| 基于HOG和SVM的手势检测技术 |
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| 引用本文： | 郭文爽,王雪芳.基于HOG和SVM的手势检测技术[J].电子科技,2014,27(8):15-18. |
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| 作者姓名： | 郭文爽 王雪芳 |
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| 作者单位： | (西安电子科技大学 电子工程学院,陕西 西安 710071) |
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| 摘 要： | 将梯度方向直方图特征,结合支持向量机应用于手势检测中,可有效减弱光照、手势旋转等因素所带来的影响,并对HOG提取过程及参数设置进行了详细分析,同时结合线性SVM训练出了检测效果较好的分类器。通过实验证明,将HOG特征提取与SVM学习算法结合,手势检测的应用限制将大幅降低。
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| 关 键 词： | 梯度方向直方图 支持向量机 手势检测 |
Hand Gesture Detection Technology Based on HOG and SVM |
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| GUO Wenshuang,WANG Xuefang.Hand Gesture Detection Technology Based on HOG and SVM[J].Electronic Science and Technology,2014,27(8):15-18. |
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| Authors: | GUO Wenshuang WANG Xuefang |
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| Affiliation: | (School of Electronic Engineering,Xidian University,Xi'an 710071,China) |
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| Abstract: | In recent years, hand gesture detection becomes a research hotspot because of its broad application fields. In this paper, histograms of oriented gradient combined with support vector machine are used in hand gesture detection, which reduces the affect of illumination and rotation of gesture. HOG extraction and parameter settings are analyzed in detail, and a better classifier is trained based on HOG and linear SVM. Experiments show that the combination of HOG extraction and SWM can dramatically reduce the limitations on the application of hand gesture detection. |
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| Keywords: | HOG SVM hand gesture detection |
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