用于步态识别的多层窗口图像矩

陈实; 马天骏; 黄万红; 高有行

doi:10.3724/SP.J.1146.2007.00247

用于步态识别的多层窗口图像矩

doi: 10.3724/SP.J.1146.2007.00247

基金项目:

宁波市自然科学基金(2008A61011)和陕西省自然科学基金 (2006F48)资助课题

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出版历程
- 收稿日期: 2007-08-08
- 修回日期: 2008-08-13
- 刊出日期: 2009-01-19

A Multi-layer Windows Method of Moments for Gait Recognition

摘要

摘要: 该文提出了一种以局部性矩统计量作为步态特征描述的步态识别方法。首先提取行人二值轮廓序列，构造一种基于直方图的轮廓点分布特征检测出步态周期；然后生成彩色步态运动历史图像CGHI描述步态的空间特征和时间信息；继而设计了多层同心矩形窗口分割CGHI，提取出一组矩形环窗口的矩特征量作为步态特征，在此基础上实现了步态识别。在Soton数据库上进行了实验，提出算法的正确识别率可达87.2%，优于现有方法。
- 步态识别;不变矩;多层窗口;历史图像
Abstract: A feature representation method based on multi-layer local moment invariants for gait analysis and recognition applications is developed. The method includes following steps: first, silhouette extraction is performed for each image sequence. Secondly, the gait cycle is detected by a histogram-based approach. Thirdly, a scalarvalued CGHI(Colored Gait History Images) is proposed to describe how human walking is evolved. To improve the recognition rate, the CGHI is decomposed into a sequnce of muti-layer rectangle windows. The moment invariants from the window are used as the gait features and finally used to recognize gait. The correct classification rate of 87.2% is achieved on Soton database, which show that the method outperforms the exist methods.

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