Face recognition based on 3D ridge images obtained from range data

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摘要

In this paper, we present an approach for 3D face recognition from frontal range data based on the ridge lines on the surface of the face. We use the principal curvature, kmax, to represent the face image as a 3D binary image called ridge image. The ridge image shows the locations of the ridge points around the important facial regions on the face (i.e., the eyes, the nose, and the mouth). We utilized the robust Hausdorff distance and the iterative closest points (ICP) for matching the ridge image of a given probe image to the ridge images of the facial images in the gallery. To evaluate the performance of our approach for 3D face recognition, we performed experiments on GavabDB face database (a small size database) and Face Recognition Grand Challenge V2.0 (a large size database). The results of the experiments show that the ridge lines have great capability for 3D face recognition. In addition, we found that as long as the size of the database is small, the performance of the ICP-based matching and the robust Hausdorff matching are comparable. But, when the size of the database increases, ICP-based matching outperforms the robust Hausdorff matching technique.

论文关键词:3D face recognition,Gaussian curvature,Iterative closest points,Hausdorff distance,Range image,Ridge image

论文评审过程:Received 24 April 2007, Revised 15 May 2008, Accepted 3 August 2008, Available online 17 August 2008.

论文官网地址:https://doi.org/10.1016/j.patcog.2008.08.012