A combined probabilistic framework for learning gestures and actions

Please use this identifier to cite or link to this item: http://hdl.handle.net/10045/23397
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Title: A combined probabilistic framework for learning gestures and actions
Authors: Escolano, Francisco | Cazorla, Miguel | Gallardo López, Domingo | Llorens Largo, Faraón | Satorre Cuerda, Rosana | Rizo, Ramón
Research Group/s: Robótica y Visión Tridimensional (RoViT) | Laboratorio de Investigación en Visión Móvil (MVRLab) | Informática Industrial e Inteligencia Artificial
Center, Department or Service: Universidad de Alicante. Departamento de Ciencia de la Computación e Inteligencia Artificial
Keywords: Visual inspection | Gesture recognition | Learning | Probabilistic constraints | Eigenmethods
Knowledge Area: Ciencia de la Computación e Inteligencia Artificial
Issue Date: 1998
Publisher: Springer Berlin / Heidelberg
Citation: ESCOLANO, Francisco, et al. "A combined probabilistic framework for learning gestures and actions". En: Tasks and Methods in Applied Artificial Intelligence : 11th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems IEA-98-AIE Benicàssim, Castellón, Spain, June 1–4, 1998 Proceedings, Volume II / Angel Pasqual del Pobil, José Mira, Moonis Ali (Eds.). Berlin : Springer, 1998. (Lecture Notes in Computer Science; 1416). ISBN 3-540-64574-8, pp. 658-667
Abstract: In this paper we introduce a probabilistic approach to support visual supervision and gesture recognition. Task knowledge is both of geometric and visual nature and it is encoded in parametric eigenspaces. Learning processes for compute modal subspaces (eigenspaces) are the core of tracking and recognition of gestures and tasks. We describe the overall architecture of the system and detail learning processes and gesture design. Finally we show experimental results of tracking and recognition in block-world like assembling tasks and in general human gestures.
URI: http://hdl.handle.net/10045/23397
ISBN: 3-540-64574-8
ISSN: 0302-9743 (Print) | 1611-3349 (Online)
DOI: 10.1007/3-540-64574-8_452
Language: eng
Type: info:eu-repo/semantics/conferenceObject
Rights: The original publication is available at www.springerlink.com
Peer Review: si
Publisher version: http://dx.doi.org/10.1007/3-540-64574-8_452
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