Selective image rendering based on an improved perceptual saliency model

Computer graphics is becoming more and more important in film and game industries. However, photorealistic image rendering is still very time consuming. To reduce the rendering cost has always been a difficult task for researchers. Visual attention guided rendering is one of the most important areas...

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Bibliographic Details
Main Author: Xu, Yadong.
Other Authors: Lin Weisi
Format: Final Year Project (FYP)
Language:English
Published: 2011
Subjects:
Online Access:http://hdl.handle.net/10356/43959
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author Xu, Yadong.
author2 Lin Weisi
author_facet Lin Weisi
Xu, Yadong.
author_sort Xu, Yadong.
collection NTU
description Computer graphics is becoming more and more important in film and game industries. However, photorealistic image rendering is still very time consuming. To reduce the rendering cost has always been a difficult task for researchers. Visual attention guided rendering is one of the most important areas of selective rendering. This project is to develop a perceptual saliency model and implement it as a selective rendering scheme which generates better quality images compared to an existing visual attention based rendering with the same amount of rendering cost. Our implementation is based on Physically Based Rendering Tool (PBRT). A blended saliency map which contains visual attention information and local sample contrast information is proposed and it guides the sampling process of the selective rending scheme. Integrating local sample contrast information into visual attention rendering in our experiment has demonstrated a better result than pure visual attention based rendering.
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spelling ntu-10356/439592023-03-03T20:40:01Z Selective image rendering based on an improved perceptual saliency model Xu, Yadong. Lin Weisi School of Computer Engineering Centre for Multimedia and Network Technology DRNTU::Engineering::Computer science and engineering::Computing methodologies::Computer graphics Computer graphics is becoming more and more important in film and game industries. However, photorealistic image rendering is still very time consuming. To reduce the rendering cost has always been a difficult task for researchers. Visual attention guided rendering is one of the most important areas of selective rendering. This project is to develop a perceptual saliency model and implement it as a selective rendering scheme which generates better quality images compared to an existing visual attention based rendering with the same amount of rendering cost. Our implementation is based on Physically Based Rendering Tool (PBRT). A blended saliency map which contains visual attention information and local sample contrast information is proposed and it guides the sampling process of the selective rending scheme. Integrating local sample contrast information into visual attention rendering in our experiment has demonstrated a better result than pure visual attention based rendering. Bachelor of Engineering (Computer Engineering) 2011-05-16T04:52:19Z 2011-05-16T04:52:19Z 2011 2011 Final Year Project (FYP) http://hdl.handle.net/10356/43959 en Nanyang Technological University 53 p. application/pdf
spellingShingle DRNTU::Engineering::Computer science and engineering::Computing methodologies::Computer graphics
Xu, Yadong.
Selective image rendering based on an improved perceptual saliency model
title Selective image rendering based on an improved perceptual saliency model
title_full Selective image rendering based on an improved perceptual saliency model
title_fullStr Selective image rendering based on an improved perceptual saliency model
title_full_unstemmed Selective image rendering based on an improved perceptual saliency model
title_short Selective image rendering based on an improved perceptual saliency model
title_sort selective image rendering based on an improved perceptual saliency model
topic DRNTU::Engineering::Computer science and engineering::Computing methodologies::Computer graphics
url http://hdl.handle.net/10356/43959
work_keys_str_mv AT xuyadong selectiveimagerenderingbasedonanimprovedperceptualsaliencymodel