The Perception of Lighting Inconsistencies in Composite Outdoor Scenes

Author:

Tan Minghui1,Lalonde Jean-François2,Sharan Lavanya3,Rushmeier Holly1,O'Sullivan Carol4

Affiliation:

1. Yale University, New Haven, CT, U.S.A.

2. Laval University, Quebec City, QC, Canada

3. Massachusetts Institute of Technology, Cambridge, MA

4. Disney Research Los Angeles, Glendale, CA, U.S.A.

Abstract

It is known that humans can be insensitive to large changes in illumination. For example, if an object of interest is extracted from one digital photograph and inserted into another, we do not always notice the differences in illumination between the object and its new background. This inability to spot illumination inconsistencies is often the key to success in digital “doctoring” operations. We present a set of experiments in which we explore the perception of illumination in outdoor scenes. Our results can be used to predict when and why inconsistencies go unnoticed. Applications of the knowledge gained from our studies include smarter digital “cut-and-paste” and digital “fake” detection tools, and image-based composite scene backgrounds for layout and previsualization.

Funder

National Science Foundation

Publisher

Association for Computing Machinery (ACM)

Subject

Experimental and Cognitive Psychology,General Computer Science,Theoretical Computer Science

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Estimating lighting direction in scenes with multiple objects;Attention, Perception, & Psychophysics;2023-08-01

2. Can people detect errors in shadows and reflections?;Attention, Perception, & Psychophysics;2019-06-28

3. Perspectives on the definition of visually lossless quality for mobile and large format displays;Journal of Electronic Imaging;2018-10-11

4. Influence of Screen Size and Field of View on Perceived Brightness;ACM Transactions on Applied Perception;2018-08-08

5. A Survey on Image-Based Approaches of Synthesizing Objects;2016 International Conference on Virtual Reality and Visualization (ICVRV);2016-09

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