Treffer: Intuitive volume exploration through spherical self-organizing map and color harmonization : Advances in Self-Organizing Maps

Title:
Intuitive volume exploration through spherical self-organizing map and color harmonization : Advances in Self-Organizing Maps
Source:
Neurocomputing (Amsterdam). 147:160-173
Publisher Information:
Amsterdam: Elsevier, 2015.
Publication Year:
2015
Physical Description:
print, 47 ref
Original Material:
INIST-CNRS
Subject Terms:
Cognition, Computer science, Informatique, Sciences exactes et technologie, Exact sciences and technology, Sciences appliquees, Applied sciences, Informatique; automatique theorique; systemes, Computer science; control theory; systems, Intelligence artificielle, Artificial intelligence, Reconnaissance des formes. Traitement numérique des images. Géométrie algorithmique, Pattern recognition. Digital image processing. Computational geometry, Connexionnisme. Réseaux neuronaux, Connectionism. Neural networks, Algorithme Kohonen, Kohonen algorithm, Algoritmo Kohonen, Amas, Cluster, Montón, Autoorganisation, Self organization, Autoorganización, Carte graphique, Graphic processing unit, Unidad de proceso gráfico, Etude expérimentale, Experimental study, Estudio experimental, Fonction transfert, Transfer function, Función traspaso, Harmonique, Harmonic, Armónica, Harmonisation, Harmonization, Armonización, Image couleur, Color image, Imagen color, Image tridimensionnelle, Tridimensional image, Imagen tridimensional, Manipulation, Manipulación, Opacité, Opacity, Opacidad, Rendu image, Image rendering, Restitucíon imagen, Réseau neuronal, Neural network, Red neuronal, Résultat expérimental, Experimental result, Resultado experimental, Temps réel, Real time, Tiempo real, Topologie, Topology, Topología, Treillis, Lattice, Enrejado, Visualisation, Visualization, Visualización, Voxel, Conception centrée utilisateur, User centred design, Diseño centrado en el usuario, Color harmonization, Direct volume rendering, Self-organizing map
Document Type:
Fachzeitschrift Article
File Description:
text
Language:
English
Author Affiliations:
Ryerson University, 350 Victoria Street, Toronto, ON, M5B 2K3, Canada
ISSN:
0925-2312
Rights:
Copyright 2015 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems
Accession Number:
edscal.28836740
Database:
PASCAL Archive

Weitere Informationen

Finding an appropriate transfer function (TF) for mapping color and opacity values in direct volume rendering (DVR) can be a daunting task. This paper presents a novel approach towards TF generation for DVR, where the traditional low-level color and opacity parameter manipulations are not necessary. The TF generation process is hidden behind a simple and intuitive spherical self-organizing map (SSOM) visualization. The SSOM represents a visual form of the topological relations among the clusters. The user interacts with the SSOM lattice to find interesting regions in the volume. The color and opacity values are generated automatically from the voxel features based on the user's perception. We also use harmonic colors to present a visually pleasing result. Due to the independence of SSOM from feature type, our proposed method is flexible in nature and can be integrated with any set of features. The GPU implementation provides real-time volume rendering and fast interaction. Experimental results on several benchmark volume datasets show the effectiveness of our proposed method.