A Robust Hand Tracking Approach Based on Modified Tracking-Learning-Detection Algorithm

被引：3

作者：

Shi, Haibin ^{[1
]}

Lin, Zhanjian ^{[1
]}

Tang, Weiwei ^{[1
]}

Liao, Bruce ^{[2
]}

Wang, Jolly ^{[2
]}

Zheng, Lingxiang ^{[1
]}

机构：

[1] Xiamen Univ, Sch Informat Sci & Engn, Xiamen 361005, Peoples R China

[2] Intel China Co Ltd, Shanghai 200241, Peoples R China

来源：

MULTIMEDIA AND UBIQUITOUS ENGINEERING | 2014年 / 308卷

关键词：

Back Projection; Tracking-Learning-Detection; Hand Tracking;

D O I：

10.1007/978-3-642-54900-7_2

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Hand tracking is an essential step for dynamic gesture recognition which catches a lot of attention in the field of gesture interaction. In this paper, we present a robust hand tracking approach for unconstrained videos based on modified Tracking-Learning-Detection (TLD) algorithm, named BP-TLD. By introducing a skin color feature to the model, we make the algorithm more suitable for hand tracking. The experimental results show that BP-TLD has a better performance compared with other tracking algorithms such as TLD, MSEPF and Handvu. It indicates that our approach can meet the requirements of robustness and real-time better for the frontal-view vision-based human computer interactions.

引用

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页码：9 / 15

页数：7

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