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Article

Visual attention models for producing high fidelity graphics efficiently

Authors:

David MaflioliAuthors Info & Claims

SCCG '03: Proceedings of the 19th Spring Conference on Computer Graphics

Pages 39 - 45

https://doi.org/10.1145/984952.984960

Published: 24 April 2003 Publication History

Abstract

Despite the ready availability of modern high performance graphics cards, the complexity of the scenes being modelled and the realism required of the images means that rendering high fidelity computer images is still simply not possible in a reasonable, let alone real-time. Knowing that it is a human that will be looking at the resultant images can be exploited to significantly reduce the computation time required for high fidelity graphical images, for although the human visual system is good, it does have limitations. The key is knowing where the user will be looking in the image.This paper describes high level task maps and low level saliency maps. For a large number of applications, these visual attention models can indeed determine where the user will be looking in scene with high accuracy. This information is then used to selectively render different parts of a complex scene at different qualities. We show that viewers performing a known visual task within the environment consistently fail to notice the difference in rendering quality between benchmark high quality images and the selectively rendered images that were rendered at a fraction of the computational cost.

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Cited By

Hirsch LSchneegass CWelsch RButz A(2021)To See or Not to SeeProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/34481235:1(1-25)Online publication date: 30-Mar-2021
https://dl.acm.org/doi/10.1145/3448123
Pal R(2018)Computational Models of Visual AttentionComputer Vision10.4018/978-1-5225-5204-8.ch001(1-26)Online publication date: 2018
https://doi.org/10.4018/978-1-5225-5204-8.ch001
Pal R(2014)Computational Models of Visual AttentionResearch Developments in Computer Vision and Image Processing10.4018/978-1-4666-4558-5.ch004(54-76)Online publication date: 2014
https://doi.org/10.4018/978-1-4666-4558-5.ch004
Show More Cited By

Visual attention models for producing high fidelity graphics efficiently
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Image and video acquisition

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Published In

cover image ACM Conferences

SCCG '03: Proceedings of the 19th Spring Conference on Computer Graphics

April 2003

267 pages

ISBN:158113861X

DOI:10.1145/984952

Editor:
László Szirmay-Kalos,
Program Chair:
Kenneth I. Joy
UC Davis

Copyright © 2003 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGGRAPH: ACM Special Interest Group on Computer Graphics and Interactive Techniques

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New York, NY, United States

Publication History

Published: 24 April 2003

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SCCG03

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SIGGRAPH

SCCG03: Spring Conference in Computer Graphics 2003

April 24 - 26, 2003

Budmerice, Slovakia

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Overall Acceptance Rate 67 of 115 submissions, 58%

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Cited By

Hirsch LSchneegass CWelsch RButz A(2021)To See or Not to SeeProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/34481235:1(1-25)Online publication date: 30-Mar-2021
https://dl.acm.org/doi/10.1145/3448123
Pal R(2018)Computational Models of Visual AttentionComputer Vision10.4018/978-1-5225-5204-8.ch001(1-26)Online publication date: 2018
https://doi.org/10.4018/978-1-5225-5204-8.ch001
Pal R(2014)Computational Models of Visual AttentionResearch Developments in Computer Vision and Image Processing10.4018/978-1-4666-4558-5.ch004(54-76)Online publication date: 2014
https://doi.org/10.4018/978-1-4666-4558-5.ch004
Aziz MMertsching B(2008)Fast and Robust Generation of Feature Maps for Region-Based Visual AttentionIEEE Transactions on Image Processing10.1109/TIP.2008.91936517:5(633-644)Online publication date: May-2008
https://doi.org/10.1109/TIP.2008.919365
Ramanarayanan GFerwerda JWalter BBala K(2007)Visual equivalenceACM Transactions on Graphics10.1145/1276377.127647226:3(76-es)Online publication date: 29-Jul-2007
https://dl.acm.org/doi/10.1145/1276377.1276472
Ramanarayanan GFerwerda JWalter BBala KLevoy M(2007)Visual equivalenceACM SIGGRAPH 2007 papers10.1145/1275808.1276472(76-es)Online publication date: 5-Aug-2007
https://dl.acm.org/doi/10.1145/1275808.1276472
Chow YPose RRegan MPhillips J(2006)Human visual perception of region warping distortionsProceedings of the 29th Australasian Computer Science Conference - Volume 4810.5555/1151699.1151724(217-226)Online publication date: 1-Jan-2006
https://dl.acm.org/doi/10.5555/1151699.1151724
Glencross MChalmers ALin MOtaduy MGutierrez DFinnegan JShreiner D(2006)Exploiting perception in high-fidelity virtual environments (Additional presentations from the 24th course are available on the citation page)ACM SIGGRAPH 2006 Courses10.1145/1185657.1185814(1-es)Online publication date: 30-Jul-2006
https://dl.acm.org/doi/10.1145/1185657.1185814
Chow YPose RRegan MPhillips JLee YShamsuddin SGutierrez DSuaib N(2006)Human visual perception of region warping distortions with different display and scene characteristicsProceedings of the 4th international conference on Computer graphics and interactive techniques in Australasia and Southeast Asia10.1145/1174429.1174490(357-365)Online publication date: 29-Nov-2006
https://dl.acm.org/doi/10.1145/1174429.1174490

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