Title :
Stochastic refinement of the visual hull to satisfy photometric and silhouette consistency constraints
Author :
Isidro ; Sclaroff, Stan
Author_Institution :
Dept. of Comput. Sci., Boston Univ., MA, USA
Abstract :
An iterative method for reconstructing a 3D polygonal mesh and color texture map from multiple views of an object is presented. In each iteration, the method first estimates a texture map given the current shape estimate. The texture map and its associated residual error image are obtained via maximum a posteriori estimation and reprojection of the multiple views into texture space. Next, the surface shape is adjusted to minimize residual error in texture space. The surface is deformed towards a photometrically-consistent solution via a series of 1D epipolar searches at randomly selected surface points. The texture space formulation has improved computational complexity over standard image-based error approaches, and allows computation of the reprojection error and uncertainty for any point on the surface. Moreover, shape adjustments can be constrained such that the recovered model´s silhouette matches those of the input images. Experiments with real world imagery demonstrate the validity of the approach.
Keywords :
cameras; computer vision; edge detection; image colour analysis; image reconstruction; image texture; maximum likelihood estimation; mesh generation; stereo image processing; 1D epipolar searches; 3D polygonal mesh; MAP framework; color texture map; computational complexity; computer vision; current shape estimate; image reconstruction; image-based error approach; maximum a posteriori estimation; multiple views; photometric constraints; real world imagery; residual error image; shape adjustments; silhouette consistency constraints; silhouette matches; stochastic refinement; surface points; surface shape; texture space; visual hull; Application software; Cameras; Computer vision; Image reconstruction; Photometry; Shape; Stochastic processes; Surface reconstruction; Surface texture; Uncertainty;
Conference_Titel :
Computer Vision, 2003. Proceedings. Ninth IEEE International Conference on
Conference_Location :
Nice, France
Print_ISBN :
0-7695-1950-4
DOI :
10.1109/ICCV.2003.1238645