Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149) (1999)
Fort Collins, Colorado
June 23, 1999 to June 25, 1999
Philip L. Worthington , University of York
Edwin R. Hancock , University of York
This paper makes two contributions to the problem of needle-map recovery using shape-from-shading. Firstly, we provide a geometric update procedure which allows the image irradiance equation to be satisfied as a hard-constraint. This improves the data-closeness of the recovered needle-map. Secondly, we consider how topographic constraints can be used to impose local consistency on the recovered needle-map. We present several alternative curvature consistency models, and provide an experimental assessment of the new shape-from-shading framework on both real-world images and synthetic images with known ground-truth surface-normals. The main conclusion drawn from our analysis is that the new framework allows rapid development of more appropriate constraints on the SFS problem.
P. L. Worthington and E. R. Hancock, "Data-Driven Shape-from-Shading Using Curvature Consistency," Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149)(CVPR), Fort Collins, Colorado, 1999, pp. 1287.