Towards robust 3D face recognition from noisy range images with low resolution

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Author(s) : Olga Ebers , Tatjana Ebers , Thea Spiridonidou , Matthias Plaue , Philipp Beckmann , Günter Bärwolff , Hartmut Schwandt

Preprint series of the Institute of Mathematics, Technische Universität Berlin
Preprint 33-2008

MSC 2000

68T45 Machine vision and scene understanding
68U10 Image processing

Abstract :
For a number of different security and industrial applications, there is the need for reliable person identification methods. Among these methods, face recognition has a number of advantages such as being non-invasive and potentially covert. Since the device for data acquisition is a conventional camera, other advantages of a 2D face recognition system are its low data capture duration and its low cost. However, the recent introduction of fast and comparatively inexpensive time-of-flight (TOF) cameras for the recording of 2.5D range data calls for a closer look at 3D face recognition in this context. One major disadvantage, however, is the low quality of the data aquired with such cameras. In this paper, we introduce a robust 3D face recognition system based on such noisy range images with low resolution.

Keywords : 3D face recognition, time-of-flight camera, range data denoising, pattern recognition, pattern matching