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基于局域性约束线性编码的人体动作识别

白琛 孙军华

白琛, 孙军华. 基于局域性约束线性编码的人体动作识别[J]. 北京航空航天大学学报, 2015, 41(6): 1122-1127. doi: 10.13700/j.bh.1001-5965.2014.0414
引用本文: 白琛, 孙军华. 基于局域性约束线性编码的人体动作识别[J]. 北京航空航天大学学报, 2015, 41(6): 1122-1127. doi: 10.13700/j.bh.1001-5965.2014.0414
BAI Chen, SUN Junhua. Human action recognition based on locality-constrained linear coding[J]. Journal of Beijing University of Aeronautics and Astronautics, 2015, 41(6): 1122-1127. doi: 10.13700/j.bh.1001-5965.2014.0414(in Chinese)
Citation: BAI Chen, SUN Junhua. Human action recognition based on locality-constrained linear coding[J]. Journal of Beijing University of Aeronautics and Astronautics, 2015, 41(6): 1122-1127. doi: 10.13700/j.bh.1001-5965.2014.0414(in Chinese)

基于局域性约束线性编码的人体动作识别

doi: 10.13700/j.bh.1001-5965.2014.0414
详细信息
    作者简介:

    白琛(1990—),男,天津人,硕士研究生,chenbai@aspe.buaa.edu.cn

    通讯作者:

    孙军华(1975—),男,湖北荆门人,教授,sjh@buaa.edu.cn,主要研究方向为视觉测量、图像分析与识别.

  • 中图分类号: TP391.4

Human action recognition based on locality-constrained linear coding

  • 摘要: 针对动作特征类内差异较大,导致动作分类识别率较低的问题,以及当前算法在计算复杂度和扩展可识别动作类别方面的不足,提出一种基于局域性约束线性编码(LLC)的人体动作识别方法.算法将人体关节的位置、速度和加速度作为局部动作特征;采用局域性约束线性编码对局部动作特征求解稀疏表达,从而减小特征的类内差异,增强区别力;由于编码方法具有解析解,方法处理视频速度可达760帧/s;词典由K均值法分别对每类数据学习得到的子词典组成,使算法在扩展可识别动作类别时无需全局优化.此外,为避免了词典较大情况下分类器的过拟合现象,利用词典元素类别对编码系数进行降维.在使用深度摄像机获得的MSR-Action3D数据库上对所提出的方法进行验证,取得了85.7%的识别率.

     

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出版历程
  • 收稿日期:  2014-07-10
  • 刊出日期:  2015-06-20

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