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Practical Acceleration Strategies for the Predictive Visualization of Fading Phenomena

Published: 23 May 2016 Publication History

Abstract

Appearance changes caused by light exposure provide important cues that impart a sense of realism to a computer-generated scene. For instance, a carpet may fade or wood may turn yellow over time as a result of many years of light exposure. In this paper, we analyse the key performance and accuracy trade-offs associated with the physically-based simulation of these phenomena. This analysis may be used to guide the selection of simulation parameters in order to achieve optimal color-accuracy and minimize runtime. We also propose a practical method to enable the predictive visualization of these phenomena within applications requiring interactive rates with minimal loss of accuracy. The effectiveness of the proposed techniques is demonstrated through simulations and image sequences depicting fading and yellowing caused by several years of exposure to light.

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Cited By

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  • (2020)Color Degradation of Printed ImagesIEEE Transactions on Reliability10.1109/TR.2019.294590169:2(458-470)Online publication date: Jun-2020
  • (2018)Degradation Modeling and Prediction of Ink Fading and Diffusion of Printed ImagesIEEE Transactions on Reliability10.1109/TR.2017.278017067:1(184-195)Online publication date: Mar-2018

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cover image ACM Other conferences
CASA '16: Proceedings of the 29th International Conference on Computer Animation and Social Agents
May 2016
200 pages
ISBN:9781450347457
DOI:10.1145/2915926
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 the author(s) 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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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 23 May 2016

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Author Tags

  1. natural phenomena
  2. physically-based simulation
  3. visualization

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  • Research-article
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CASA '16
CASA '16: Computer Animation and Social Agents
May 23 - 25, 2016
Geneva, Switzerland

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Overall Acceptance Rate 18 of 110 submissions, 16%

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Cited By

View all
  • (2020)Color Degradation of Printed ImagesIEEE Transactions on Reliability10.1109/TR.2019.294590169:2(458-470)Online publication date: Jun-2020
  • (2018)Degradation Modeling and Prediction of Ink Fading and Diffusion of Printed ImagesIEEE Transactions on Reliability10.1109/TR.2017.278017067:1(184-195)Online publication date: Mar-2018

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