Interactive retexturing from unordered images

2014 
The texture quality of 3D models, generated from either multi-view color images or color-depth images, mainly depends on the resolution of the images and the lighting condition used in the 3D reconstruction stage. It is often required to increase the texture quality or remove the unwanted artifacts such as seams or shadings without reinitiating the entire process. We propose an interactive method to seamlessly replace the low quality texture map of 3D models using unordered high resolution images taken later with different cameras. The camera pose of each new image is estimated using the nearest key-frame image with two-frame bundle adjustment. The new images with the estimated pose are then individually mapped onto the texture map. Finally the user-preferred regions in the specific images are seamlessly aligned with other texture patches in the combinatorial optimization framework. As demonstrated in the results, our approach significantly improves visual quality of textured 3D models while preserving the geometric details.
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