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Face identification using a 3D gray-scale image-a method for lessening restrictions on facial directions

机译:使用3D灰度图像的面部识别 - 一种减少面部方向限制的方法

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We propose a method to identify the human face using a 3D gray scale image which combines a 3D image with a gray scale image. The proposed method can identify facial images which face in various directions. First, 3D positions, where the eyes and the tip of the nose are located, are estimated in the acquired 3D gray scale image. Next, the calibration of facial directions and brightness is performed. Due to facial images facing more to the right or the left, some parts of the calibrated data are lost by occlusion. Thus, we assume that a human face is almost symmetrical, and the side of the facial image without any loss of data is regarded as the region for identification. Feature vectors which reflect individuality are extracted from this region. The identification procedure is conducted using the subspace method. In order to demonstrate the efficiency of this method, the experiment used 3D gray scale images of 24 people.
机译:我们提出了一种使用3D灰度图像来识别人脸的方法,该3D灰度图像将3D图像与灰度图像相结合。该方法可以识别在各种方向上面对的面部图像。首先,在所获取的3D灰度图像中估计了3D位置,其中眼睛的眼睛和鼻梁的尖端估计。接下来,执行面部方向和亮度的校准。由于面向右侧或左侧的面部图像,校准数据的某些部分被遮挡丢失。因此,我们假设人称几乎对称,并且面部图像的侧面没有任何数据丢失的侧面被认为是用于识别的区域。从该区域提取反映个性的特征向量。使用子空间方法进行识别过程。为了证明这种方法的效率,实验使用了34人的3D灰度图像。

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