Perception of solid shape from shading
Biological Cybernetics
Multiple Illuminant Direction Detection with Application to Image Synthesis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Estimation of Multiple Directional Light Sources for Synthesis of Mixed Reality Images
PG '02 Proceedings of the 10th Pacific Conference on Computer Graphics and Applications
Exposing digital forgeries by detecting inconsistencies in lighting
MM&Sec '05 Proceedings of the 7th workshop on Multimedia and security
Using Specularities to Recover Multiple Light Sources in the Presence of Texture
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 01
The influence of shape on the perception of material reflectance
ACM SIGGRAPH 2007 papers
The assumed light direction for perceiving shape from shading
Proceedings of the 5th symposium on Applied perception in graphics and visualization
Exposing Digital Forgeries in Complex Lighting Environments
IEEE Transactions on Information Forensics and Security - Part 1
Sparse lumigraph relighting by illumination and reflectance estimation from multi-view images
EGSR'06 Proceedings of the 17th Eurographics conference on Rendering Techniques
Perceptual considerations for motion blur rendering
ACM Transactions on Applied Perception (TAP)
Understanding and improving the realism of image composites
ACM Transactions on Graphics (TOG) - SIGGRAPH 2012 Conference Proceedings
Shadow map silhouette revectorization
Proceedings of the 18th meeting of the ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games
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In this paper we explore the ability of the human visual system to detect inconsistencies in the illumination of objects in images. We specifically focus on objects being lit from different angles as the rest of the image. We present the results of three different tests, two with synthetic objects and a third one with digitally manipulated real images. Our results seem to agree with previous publications exploring the topic, but we extend them by providing quantifiable data which in turn suggest approximate perceptual thresholds. Given that light detection in single images is an ill-posed problem, these thresholds can provide valid error limits to related algorithms in different contexts, such as compositing or augmented reality.