Documents disponibles écrits par cet auteur

Statistical modeling and many-to-many matching for view-based 3D object retrieval / Fei Li in Signal processing. Image communication, Vol. 25 N° 1 (Janvier 2010) 

Public ISBD [article]  in Signal processing. Image communication > Vol. 25 N° 1 (Janvier 2010) . - pp. 18-27 Titre : Statistical modeling and many-to-many matching for view-based 3D object retrieval Type de document : texte imprimé Auteurs : Fei Li, Auteur ; Qionghai Dai, Auteur ; Wenli Xu, Auteur Article en page(s) : pp. 18-27 Note générale : Electronique Langues : Anglais (eng) Mots-clés : View-based  3D  object  retrieval  Statistical  modeling  Markov  chain  Many-to-many  matching  Earth  mover's  distance Index. décimale : 621.382 Dispositifs électroniques utilisant les effets des corps solides. Dispositifs semi-conducteurs Résumé : We address the task of view-based 3D object retrieval, in which each object is represented by a set of views taken from different positions, rather than a geometrical model based on polygonal meshes. As the number of views and the view point setting cannot always be the same for different objects, the retrieval task is more challenging and the existing methods for 3D model retrieval are infeasible. In this paper, the information in the sets of views is exploited from two aspects. On the one hand, the form of histogram is converted from vector to state sequence, and Markov chain (MC) is utilized for modeling the statistical characteristics of all the views representing the same object. On the other hand, the earth mover's distance (EMD) is involved to achieve many-to-many matching between two sets of views. For 3D object retrieval, by combining the above two aspects together, a new distance measure is defined, and a novel approach to automatically determine the edge weights in graph-based semi-supervised learning is proposed. Experimental results on different databases demonstrate the effectiveness of our proposal. DEWEY : 361.382 ISSN : 0923-5965 En ligne : http://www.sciencedirect.com/science?_ob=PublicationURL&_tockey=%23TOC%235640%23 [...] [article] Statistical modeling and many-to-many matching for view-based 3D object retrieval [texte imprimé] / Fei Li, Auteur ; Qionghai Dai, Auteur ; Wenli Xu, Auteur . - pp. 18-27. Electronique Langues : Anglais (eng) in Signal processing. Image communication > Vol. 25 N° 1 (Janvier 2010) . - pp. 18-27 Mots-clés : View-based  3D  object  retrieval  Statistical  modeling  Markov  chain  Many-to-many  matching  Earth  mover's  distance Index. décimale : 621.382 Dispositifs électroniques utilisant les effets des corps solides. Dispositifs semi-conducteurs Résumé : We address the task of view-based 3D object retrieval, in which each object is represented by a set of views taken from different positions, rather than a geometrical model based on polygonal meshes. As the number of views and the view point setting cannot always be the same for different objects, the retrieval task is more challenging and the existing methods for 3D model retrieval are infeasible. In this paper, the information in the sets of views is exploited from two aspects. On the one hand, the form of histogram is converted from vector to state sequence, and Markov chain (MC) is utilized for modeling the statistical characteristics of all the views representing the same object. On the other hand, the earth mover's distance (EMD) is involved to achieve many-to-many matching between two sets of views. For 3D object retrieval, by combining the above two aspects together, a new distance measure is defined, and a novel approach to automatically determine the edge weights in graph-based semi-supervised learning is proposed. Experimental results on different databases demonstrate the effectiveness of our proposal. DEWEY : 361.382 ISSN : 0923-5965 En ligne : http://www.sciencedirect.com/science?_ob=PublicationURL&_tockey=%23TOC%235640%23 [...]

Statistical modeling and many-to-many matching for view-based 3D object retrieval / Fei Li in Signal processing. Image communication, Vol. 25 N° 1 (Janvier 2010) 

Public ISBD [article]  in Signal processing. Image communication > Vol. 25 N° 1 (Janvier 2010) . - pp. 18–27 Titre : Statistical modeling and many-to-many matching for view-based 3D object retrieval Type de document : texte imprimé Auteurs : Fei Li, Auteur ; Qionghai Dai, Auteur ; Wenli Xu, Auteur Année de publication : 2012 Article en page(s) : pp. 18–27 Note générale : Electronique Langues : Anglais (eng) Mots-clés : View-based  3D  object  retrieval  Statistical  modeling  Markov  chain  Many-to-many  matching  Earth  mover's  distance Résumé : We address the task of view-based 3D object retrieval, in which each object is represented by a set of views taken from different positions, rather than a geometrical model based on polygonal meshes. As the number of views and the view point setting cannot always be the same for different objects, the retrieval task is more challenging and the existing methods for 3D model retrieval are infeasible. In this paper, the information in the sets of views is exploited from two aspects. On the one hand, the form of histogram is converted from vector to state sequence, and Markov chain (MC) is utilized for modeling the statistical characteristics of all the views representing the same object. On the other hand, the earth mover's distance (EMD) is involved to achieve many-to-many matching between two sets of views. For 3D object retrieval, by combining the above two aspects together, a new distance measure is defined, and a novel approach to automatically determine the edge weights in graph-based semi-supervised learning is proposed. Experimental results on different databases demonstrate the effectiveness of our proposal. ISSN : 0923-5965 En ligne : http://www.sciencedirect.com/science/article/pii/S0923596509001313 [article] Statistical modeling and many-to-many matching for view-based 3D object retrieval [texte imprimé] / Fei Li, Auteur ; Qionghai Dai, Auteur ; Wenli Xu, Auteur . - 2012 . - pp. 18–27. Electronique Langues : Anglais (eng) in Signal processing. Image communication > Vol. 25 N° 1 (Janvier 2010) . - pp. 18–27 Mots-clés : View-based  3D  object  retrieval  Statistical  modeling  Markov  chain  Many-to-many  matching  Earth  mover's  distance Résumé : We address the task of view-based 3D object retrieval, in which each object is represented by a set of views taken from different positions, rather than a geometrical model based on polygonal meshes. As the number of views and the view point setting cannot always be the same for different objects, the retrieval task is more challenging and the existing methods for 3D model retrieval are infeasible. In this paper, the information in the sets of views is exploited from two aspects. On the one hand, the form of histogram is converted from vector to state sequence, and Markov chain (MC) is utilized for modeling the statistical characteristics of all the views representing the same object. On the other hand, the earth mover's distance (EMD) is involved to achieve many-to-many matching between two sets of views. For 3D object retrieval, by combining the above two aspects together, a new distance measure is defined, and a novel approach to automatically determine the edge weights in graph-based semi-supervised learning is proposed. Experimental results on different databases demonstrate the effectiveness of our proposal. ISSN : 0923-5965 En ligne : http://www.sciencedirect.com/science/article/pii/S0923596509001313