ICONDENSATION-based hand tracking and gesture recognition with color and depth cues

Fa Wang Liu; Gang Yi Ding; Shan Qing Li; Yi Hua Xu

ICONDENSATION-based hand tracking and gesture recognition with color and depth cues

Fa Wang Liu^*, Gang Yi Ding, Shan Qing Li, Yi Hua Xu

^*此作品的通讯作者

计算机学院

Beijing Institute of Technology

科研成果: 期刊稿件 › 文章 › 同行评审

1 引用（Scopus）

摘要

Presents a hand tracking and gesture recognition algorithm for human-computer interaction with two web cameras. ICONDENSATION technique is employed to fuse color and depth to generate importance particles. To improve the efficiency and accuracy of likelihood evaluation, all samples are validated according to the energy function of active contour models, taking into account the contour information. Gesture recognition is realized through the maximum posterior estimation of several predefined templates. Experimental results showed that the proposed method works well even in cluttered scenarios.

源语言	英语
页（从-至）	1069-1072
页数	4
期刊	Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology
卷	27
期	12
出版状态	已出版 - 12月 2007

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引用此

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title = "ICONDENSATION-based hand tracking and gesture recognition with color and depth cues",

abstract = "Presents a hand tracking and gesture recognition algorithm for human-computer interaction with two web cameras. ICONDENSATION technique is employed to fuse color and depth to generate importance particles. To improve the efficiency and accuracy of likelihood evaluation, all samples are validated according to the energy function of active contour models, taking into account the contour information. Gesture recognition is realized through the maximum posterior estimation of several predefined templates. Experimental results showed that the proposed method works well even in cluttered scenarios.",

keywords = "Gesture recognition, Hand tracking, Human-computer interaction",

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AU - Ding, Gang Yi

AU - Li, Shan Qing

AU - Xu, Yi Hua

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N2 - Presents a hand tracking and gesture recognition algorithm for human-computer interaction with two web cameras. ICONDENSATION technique is employed to fuse color and depth to generate importance particles. To improve the efficiency and accuracy of likelihood evaluation, all samples are validated according to the energy function of active contour models, taking into account the contour information. Gesture recognition is realized through the maximum posterior estimation of several predefined templates. Experimental results showed that the proposed method works well even in cluttered scenarios.

AB - Presents a hand tracking and gesture recognition algorithm for human-computer interaction with two web cameras. ICONDENSATION technique is employed to fuse color and depth to generate importance particles. To improve the efficiency and accuracy of likelihood evaluation, all samples are validated according to the energy function of active contour models, taking into account the contour information. Gesture recognition is realized through the maximum posterior estimation of several predefined templates. Experimental results showed that the proposed method works well even in cluttered scenarios.

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KW - Hand tracking

KW - Human-computer interaction

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ER -

ICONDENSATION-based hand tracking and gesture recognition with color and depth cues

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