Name
Abstract | ||
|---|---|---|
Images of a scene captured with multiple cameras have different color values due to variations in capture and color rendering across devices. We present a method to accurately retrieve color information from uncalibrated images taken under uncontrolled lighting conditions with an unknown device and no access to raw data, but with a limited number of reference colors in the scene. The method is used to assess skin tones for cosmetics recommendations. A subject is imaged with a calibration target in the scene. This target is extracted and its color values are used to compute a color correction transform that is applied to the entire image. We establish that the best mapping is done using a target consisting of skin colored patches representing a range of human skin colors. We show that color information extracted from images is well correlated with color data derived from spectral measurements of skin. Skin color can be consistently assessed across cameras with different color rendering and resolutions ranging from 0.1 Mpixels to 4.0 Mpixels. |
Year | Venue | Keywords |
|---|---|---|
2007 | FIFTEENTH COLOR IMAGING CONFERENCE: COLOR SCIENCE AND ENGINEERING SYSTEMS, TECHNOLOGIES, AND APPLICATIONS, FINAL PROGRAM AND PROCEEDINGS | camera calibration |
Field | DocType | Citations |
Computer vision,Color space,Color histogram,Computer science,Color depth,Color balance,Color correction,Artificial intelligence,RGB color model,False color,Color image | Conference | 3 |
PageRank | References | Authors |
0.57 | 1 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Joanna Marguier | 1 | 8 | 1.76 |
| Nina Bhatti | 2 | 59 | 7.81 |
| H. Harlyn Baker | 3 | 337 | 340.55 |
| Michael Harville | 4 | 369 | 35.55 |
| Sabine Süsstrunk | 5 | 4984 | 207.02 |