基于三维行为数据匹配的身份识别方法
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摘要
针对传统的身份识别方法由于在对采集的图像进行去噪处理时也最大程度的去除了行为前景特征,使得行为特征形式无法统一,导致身份识别不准确的问题。提出采用三维行为数据匹配的身份识别方法,通过均值滤波法对图像进行去噪处理。使用人体行为图像的一阶差分,求出各像素处的平均平方梯度矩阵,依据特征值给出角点响应确定Harris角点,利用Harris角点对人体行为特征进行提取。并将两个完全相同的摄像机构成的两个图像平面置于同一个平面上,模仿人眼获得物体位置信息的原理,获取人体行为数据的三维坐标及全部特征点的三维坐标。通过计算搜索窗口内对应点的相关系数和阈值的比较来实现特征点匹配,完成身份识别。仿真结果表明,所提方法相比传统方法具有很高的识别精度及识别效率。
An identity recognition method using 3D behavior data matching is proposed. Image denoising is carried out by means of the mean filter method. By using the first order difference of the human behavior image,the average square gradient matrix of each pixel is obtained. According to the characteristic value,the angular point response is obtained,and the Harris angular point is determined. Harris angular point is used to extract human behavior features. And two image planes constituted by two identical cameras are placed in the same plane,to imitate principle of the human eye to obtain the object position information,and obtain the 3D coordinates of the human behavior data and the 3D coordinates of all feature points. By computing the correlation coefficient and the threshold value of the corresponding point in the search window,the feature points matching is realized,and the identity recognition is completed. Simulation results show that,compared with the traditional method,the proposed method has a high recognition accuracy and recognition efficiency.
An identity recognition method using 3D behavior data matching is proposed. Image denoising is carried out by means of the mean filter method. By using the first order difference of the human behavior image,the average square gradient matrix of each pixel is obtained. According to the characteristic value,the angular point response is obtained,and the Harris angular point is determined. Harris angular point is used to extract human behavior features. And two image planes constituted by two identical cameras are placed in the same plane,to imitate principle of the human eye to obtain the object position information,and obtain the 3D coordinates of the human behavior data and the 3D coordinates of all feature points. By computing the correlation coefficient and the threshold value of the corresponding point in the search window,the feature points matching is realized,and the identity recognition is completed. Simulation results show that,compared with the traditional method,the proposed method has a high recognition accuracy and recognition efficiency.
引文
[1]亢瑞红,胡洪,甘梦仙.基于ICP算法的三维激光扫描点云数据配准方法[J].池州学院学报,2014:68-70.
[2]叶建华,高诚辉,江吉彬.基于遗传算法的三维模型匹配方法[J].图学学报,2015,36:22-27.
[3]刘建兰,朱丽.基于计算机三维视觉的物流产品防伪算法研究[J].物流技术,2014,33:354-356.
[4]李春磊,常智勇,莫蓉.基于改进LMed S算法和贪心估计的相位立体匹配[J].计算机辅助设计与图形学学报,2014:2046-2055.
[5]王蒙,戴亚平,王庆林.单目视觉下目标三维行为的时间尺度不变建模及识别[J].自动化学报,2014,40(8):1644-1653.
[6]赵治栋,杨雷,陈甸甸.基于FFT-Matching Pursuit的心电身份识别算法研究[J].传感技术学报,2013,26:307-314.
[7]汪西原,闫辉.一种新的基于不变矩的步态特征身份识别算法[J].电视技术,2014,38:169-172.
[8]卢阳,等.基于动态心电信号的实时身份识别算法[J].计算机应用,2015,35(1):262-264.
[9]林源,梁舒,王生进.基于非刚性ICP的三维人脸数据配准算法[J].清华大学学报(自然科学版),2014,54(3):334-340.
[10]李学相,安学庆.基于三维图像动作识别算法研究[J].计算机仿真,2013,30:374-377.
[2]叶建华,高诚辉,江吉彬.基于遗传算法的三维模型匹配方法[J].图学学报,2015,36:22-27.
[3]刘建兰,朱丽.基于计算机三维视觉的物流产品防伪算法研究[J].物流技术,2014,33:354-356.
[4]李春磊,常智勇,莫蓉.基于改进LMed S算法和贪心估计的相位立体匹配[J].计算机辅助设计与图形学学报,2014:2046-2055.
[5]王蒙,戴亚平,王庆林.单目视觉下目标三维行为的时间尺度不变建模及识别[J].自动化学报,2014,40(8):1644-1653.
[6]赵治栋,杨雷,陈甸甸.基于FFT-Matching Pursuit的心电身份识别算法研究[J].传感技术学报,2013,26:307-314.
[7]汪西原,闫辉.一种新的基于不变矩的步态特征身份识别算法[J].电视技术,2014,38:169-172.
[8]卢阳,等.基于动态心电信号的实时身份识别算法[J].计算机应用,2015,35(1):262-264.
[9]林源,梁舒,王生进.基于非刚性ICP的三维人脸数据配准算法[J].清华大学学报(自然科学版),2014,54(3):334-340.
[10]李学相,安学庆.基于三维图像动作识别算法研究[J].计算机仿真,2013,30:374-377.