Xiaoguang Wang, Jonathan Lim, Robert T. Collins, and Allen R. Hanson
"Automated Texture Extraction from Multiple Images to Support Site
     Model Refinement and Visualization,"
Proc.Computer Graphics and Visualization, 
Plzen, Czech Republic,1996.


Texture mapping has wide and important applications in visualization and virtual reality. Surface texture extraction from a single image suffers from perspective distortion, data deficiency, and corruption caused by shadows and occlusions. In this paper, a system is developed for automated acquisition of complete and consistent texture maps from multiple images in order to support subsequent detailed surface analysis and scene rendering. Given camera and light source parameters for each image, and a geometric model of the scene, the textures of object surfaces are systematically collected into an organized orthographic library. Occlusions and shadows caused by objects in the scene are computed and associated with each retrieved surface. A "Best Piece Representation," algorithm is designed to combine the intensities from multiple views, resulting in a unique surface intensity representation. Detailed surface structures, such as windows and doors, are extracted from the uniquely represented surface images to refine the geometric model. Experiments show successul applications of this approach to model refinement and scene visualization.

Full Paper

Click here for full paper (572681 bytes, compressed using gzip).