An Adaptive Superpixel Based Hand Gesture Tracking and Recognition System

We propose an adaptive and robust superpixel based hand gesture tracking system, in which hand gestures drawn in free air are recognized from their motion trajectories. First we employed the motion detection of superpixels and unsupervised image segmentation to detect the moving target hand using th...

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Main Authors: Hong-Min Zhu, Chi-Man Pun
Format: Article
Language:English
Published: Wiley 2014-01-01
Series:The Scientific World Journal
Online Access:http://dx.doi.org/10.1155/2014/849069
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author Hong-Min Zhu
Chi-Man Pun
author_facet Hong-Min Zhu
Chi-Man Pun
author_sort Hong-Min Zhu
collection DOAJ
description We propose an adaptive and robust superpixel based hand gesture tracking system, in which hand gestures drawn in free air are recognized from their motion trajectories. First we employed the motion detection of superpixels and unsupervised image segmentation to detect the moving target hand using the first few frames of the input video sequence. Then the hand appearance model is constructed from its surrounding superpixels. By incorporating the failure recovery and template matching in the tracking process, the target hand is tracked by an adaptive superpixel based tracking algorithm, where the problem of hand deformation, view-dependent appearance invariance, fast motion, and background confusion can be well handled to extract the correct hand motion trajectory. Finally, the hand gesture is recognized by the extracted motion trajectory with a trained SVM classifier. Experimental results show that our proposed system can achieve better performance compared to the existing state-of-the-art methods with the recognition accuracy 99.17% for easy set and 98.57 for hard set.
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publishDate 2014-01-01
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spelling doaj-art-b41a9ab10a6a4fd38cd167aacf0cad142025-08-20T03:20:51ZengWileyThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/849069849069An Adaptive Superpixel Based Hand Gesture Tracking and Recognition SystemHong-Min Zhu0Chi-Man Pun1Department of Computer and Information Science, University of Macau, MacauDepartment of Computer and Information Science, University of Macau, MacauWe propose an adaptive and robust superpixel based hand gesture tracking system, in which hand gestures drawn in free air are recognized from their motion trajectories. First we employed the motion detection of superpixels and unsupervised image segmentation to detect the moving target hand using the first few frames of the input video sequence. Then the hand appearance model is constructed from its surrounding superpixels. By incorporating the failure recovery and template matching in the tracking process, the target hand is tracked by an adaptive superpixel based tracking algorithm, where the problem of hand deformation, view-dependent appearance invariance, fast motion, and background confusion can be well handled to extract the correct hand motion trajectory. Finally, the hand gesture is recognized by the extracted motion trajectory with a trained SVM classifier. Experimental results show that our proposed system can achieve better performance compared to the existing state-of-the-art methods with the recognition accuracy 99.17% for easy set and 98.57 for hard set.http://dx.doi.org/10.1155/2014/849069
spellingShingle Hong-Min Zhu
Chi-Man Pun
An Adaptive Superpixel Based Hand Gesture Tracking and Recognition System
The Scientific World Journal
title An Adaptive Superpixel Based Hand Gesture Tracking and Recognition System
title_full An Adaptive Superpixel Based Hand Gesture Tracking and Recognition System
title_fullStr An Adaptive Superpixel Based Hand Gesture Tracking and Recognition System
title_full_unstemmed An Adaptive Superpixel Based Hand Gesture Tracking and Recognition System
title_short An Adaptive Superpixel Based Hand Gesture Tracking and Recognition System
title_sort adaptive superpixel based hand gesture tracking and recognition system
url http://dx.doi.org/10.1155/2014/849069
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