识别移动的手部形状

E. Holden, R. Owens
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引用次数: 17

摘要

本文提出了一种新的手部形状表示技术,该技术通过采用语音信号处理中的现有技术来表征手部的手指拓扑结构。该跟踪算法结合模式匹配和凝聚算法,从移动的手序列中确定手的最大凸子集的中心。手的形状特征表示的拓扑结构的手指区域的手使用线性预测编码参数集称为倒谱系数。实验结果证明了该方法从运动序列中检测形状特征的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Recognising moving hand shapes
The paper presents a new hand shape representation technique that characterises the finger-only topology of the hand, by adapting an existing technique from speech signal processing. From a moving hand sequence, the tracking algorithm determines the centre of the largest convex subset of the hand, using a combination of pattern matching and condensation algorithms. A hand shape feature represents the topological formation of the finger-only regions of the hand using a linear predictive coding parameter set called cepstral coefficients. Experimental results demonstrate the effectiveness of detecting the shape feature from motion sequences.
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