Low-Resolution Range Data Surface Matching for 3D Face Verification

Abstract:

In this paper, we presented a novel approach for automatic 3D face verification by range data surface matching. The method consists of range data registration and comparison. There are three steps in registration procedure: the coarse step conducting the normalization by exploiting a priori knowledge of the human face and facial features to make faces have the similar attitude; the next step considering the existence of holes in the low-resolution range data will undermining the recognition results, we presented a novel approach for holes filling to improve the range data quality; and the fine step aligning the input data with the model in the database by the Delaunay-Iterative Closest Point (D-ICP) algorithm. During the face comparison, a Modified Hausdorff Distance (MHD) is employed as the similarity metrics. The experiments are carried out on a database with 30 individuals, and the best EER of 1.667% is achieved.

• Periodical: Advanced Materials Research (Volumes 468-471)
• Pages: 1957-1961
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.468-471.1957
• Online since: February 2012
• Authors: Juan Zhou, Yong Ping Li
• Keywords: Holes Filling, Low-Resolution, Similar Attitude, Surface Matching

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