.png){kind=icon}
返回
From sample selection to model update: A robust online visual tracking algorithm against drifting
.png){kind=icon}
PRE
AI
DOI：10.1016/j.neucom.2015.08.080.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
This paper proposes an online tracking algorithm that employs a confidence combinatorial map model. Drifting is a problem that easily occurs in object tracking and most of the recent tracking algorithms have attempted to solve this problem. In this paper, we propose a confidence combinatorial map that describes the structure of the object, based on which the confidence combinatorial map model is developed. The model associates the relationship between the object in the current frame and that in the previous frame. On the strength of this relationship, more precisely classified samples can be selected and are employed in the model update stage, which directly influences the occurrence of the tracking drift. The proposed algorithm was estimated on several public video sequences and the performance was compared with several state-of-the-art algorithms. The experiments demonstrate that the proposed algorithm outperforms other comparative algorithms and gives a very good performance. (C) 2015 Elsevier B.V. All rights reserved.
Keyword:
Visual tracking
Confidence combinatorial map
Model update
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
6.5
论文数:
2.5W
被引数:
6.5W
机构
引用论文
Crystalline‐State Reaction with Allosteric Effect in Spin‐Crossover, Interpenetrated Networks with Magnetic and Optical Bistability具有磁和光学双稳态的自旋交叉，互穿网络中具有变构效应的晶态反应
PREAI
分享收藏Increased Bacillus Calmette-Guérin Treatment Intensity Associated With Improved Outcomes in Elderly Patients With Non–Muscle-invasive Bladder Cancer in United States Clinical Practice.png)
Urology
UrologyIF0
PREAI
分享收藏Discovery of the water scavenger beetle genus Brownephilus Mouchamps in Turkey (Coleoptera, Hydrophilidae, Hydrophilini)ZooKeys
OAAI
ZooKeysIF0
OAAI分享收藏
查看更多内容