Gradient based Volume Visual Attention Maps in Ray Casting Rendering

Autores: Andoni Beristain, Luis Kabongo, Sabarinath Rajasekharan

Fecha: 20.02.2013


PDF

Abstract

This paper presents a method to naturally enhance spatial regions in ray casting volume rendering using a spatial importance measure inferred from the user’s visual attention focus. This work presents three improvements over a former work of the author on Volume Visual Attention Maps in Ray-Casting rendering. These contributions are: a more accurate and realistic volume visual attention map definition, a watershed pre-segmentation guided visualization enhancement and the use of a generic two-dimensional transfer functions combined with the importance measure as opposed to the one-dimensional functions used in the previous work.

BIB_text

@Article {
author = {Andoni Beristain, Luis Kabongo, Sabarinath Rajasekharan},
title = {Gradient based Volume Visual Attention Maps in Ray Casting Rendering},
keywds = {

volume rendering, eye-gaze, eye-tracking, interaction, ray-casting


}
abstract = {

This paper presents a method to naturally enhance spatial regions in ray casting volume rendering using a spatial importance measure inferred from the user’s visual attention focus. This work presents three improvements over a former work of the author on Volume Visual Attention Maps in Ray-Casting rendering. These contributions are: a more accurate and realistic volume visual attention map definition, a watershed pre-segmentation guided visualization enhancement and the use of a generic two-dimensional transfer functions combined with the importance measure as opposed to the one-dimensional functions used in the previous work.


}
date = {2013-02-20},
year = {2013},
}
Vicomtech

Parque Científico y Tecnológico de Gipuzkoa,
Paseo Mikeletegi 57,
20009 Donostia / San Sebastián (España)

+(34) 943 309 230

Zorrotzaurreko Erribera 2, Deusto,
48014 Bilbao (España)

close overlay

Las cookies de publicidad comportamental son necesarias para cargar el contenido

Aceptar cookies de publicidad comportamental