/app9224771 |
| 英文摘要 | 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. |
| URL标识 | 查看原文 |
| 语种 | 英语 |
| 源URL | [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. |
入库方式： OAI收割
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。