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基于自适应子空间在线PCA的手势识别

, PP. 299-304

Keywords: 在线学习,在线PCA,自适应子空间,手势识别

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Abstract:

基于视觉的手势识别系统的学习一般是离线的,导致系统对新手势的正确识别需要重新离线学习,因此系统实时性、可扩展性和鲁棒性较差,不适合认知发育的智能框架。文中提出了基于自适应子空间在线PCA的手势识别方法。该方法通过计算样本投影系数向量的PCA来实现子空间在线更新,并根据新样本与已学习样本的差异程度,调整子空间更新策略,使算法自适应于不同情况,减少计算和存储开销,实现增量的在线学习和识别手势的目的。实验表明,本文方法能处理未知手势问题,实现手势在线积累和更新,逐渐增强系统识别能力。

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