Title: Application of geometry to RGB images for facial landmark localisation - a preliminary approach

Authors: Enrico Vezzetti; Federica Marcolin; Stefano Tornincasa; Pietro Maroso

Addresses: Department of Management and Production Engineering, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Turin, Italy ' Department of Management and Production Engineering, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Turin, Italy ' Department of Management and Production Engineering, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Turin, Italy ' Department of Management and Production Engineering, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Turin, Italy

Abstract: This study proposes a novel approach to automatically localise 11 landmarks from facial RGB images. The novelty of this method relies on the application, i.e., point-by-point mapping, of 11 differential geometry descriptors such as curvatures to the three individual RGB image components. Thus, three-dimensional features are applied to bidimensional facial image representations and used, via thresholding techniques, to extract the landmark positions. The method was tested on the Bosphorus database and showed global average errors lower than five millimetres. The idea behind this approach is to embed this methodology in state-of-the-art 3D landmark detection methods to accomplish a full automatic landmarking by exploiting the advantages of both 2D and 3D data. Some landmarks such as pupils are arduous to be automatically extracted only via three-dimensional techniques. Thus, this method is intended as a bridging-the-gap preliminary technique that takes advantages of 2D imaging only for integrating advanced landmark localisation methodologies.

Keywords: facial landmarks; landmark localisation; face analysis; RGB images; differential geometry; biometrics; facial images; thresholding; 3D features; automatic landmarking.

DOI: 10.1504/IJBM.2016.082597

International Journal of Biometrics, 2016 Vol.8 No.3/4, pp.216 - 236

Available online: 27 Feb 2017 *

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