Access the full text.
Sign up today, get DeepDyve free for 14 days.
References for this paper are not available at this time. We will be adding them shortly, thank you for your patience.
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. Reference to this paper should be made as follows: Vezzetti, E., Marcolin, F., Tornincasa, S. and Maroso, P. (2016) `Application of geometry to RGB images for facial landmark localisation a preliminary approach', Int. J. Biometrics, Vol. 8,
International Journal of Biometrics – Inderscience Publishers
Published: Jan 1, 2016
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.