Robot vision
Estimation of Illuminant Direction, Albedo, and Shape from Shading
IEEE Transactions on Pattern Analysis and Machine Intelligence
A new approach to photometric stereo
Pattern Recognition Letters
Rough surface classification using point statistics from photometric stereo
Pattern Recognition Letters
Fast Approximate Energy Minimization via Graph Cuts
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Simple Strategy for Calibrating the Geometry of Light Sources
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multi-camera Scene Reconstruction via Graph Cuts
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
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
Albedo Recovery Using a Photometric Stereo Approach
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 3 - Volume 3
Self-Calibration and Neural Network Implementation of Photometric Stereo
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 4 - Volume 4
What Energy Functions Can Be Minimizedvia Graph Cuts?
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Experimental Comparison of Min-Cut/Max-Flow Algorithms for Energy Minimization in Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Estimation of the Size and Location of Multiple Area Light Sources
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
Coplanar Light Sweep-Surface Supported Uncalibrated Photometric Stereo
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 4 - Volume 04
IEEE Transactions on Pattern Analysis and Machine Intelligence
Dense Photometric Stereo Using a Mirror Sphere and Graph Cut
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Photometric Stereo with General, Unknown Lighting
International Journal of Computer Vision
Super resolution using graph-cut
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part II
Binocular uncalibrated photometric stereo
ISVC'06 Proceedings of the Second international conference on Advances in Visual Computing - Volume Part I
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Given blurred observations of a stationary scene captured using a static camera but with different and unknown light source positions, we estimate the light source positions and scene structure (surface gradients) and perform blind image restoration. The images are restored using the estimated light source positions, surface gradients, and albedo. The surface of the object is assumed to be Lambertian. We first propose a simple approach to obtain a rough estimate of the light source position from a single image using the shading information which does not use any calibration or initialization. We model the prior information for the scene structure as a separate Markov random field (MRF) with discontinuity preservation, and the blur function is modeled as Gaussian. A proper regularization approach is then used to estimate the light source position, scene structure, and blur parameter. The optimization is carried out using the graph cuts approach. The advantage of the proposed approach is that its time complexity is much less as compared to other approaches that use global optimization techniques such as simulated annealing. Reducing the time complexity is crucial in many of the practical vision problems. Results of experimentation on both synthetic and real images are presented.