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

^*Corresponding author for this work

School of Computer Science and Technology

Beijing Institute of Technology

Research output: Contribution to journal › Article › peer-review

1 Citation (Scopus)

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.

Original language	English
Pages (from-to)	1069-1072
Number of pages	4
Journal	Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology
Volume	27
Issue number	12
Publication status	Published - Dec 2007

Keywords

Gesture recognition
Hand tracking
Human-computer interaction

Cite this

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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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year = "2007",

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AU - Liu, Fa Wang

AU - Ding, Gang Yi

AU - Li, Shan Qing

AU - Xu, Yi Hua

PY - 2007/12

Y1 - 2007/12

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.

KW - Gesture recognition

KW - Hand tracking

KW - Human-computer interaction

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SN - 1001-0645

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JF - Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology

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ER -

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

Abstract

Keywords

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