Object shape and reflectance modeling from observation

An object model for computer graphics applications should contain two aspects of information: shape and reflectance properties of the object. A number of techniques have been developed for modeling object shapes by observing real objects. In contrast, attempts to model reflectance properties of real objects have been rather limited. In most cases, modeled reflectance properties are too simple or too complicated to be used for synthesizing realistic images of the object.

[1]  Marc Levoy,et al.  A volumetric method for building complex models from range images , 1996, SIGGRAPH.

[2]  James J. Little,et al.  Reflectance function estimation and shape recovery from image sequence of a rotating object , 1995, Proceedings of IEEE International Conference on Computer Vision.

[3]  Adrian Hilton,et al.  Reliable Surface Reconstructiuon from Multiple Range Images , 1996, ECCV.

[4]  K. Torrance,et al.  Theory for off-specular reflection from roughened surfaces , 1967 .

[5]  Tony DeRose,et al.  Surface reconstruction from unorganized points , 1992, SIGGRAPH.

[6]  Chris L. Jackins,et al.  Oct-trees and their use in representing three-dimensional objects , 1980 .

[7]  Robert L. Cromwell.  Efficient Eigenvalues for Visualization , 1994, Graphics Gems.

[8]  Marc Rioux,et al.  Color Reflectance Modeling Using a Polychromatic Laser Range Sensor , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[9]  E LorensenWilliam,et al.  Marching cubes: A high resolution 3D surface construction algorithm , 1987 .

[10]  Katsushi Ikeuchi,et al.  Reflectance Analysis for 3D Computer Graphics Model Generation , 1996, CVGIP Graph. Model. Image Process..

[11]  Kosuke Sato,et al.  Determining Reflectance Properties of an Object Using Range and Brightness Images , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[12]  William E. Lorensen,et al.  Marching cubes: A high resolution 3D surface construction algorithm , 1987, SIGGRAPH.

[13]  Steven A. Shafer,et al.  Using color to separate reflection components , 1985 .

[14]  Tony DeRose,et al.  Mesh optimization , 1993, SIGGRAPH.

[15]  Terrance E. Boult,et al.  Constraining Object Features Using a Polarization Reflectance Model , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[16]  Katsushi Ikeuchi,et al.  Temporal-color space analysis of reflection , 1993, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[17]  K. Sato,et al.  Range imaging system utilizing nematic liquid crystal mask , 1987 .

[18]  Katsushi Ikeuchi,et al.  Consensus surfaces for modeling 3D objects from multiple range images , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[19]  T. Caelli,et al.  Inverting an illumination model from range and intensity maps , 1994 .

[20]  Shree K. Nayar,et al.  Removal of specularities using color and polarization , 1993, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[21]  Takeo Kanade,et al.  Surface Reflection: Physical and Geometrical Perspectives , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[22]  J WardGregory,et al.  Measuring and modeling anisotropic reflection , 1992 .

[23]  Gregory J. Ward,et al.  Measuring and modeling anisotropic reflection , 1992, SIGGRAPH.