Surface Shape from Specularities
In this paper a method for reconstructing a specular surface from an image sequence is presented. It is based on tracking both feature points and specularities through the sequence. The feature points are used to calculate the motion of the camera and provide depth information for some points on the boundary of the surface. The specularities give constraints on the surface normal and these constraints are complemented by a smoothness condition in order to estimate the surface shape. The smoothness measure is based on minimizing the surface curvature and a spline representation of the surface is used in the optimization step.
Using the proposed method it is possible to reconstruct completely textureless smooth surfaces. This is shown in both simulated and real experiments.
KeywordsSpecularities Surface Estimation Structrure from Motion Splines
- 1.Pollefeys, M., Koch, R., Van Gool, L.: Self-calibration and metric reconstruction in spite of varying and unknown internal camera parameters. In: Int. Conf. Computer Vision, Mumbai, India (1998) 90–95Google Scholar
- 2.Nister, D.: Automatic Dense Reconstruction from Uncalibrated Video Sequences. PhD thesis, Royal Institute of Technology, KTH (2001)Google Scholar
- 4.Morris, D., Kanade, T.: Image-consistent surface triangulation. In: Conf. Computer Vision and Pattern Recognition. Volume 1., Hilton Head SC, USA (2000) 332–338Google Scholar
- 5.Zisserman, A., Giblin, P., Blake, A.: The information available to a moving observer from specularities. Image and vision computing (1989)Google Scholar
- 7.Savarese, S., Perona, P.: Local analysis for 3d reconstruction of specular surfaces — part ii. In: Proc. European Conf. on Computer Vision. (2002) 759–774Google Scholar
- 8.Halstead, M.A., Barsky, B.A., Klein, S.A., Mandell, R.B.: Reconstructing curved surfaces from specular reflection patterns using spline fitting of normals. In: Siggraph. (1996) 335–342Google Scholar
- 9.Heyden, A., Åström, K.: Euclidean reconstruction from image sequences with varying and unknown focal length and principal point. In: Proc. Conf. Computer Vision and Pattern Recognition. (1997) 438–443Google Scholar
- 10.Triggs, B., McLauchlan, P.F., Hartley, R.I., Fitzgibbon, A.W.: Special sessions — bundle adjustment — a modern synthesis. Lecture Notes in Computer Science 1883 (2000) 298–372Google Scholar
- 12.Farin, G.: Curves and Surfaces for CAGD: A Practical Guide. Academic Press (2002)Google Scholar
- 13.Pressley, A.: Elementary Differential Geometry. Springer-Verlag (2001)Google Scholar