What you look at is what you get: eye movement-based interaction techniques
CHI '90 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Constraining Object Features Using a Polarization Reflectance Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
Estimation of Illuminant Direction, Albedo, and Shape from Shading
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face recognition: the problem of compensating for changes in illumination direction
ECCV '94 Proceedings of the third European conference on Computer vision (vol. 1)
Proceedings of the 25th annual conference on Computer graphics and interactive techniques
Multiple Illuminant Direction Detection with Application to Image Synthesis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Adaptive Image Segmentation by Combining Photometric Invariant Region and Edge Information
IEEE Transactions on Pattern Analysis and Machine Intelligence
High Confidence Visual Recognition of Persons by a Test of Statistical Independence
IEEE Transactions on Pattern Analysis and Machine Intelligence
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Estimation of Multiple Illuminants from a Single Image of Arbitrary Known Geometry
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
Diffuse-Specular Separation and Depth Recovery from Image Sequences
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
Stereo in the presence of specular reflection
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Highlight Removal by Illumination-Constrained Inpainting
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Separating Reflection Components of Textured Surfaces using a Single Image
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
An Ocularist's Approach to Human Iris Synthesis
IEEE Computer Graphics and Applications
ACM SIGGRAPH 2004 Papers
Separating Reflections in Human Iris Images for Illumination Estimation
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Separating Reflections from Images Using Kernel Independent Component Analysis
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 03
Illumination Invariant Face Recognition Using Near-Infrared Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Display-camera calibration using eye reflections and geometry constraints
Computer Vision and Image Understanding
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Eyes exhibit a significant amount of specular reflection and could be used to derive a detailed estimate of frontal illumination. To determine a more accurate estimate of illumination from the environment, iris color and texture should be separated from the specularly reflected light, since they may substantially obscure reflections of the scene. In this paper, a method is presented for separating corneal reflections in an image of human irises. We consider the iris texture to be diffuse, and the observed image color is produced as the sum of the diffuse component and the specular component. A number of methods have been proposed to separate or decompose these two components. To our knowledge, all methods that use a single input image demonstrated success in only limited cases, such as for uniform colored lighting and simple object textures. They are not applicable to irises, which exhibit intricate textures and complicated reflections of the environment. To make this problem feasible, our method capitalizes on physical characteristics of human irises to obtain an illumination estimate that encompasses the prominent light contributors in the scene. Results of the algorithm are presented for eyes of different colors, including light colored eyes for which reflection separation is necessary to determine a valid illumination estimate.