基于傅立叶描述子的RGB-D手部姿态估计

Zihao Rong, Dehui Kong, Shaofan Wang, Baocai Yin
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引用次数: 3

摘要

民用深度传感器的出现使得基于视觉的人机交互通过手势成为可能,这主要依赖于手部姿势估计技术。在这项工作中,提出了一种新的手部姿态估计方法,该方法主要基于预先构建的手部模板库中的基于傅里叶描述符的索引。该方法以颜色深度为输入,在预处理中提取必要的手部信息,通过从粗略到精确两个阶段估计手部姿态。提出的手姿估计方法简单有效;定量和定性评价显示了其有效性。
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RGB-D Hand Pose Estimation Using Fourier Descriptor
The emergence of civil-use depth sensors made vision-based man-machine interaction possible through hand gesture, which relies fundamentally on hand pose estimation techniques. In this work, a novel hand pose estimation method is proposed, based essentially on Fourier-descriptor-based indexing in a pre-built hand template library. The proposed method takes color-depth as input, extracts necessary hand information in preprocessing, and estimate hand pose through two stages, from rough to accurate. This proposed hand pose estimation method is simple and efficient; quantitative and qualitative evaluations exhibit its effectiveness.
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