000182538 001__ 182538
000182538 005__ 20190316235531.0
000182538 0247_ $$2doi$$a10.1109/WACV.2013.6475015
000182538 037__ $$aCONF
000182538 245__ $$aWhat is the Space of Spectral Sensitivity Functions for Digital Color Cameras?
000182538 269__ $$a2013
000182538 260__ $$c2013
000182538 336__ $$aConference Papers
000182538 500__ $$aThe database and code are available at http://www.cis.rit.edu/jwgu/
000182538 520__ $$aCamera spectral sensitivity functions relate scene radiance with captured RGB triplets. They are important for many computer vision tasks that use color information, such as multispectral imaging, color rendering, and color constancy. In this paper, we aim to explore the space of spectral sensitivity functions for digital color cameras. After collecting a database of 28 cameras covering a variety of types, we find this space convex and two-dimensional. Based on this statistical model, we propose two methods to recover camera spectral sensitivities using regular reflective color targets (e.g., color checker) from a single image with and without knowing the illumination. We show the proposed model is more accurate and robust for estimating camera spectral sensitivities than other basis functions. We also show two applications for the recovery of camera spectral sensitivities — simulation of color rendering for cameras and computational color constancy.
000182538 6531_ $$adigital cameras
000182538 6531_ $$aspectral sensitivity functions
000182538 6531_ $$acolor checker
000182538 6531_ $$acamera spectral sensitivities
000182538 6531_ $$acolor rendering
000182538 6531_ $$acolor constancy
000182538 6531_ $$aNCCR-MICS/EMSP
000182538 6531_ $$aNCCR-MICS
000182538 700__ $$0(EPFLAUTH)229062$$g229062$$aJiang, Jun
000182538 700__ $$aLiu, Dengyu
000182538 700__ $$aGu, Jinwei
000182538 700__ $$aSüsstrunk, Sabine$$g125681$$0241946
000182538 7112_ $$dJanuary 17-18, 2013$$cClearwater Beach, Florida, USA$$aIEEE Workshop on the Applications of Computer Vision (WACV)
000182538 773__ $$tIEEE Workshop on the Applications of Computer Vision (WACV)$$q168-179
000182538 8564_ $$uhttp://www.cis.rit.edu/jwgu/$$zURL
000182538 8564_ $$uhttps://infoscience.epfl.ch/record/182538/files/egpaper_final.pdf$$zn/a$$s10037879$$yn/a
000182538 909C0 $$xU10429$$0252320$$pIVRL
000182538 909CO $$qGLOBAL_SET$$pconf$$ooai:infoscience.tind.io:182538$$pIC
000182538 917Z8 $$x125681
000182538 917Z8 $$x125681
000182538 917Z8 $$x125681
000182538 917Z8 $$x125681
000182538 937__ $$aEPFL-CONF-182538
000182538 973__ $$rREVIEWED$$sPUBLISHED$$aEPFL
000182538 980__ $$aCONF