Детайли за публикацията
(Publication details)

Autors: Martin Penev., Boumbarov, O. L.
Title: Facial Landmarks Detection using Linear Regression and SIFT
Keywords: Facial Landmark Extraction, Facial Features, SIFT, Linear Regression

Abstract: Accurate detection of facial components is an important operation which reflects numerous applications based on face analysis. Hence, there is a great demand on real-time algorithms for detection of face components. In this paper we propose a fast method with relatively low computational complexity, which achieves excellent results, comparable to those of the state-of-the-art methods.


  1. T. F. Cootes, G. J. Edwards, and C. J. Taylor, 1998, Active appearance models, , , <>,
  2. D. Cristinacce and T. Cootes, 2008, Automatic feature localisation with constrained local models, Pattern Recognition, Volume 41, pp. pp.3054–3067
  3. X. Cao, Y. Wei, F. Wen, and J. Sun, 2014, Face alignment by explicit shape regression, International Journal of Computer Vision, Volume 107, pp. pp. 177–190
  4. X. P. Burgos-Artizzu, P. Perona, and P. Dollar, 2013, Robust face landmark estimation under occlusion, , 2013, <>, IEEE

Computer and communications engineering, vol. 9, pp. 4, 2014, Bulgaria, ISSN 1314-2291

Copyright Computer and communications engineering

Вид: статия в списание, публикация в реферирано издание

Въведена от: доц. д-р Агата Христова Манолова