An Open Platform for 3D Face Recognition Algorithms
Hassen Drira, Boulbaba Ben Amor, Mohamed Daoudi, Anuj Srivastava, Joseph Colineau · 2010
In this paper we describe a new open platform designed to integrate 3D face matching algorithms for recognition.Its main purpose is to provide experimental environment to online operational testing of 3D face recognition approaches, in laboratory conditions.The proposed platform consists of: (i) An acquisition module that interfaces with Minolta 3D laser-based scanner, (ii) A preprocessing sub-system allowing detection and segmentation of the useful part of the face from the depth image (scanner's output) and its processing (iii) A face matching module that incorporates matching algorithms, and (iv) A decision component that provides the final matching result.Moreover, we show an integration example of our algorithm [1] and discuss experimental results.Our 3D facial matching algorithm currently integrated to the proposed platform represents facial surfaces by indexed collections of radial curves on them, emanating from the nose tips, and compares the facial shapes by comparing the shapes of their corresponding curves.Using a framework on elastic shape analysis of curves, we obtain an algorithm for comparing facial surfaces.We also introduce a quality control module which allows our approach to be robust to pose variations and missing data.Comparative evaluation using a common experimental setup on GavabDB 1 dataset, considered as the most expression-rich and noise-prone 3D face dataset, shows that our approach outperforms other state-of-the-art approaches.