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.
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