2015/03/26 by Laura Florea, Florea, Laura, Corneliu Florea +3
Computer Science · Medicine · #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Face and Expression Recognition #Gaze Tracking and Assistive Technology #Glaucoma and retinal disorders #Ocular Diseases and Behçet’s Syndrome #cs.CV
paper · pdf · doi:10.48550/arxiv.1503.07697
arxiv created 2015/03/26 · openalex publication_date 2015/03/26 · arxiv updated 2015/03/27 · openalex created_date 2022/10/01 · openalex updated_date 2026/07/28
This paper proposes a new framework for the eye centers localization by the joint use of encoding of normalized image projections and a Multi Layer Perceptron (MLP) classifier. The encoding is novel and it consists in identifying the zero-crossings and extracting the relevant parameters from the resulting modes. The compressed normalized projections produce feature descriptors that are inputs to a properly-trained MLP, for discriminating among various categories of image regions. The proposed framework forms a fast and reliable system for the eye centers localization, especially in the context of face expression analysis in unconstrained environments. We successfully test the proposed method on a wide variety of databases including BioID, Cohn-Kanade, Extended Yale B and Labelled Faces in the Wild (LFW) databases.