计算机应用 ›› 2015, Vol. 35 ›› Issue (1): 189-193.DOI: 10.11772/j.issn.1001-9081.2015.01.0189

• 人工智能 • 上一篇    下一篇

基于随机投影的加速度手势识别

刘红, 刘蓉, 李书玲   

  1. 华中师范大学 物理科学与技术学院, 武汉430079
  • 收稿日期:2014-08-07 修回日期:2014-09-20 出版日期:2015-01-01 发布日期:2015-01-26
  • 通讯作者: 刘蓉
  • 作者简介:刘红(1988-),女,湖北孝感人,硕士研究生,主要研究方向:模式识别;刘蓉(1969-),女,湖南安化人,副教授,博士,主要研究方向:智能信息处理、模式识别;李书玲(1988-),女,山东禹城人,硕士,主要研究方向:语音情感识别.
  • 基金资助:

    国家社会科学基金资助项目(12BTQ038).

Acceleration gesture recognition based on random projection

LIU Hong, LIU Rong, LI Shuling   

  1. School of Physical Science and Technology, Central China Normal University, Wuhan Hubei 430079, China
  • Received:2014-08-07 Revised:2014-09-20 Online:2015-01-01 Published:2015-01-26

摘要:

针对手势交互中手势信号的相似性及不稳定性,设计并实现了一种基于随机投影(RP)的加速度手势识别方法.识别系统包含训练阶段和测试阶段:训练阶段运用动态时间规整(DTW)和近邻传播(AP)算法对训练集中的每一个手势迹创建样本中心;测试阶段先通过计算未知手势迹与样本中心的距离找出候选姿势迹,然后用RP算法将候选手势迹和未知手势迹投影到低维子空间,把识别问题转换成l1-minimization问题来对未知的手势迹进行识别.在采集的2400个数据样本上进行了基于特定人和非特定人的实验,结果表明所提算法分别取得了98.41%和96.67%的识别率,该方法能够有效识别加速度手势动作.

关键词: 手势识别, 加速度手势, 动态时间规整, 近邻传播, 随机投影

Abstract:

Since the gesture signals in gesture interaction are similar and instable, an acceleration gesture recognition method based on Random Projection (RP) was designed and implemented. The system incorporated two parts, one was the training stage and the other was the testing stage. In the training stage, the system employed Dynamic Time Warping (DTW) and Affinity Propagation (AP) algorithms to create exemplars for each gesture; in the testing stage, the method firstly calculated the distance between the unknown trace and all exemplars to find the candidate traces, then used the RP algorithm to translate all the candidate traces and the unknown trace onto the same lower dimensional subspace, and by formulating the whole recognition problem as an l1-minimization problem, the unknown trace was recognized. The experimental results on 2400 gesture traces show that the proposed algorithm achieves an accuracy rate of 98.41% for specific individuals and 96.67% for unspecific individuals, and it can effectively identify acceleration gestures.

Key words: gesture recognition, acceleration gesture, Dynamic Time Warping (DTW), Affinity Propagation (AP), Random Projection (RP)

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