Revisiting gray pixel for statistical illumination estimation
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Yksityiskohdat
| Alkuperäiskieli | Englanti |
|---|---|
| Otsikko | VISIGRAPP 2019 - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications |
| Toimittajat | Andreas Kerren, Christophe Hurter, Jose Braz |
| Kustantaja | SCITEPRESS |
| Sivut | 36-46 |
| Sivumäärä | 11 |
| ISBN (elektroninen) | 9789897583544 |
| DOI - pysyväislinkit | |
| Tila | Julkaistu - 2019 |
| OKM-julkaisutyyppi | A4 Artikkeli konferenssijulkaisussa |
| Tapahtuma | International Conference on Computer Vision Theory and Applications - Prague, Tshekki Kesto: 25 helmikuuta 2019 → 27 helmikuuta 2019 |
Conference
| Conference | International Conference on Computer Vision Theory and Applications |
|---|---|
| Maa | Tshekki |
| Kaupunki | Prague |
| Ajanjakso | 25/02/19 → 27/02/19 |
Tiivistelmä
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.