Consistent Surface Color for Texturing Large Objects in Outdoor Scenes
Abstract
Color appearance of an object is significantly influenced by the color of the illumination. When the illumination color changes, the color appearance of the object change accordingly, causing its appearance to be inconsistent. To arrive at color constancy, we have developed a physics-based method of estimating and removing the illumination color. In this paper, we focus on the use of this method to deal with outdoor scenes, since very few physics-based methods have successfully handled outdoor color constancy. Our method is principally based on shadowed and non-shadowed regions. Previously researchers have discovered that shadowed regions are illuminated by sky light, while non-shadowed regions are illuminated by a combination of sky light and sunlight. Based on this difference of illumination, we estimate the illumination colors (both the sunlight and the sky light) and then remove them. To reliably estimate the illumination colors in outdoor scenes, we include the analysis of noise, since the presence of noise is inevitable in natural images. As a result, compared to existing methods, the proposed method is more effective and robust in handling outdoor scenes. In addition, the proposed method requires only a single input image, making it useful for many applications of computer vision
Cite
Text
Kawakami et al. "Consistent Surface Color for Texturing Large Objects in Outdoor Scenes." IEEE/CVF International Conference on Computer Vision, 2005. doi:10.1109/ICCV.2005.62Markdown
[Kawakami et al. "Consistent Surface Color for Texturing Large Objects in Outdoor Scenes." IEEE/CVF International Conference on Computer Vision, 2005.](https://mlanthology.org/iccv/2005/kawakami2005iccv-consistent/) doi:10.1109/ICCV.2005.62BibTeX
@inproceedings{kawakami2005iccv-consistent,
title = {{Consistent Surface Color for Texturing Large Objects in Outdoor Scenes}},
author = {Kawakami, Rei and Ikeuchi, Katsushi and Tan, Robby T.},
booktitle = {IEEE/CVF International Conference on Computer Vision},
year = {2005},
pages = {1200-1207},
doi = {10.1109/ICCV.2005.62},
url = {https://mlanthology.org/iccv/2005/kawakami2005iccv-consistent/}
}