针对照明变化条件下人脸图像检测精度相对较低的问题,以照明变化下的人脸检测为研究对象,提出局部自我相关函数(local autocorrelation,LAC),研究基于Adaboost算法下采用局部自我相关函数为前处理的光照变化下人脸检测。提出了局部自我...针对照明变化条件下人脸图像检测精度相对较低的问题,以照明变化下的人脸检测为研究对象,提出局部自我相关函数(local autocorrelation,LAC),研究基于Adaboost算法下采用局部自我相关函数为前处理的光照变化下人脸检测。提出了局部自我相关函数定义模型,对局部自我相关函数的物理特性进行分析,从理论上验证局部自我相关函数对线性照明变化的鲁棒性。采用卡内基梅隆大学的人脸照明变化数据库(CMU PIE Database)作为检测数据验证基于局部自我相关函数的光线照明变化下的人脸检测,实验结果证明了局部自我相关函数消除照明变化对人脸检测精度影响的有效性。展开更多
A novel adaptive illumination normalization approach is proposed to eliminate the effects caused by illumination variations for face recognition. The proposed method divides an image into blocks and performs discrete ...A novel adaptive illumination normalization approach is proposed to eliminate the effects caused by illumination variations for face recognition. The proposed method divides an image into blocks and performs discrete cosine transform(DCT) in blocks independently in the logarithm domain. For each block-DCT coefficient except the direct current(DC) component, we take the illumination as main signal and take the reflectance as "noise". A data-driven and adaptive soft-thresholding denoising technique is employed in each block-DCT coefficient except the DC component. Illumination is estimated by applying the inverse DCT in the block-DCT coefficients, and the indirectly obtained reflectance can be used in further recognition task. Experimental results show that the proposed approach outperforms other existing methods. Moreover, the proposed method does not need any prior information, and none of the parameters can be determined by experience.展开更多
文摘针对照明变化条件下人脸图像检测精度相对较低的问题,以照明变化下的人脸检测为研究对象,提出局部自我相关函数(local autocorrelation,LAC),研究基于Adaboost算法下采用局部自我相关函数为前处理的光照变化下人脸检测。提出了局部自我相关函数定义模型,对局部自我相关函数的物理特性进行分析,从理论上验证局部自我相关函数对线性照明变化的鲁棒性。采用卡内基梅隆大学的人脸照明变化数据库(CMU PIE Database)作为检测数据验证基于局部自我相关函数的光线照明变化下的人脸检测,实验结果证明了局部自我相关函数消除照明变化对人脸检测精度影响的有效性。
基金the Natural Science Foundation of Jiangsu Province(No.BK20150784)the Fund of Jiangsu Key Laboratory of Image and Video Understanding for Social Safety(Nanjing University of Science and Technology)(No.30920140122007)
文摘A novel adaptive illumination normalization approach is proposed to eliminate the effects caused by illumination variations for face recognition. The proposed method divides an image into blocks and performs discrete cosine transform(DCT) in blocks independently in the logarithm domain. For each block-DCT coefficient except the direct current(DC) component, we take the illumination as main signal and take the reflectance as "noise". A data-driven and adaptive soft-thresholding denoising technique is employed in each block-DCT coefficient except the DC component. Illumination is estimated by applying the inverse DCT in the block-DCT coefficients, and the indirectly obtained reflectance can be used in further recognition task. Experimental results show that the proposed approach outperforms other existing methods. Moreover, the proposed method does not need any prior information, and none of the parameters can be determined by experience.
