计算机应用与软件Issue(3)：177-181,5.DOI:10.3969/j.issn.1000-386x.2015.03.041
基于 KINECT 传感器采集三维点云的高效鲁棒人脸识别
EFFICIENT AND ROBUST FACE RECOGNITION BASED ON COLLECTING 3D POINT CLOUD BY KINECT SENSOR
摘要
Abstract
For the problem that traditional 3D face recognition algorithms cost high but still can not deal with robust face recognition,we propose an efficient and robust face recognition algorithm which is based on collecting 3D point cloud by low resolution KINECT sensor.First, for the problem that the data collected by KINECT sensor has big noises,we present the standardised pretreatment process,it is to get the standardised texture images by nose tip detecting,face image cropping,posture correcting,symmetry filling and smooth sampling.Then,we run discriminant colour space transform on texture images so as to maximise the separability between the classes.At last,we use multi-modal sparse coding to effectually reconstruct the errors for getting the similarity between the querying image and the training set,and use Z-scoring technique to complete final face recognition.The efficiency and robustness of the proposed algorithm have been verified by experiments on common face database CurtinFaces.Experimental results show that the proposed algorithm achieves higher recognition accuracy and better robustness than several other relatively advanced robust face recognition algorithms.关键词
人脸识别/KINECT 传感器/三维点云/判别色彩空间/高鲁棒性Key words
Face recognition/KINECT sensor/3D Point cloud/Discriminant colour space/High robustness分类
信息技术与安全科学引用本文复制引用
杨善友,蓝新波,赵志俊..基于 KINECT 传感器采集三维点云的高效鲁棒人脸识别[J].计算机应用与软件,2015,(3):177-181,5.基金项目
国家自然科学基金项目 （）
