| 角度与动态时间归一化的步态识别 |
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| 引用本文： | 陈璇,吴清江,路远. 角度与动态时间归一化的步态识别[J]. 华侨大学学报(自然科学版), 2010, 31(1) |
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| 作者姓名： | 陈璇 吴清江 路远 |
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| 作者单位： | 华侨大学,计算机科学与技术学院,福建,泉州,362021;华侨大学,计算机科学与技术学院,福建,泉州,362021;华侨大学,计算机科学与技术学院,福建,泉州,362021 |
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| 基金项目： | 福建省自然科学基金资助项目(2006J0036) |
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| 摘 要： | 首先选择具有鲁棒性的累积角度特征作为步态特征,并对每个序列提取角度特征,构成特征矩阵.根据步态序列具有线性特征的特点,在提取步态周期的基础上,采用动态时间归一化做序列匹配,计算最终的特征距离.实验结果表明,算法具有快速、稳健的特征,并且在120人的步态数据库0(°)与90(°)的视角上取得较好的识别率.
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| 关 键 词： | 步态识别 角度特征 动态时间归一化 距离计算 |
Gait Recognition of Angle and Dynamical Time Normalization |
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| CHEN Xuan,WU Qing-jiang,LU Yuan. Gait Recognition of Angle and Dynamical Time Normalization[J]. Journal of Huaqiao University(Natural Science), 2010, 31(1) |
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| Authors: | CHEN Xuan WU Qing-jiang LU Yuan |
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| Affiliation: | College of Information Science and Engineering;Huaqiao University;Quanzhou 362021;China |
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| Abstract: | Firstly, robust accumulative angle feature is chosen to be the basic gait feature, and the angle feature of sequences are saved as matrixes. Secondly, on the basis of gait sequence linearity, extract the gait cycle, and then introduce dynamical time normalization into sequence matching, to get the final feature distance. Experimental result shows that the proposed algorithm performs an encouraging recognition rate with relatively lower computational cost at 0 (°) and 90 (°) viewing angle in large gait dataset for 120 persons. |
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| Keywords: | gait recognition angle feature dynamical time normalization distance calculation |
| 本文献已被 CNKI 万方数据 等数据库收录！ |
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