Revisiting gray pixel for statistical illumination estimation
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review
Details
| Original language | English |
|---|---|
| Title of host publication | VISIGRAPP 2019 - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications |
| Editors | Andreas Kerren, Christophe Hurter, Jose Braz |
| Publisher | SCITEPRESS |
| Pages | 36-46 |
| Number of pages | 11 |
| ISBN (Electronic) | 9789897583544 |
| DOIs | |
| Publication status | Published - 2019 |
| Publication type | A4 Article in a conference publication |
| Event | International Conference on Computer Vision Theory and Applications - Prague, Czech Republic Duration: 25 Feb 2019 → 27 Feb 2019 |
Conference
| Conference | International Conference on Computer Vision Theory and Applications |
|---|---|
| Country | Czech Republic |
| City | Prague |
| Period | 25/02/19 → 27/02/19 |
Abstract
We present a statistical color constancy method that relies on novel gray pixel detection and mean shift clustering. The method, called Mean Shifted Grey Pixel – MSGP, is based on the observation: true-gray pixels are aligned towards one single direction. Our solution is compact, easy to compute and requires no training. Experiments on two real-world benchmarks show that the proposed approach outperforms state-of-the-art methods in the camera-agnostic scenario. In the setting where the camera is known, MSGP outperforms all statistical methods.
ASJC Scopus subject areas
Keywords
- Color Constancy, Gray Pixel, Illumination Estimation
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Field of science, Statistics Finland
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