System and process for optimal texture map reconstruction...

Details System and process for optimal texture map reconstruction... System and process for optimal texture map reconstruction...

2006-01-10

2006-01-10

Bella, Matthew C. (Department: 2676)

Computer graphics processing and selective visual display system

Computer graphics processing

Attributes

Reexamination Certificate

active

06985156

ABSTRACT:
A system and process for reconstructing optimal texture maps from multiple views of a scene is described. In essence, this reconstruction is based on the optimal synthesis of textures from multiple sources. This is generally accomplished using basic image processing theory to derive the correct weights for blending the multiple views. Namely, the steps of reconstructing, warping, prefiltering, and resampling are followed in order to warp reference textures to a desired location, and to compute spatially-variant weights for optimal blending. These weights take into consideration the anisotropy in the texture projection and changes in sampling frequency due to foreshortening. The weights are combined and the computation of the optimal texture is treated as a restoration problem, which involves solving a linear system of equations. This approach can be incorporated in a variety of applications, such as texturing of 3D models, analysis by synthesis methods, super-resolution techniques, and view-dependent texture mapping.

REFERENCES:
patent: 6825850 (2004-11-01), Wang et al.
patent: 2003/0052837 (2003-03-01), Raskar

Affiliated with

Also associated with

Rating

System and process for optimal texture map reconstruction... does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with System and process for optimal texture map reconstruction..., we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and System and process for optimal texture map reconstruction... will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFUS-PAI-O-3581910