caa a22 4500 467915016 CHVBK 20180406152859.0 cr unu---uuuuu 170328e20060701xx s 000 0 eng 10.1007/s11263-005-4436-9 doi (NATIONALLICENCE)springer-10.1007/s11263-005-4436-9 Efficient Discriminant Viewpoint Selection for Active Bayesian Recognition [Elektronische Daten] [Catherine Laporte, Tal Arbel] This paper presents a novel viewpoint selection criterion for active object recognition and pose estimation whose key advantage resides in its low computational cost with respect to current popular approaches in the literature. The proposed observation selection criterion associates high utility with observations that predictably facilitate distinction between pairs of competing hypotheses by a Bayesian classifier. Rigorous experimentation of the proposed approach was conducted on two case studies, involving synthetic and real data, respectively. The results show the proposed algorithm to perform better than a random navigation strategy in terms of the amount of data required for recognition while being much faster than a strategy based on mutual information, without compromising accuracy. Springer Science + Business Media, LLC, 2006 active vision nationallicence object recognition nationallicence pose estimation nationallicence Bayesian inference nationallicence efficient viewpoint selection nationallicence Laporte Catherine Centre for Intelligent Machines, McGill University, Montreal, Quebec, Canada aut Arbel Tal Centre for Intelligent Machines, McGill University, Montreal, Quebec, Canada aut International Journal of Computer Vision Kluwer Academic Publishers 68/3(2006-07-01), 267-287 0920-5691 68:3<267 2006 68 11263 https://doi.org/10.1007/s11263-005-4436-9 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s11263-005-4436-9 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Laporte Catherine Centre for Intelligent Machines, McGill University, Montreal, Quebec, Canada aut NATIONALLICENCE 700 1- Arbel Tal Centre for Intelligent Machines, McGill University, Montreal, Quebec, Canada aut NATIONALLICENCE 773 0- International Journal of Computer Vision Kluwer Academic Publishers 68/3(2006-07-01), 267-287 0920-5691 68:3<267 2006 68 11263 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer