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oai:recercat.cat:2117/182782026-02-07T11:19:47Zcom_2072_1033col_2072_452950

INTAIRACT: Joint hand gesture and fingertip classification for touchless interaction Suau Cuadros, Xavier Alcoverro Vidal, Marcel López Méndez, Adolfo Ruiz Hidalgo, Javier Casas Pla, Josep Ramon Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions Universitat Politècnica de Catalunya. GPI - Grup de Processament d'Imatge i Vídeo Àrees temàtiques de la UPC::Informàtica::Sistemes d'informació::Interacció home-màquina Àrees temàtiques de la UPC::Enginyeria de la telecomunicació Human-computer interaction Interacció persona-ordinador In this demo we present intAIRact, an online hand-based touchless interaction system. Interactions are based on easy-to-learn hand gestures, that combined with translations and rotations render a user friendly and highly configurable system. The main advantage with respect to existing approaches is that we are able to robustly locate and identify fingertips. Hence, we are able to employ a simple but powerful alphabet of gestures not only by determining the number of visible fingers in a gesture, but also which fingers are being observed. To achieve such a system we propose a novel method that jointly infers hand gestures and fingertip locations using a single depth image from a consumer depth camera. Our approach is based on a novel descriptor for depth data, the Oriented Radial Distribution (ORD) [1]. On the one hand, we exploit the ORD for robust classification of hand gestures by means of efficient k-NN retrieval. On the other hand, maxima of the ORD are used to perform structured inference of fingertip locations. The proposed method outperforms other state-of-the-art approaches both in gesture recognition and fingertip localization. An implementation of the ORD extraction on a GPU yields a real-time demo running at approximately 17fps on a single laptop Peer Reviewed Postprint (published version) 2012 Conference lecture Suau, X. [et al.]. INTAIRACT: Joint hand gesture and fingertip classification for touchless interaction. A: European Conference on Computer Vision. "Computer Vision – ECCV 2012. Workshops and Demonstrations". Florència: Springer, 2012, p. 602-606. 978-3-642-33884-7 https://hdl.handle.net/2117/18278 10.1007/978-3-642-33885-4_62 eng http://link.springer.com/chapter/10.1007/978-3-642-33885-4_62 http://creativecommons.org/licenses/by-nc-nd/3.0/es/ Restricted access - publisher's policy Attribution-NonCommercial-NoDerivs 3.0 Spain 5 p. application/pdf Springer