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Facial features detection by saccadic exploration of the Gabor decomposition and Support Vector Machines

  1. Smeraldi, N. Capdevielle and J. Bigun, Proceedings of the 11th Scandinavian Conference on Image Analysis, Kangerlussuaq (Greenland), volume I, pages 39-44, June 1999

Abstract


Facial features detection is of primary importance to face authentication and recognition. In this paper, we present an attention-driven approach to eyes and mouth detection inspired by the human saccadic system. The algorithm is centred around a log-polar retinotopic grid that is used to sample the Gabor decomposition of the image. Detection is achieved by displacing the grid according to a saccadic pattern. Saccade planning is performed using eye and mouth models implemented by means of Support Vector Machine classifiers

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