An adaptive local binary pattern for 3D hand tracking
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- 作者：Joongrock Kima ; jurock@yonsei.ac.kr" class="auth_mail" title="E-mail the corresponding authorAuthor Vitae ; Sunjin Yub ; sjyu@chu.ac.kr" class="auth_mail" title="E-mail the corresponding authorAuthor Vitae ; Dongchul Kimc ; dckim@msl.yonsei.ac.kr" class="auth_mail" title="E-mail the corresponding authorAuthor Vitae ; Kar-Ann Toha ; katoh@yonsei.ac.kr" class="auth_mail" title="E-mail the corresponding authorAuthor Vitae ; Sangyoun Leea ; syleee@yonsei.ac.kr" class="auth_mail" title="E-mail the corresponding authorAuthor Vitae
- 关键词：3D hand tracking ; Hand gesture recognition ; Human computer interaction ; Natural user interface
- 刊名：Pattern Recognition
- 出版年：2017
- 出版时间：January 2017
- 年：2017
- 卷：61
- 期：Complete
- 页码：139-152
- 全文大小：3116 K
文摘
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We propose an adaptive local binary pattern (ALBP) for depth image based applications.
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The proposed ALBP is invariant to both rotation and depth distance in range images.
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Using ALBP, we can extract object feature without using texture or color information.
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We apply the proposed ALBP for hand tracking using depth images.
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The tracking accuracy is compared with several existing hand trackers.