TY - GEN
T1 - Color calibration of multi-projector displays through automatic optimization of hardware settings
AU - Matt Steele, R.
AU - Ye, Mao
AU - Yang, Ruigang
PY - 2009
Y1 - 2009
N2 - We describe a system that performs automatic, camerabased photometric projector calibration by adjusting hardware settings (e.g. brightness, contrast, etc.). The approach has two basic advantages over software-correction methods. First, there is no software interface imposed on graphical programs: all imagery displayed on the projector benefits from the calibration immediately, without render-time overhead or code changes. Secondly, the approach benefits from the fact that projector hardware settings typically are capable of expanding or shifting color gamuts (e.g. trading off maximum brightness versus darkness of black levels), something that software methods, which only shrink gamuts, cannot do. In practice this means that hardware settings can possibly match colors between projectors while maintaining a larger overall color gamut (e.g. better contrast) than software-only correction can. The prototype system is fully automatic. The space of hardware settings is explored by using a computercontrolled universal remote to navigate each projector's menu system. An off-the-shelf camera observes each projector's response curves. A cost function is computed for the curves based on their similarity to each other, as well as intrinsic characteristics, including color balance, black level, gamma, and dynamic range. An approximate optimum is found using a heuristic combinatoric search. Results show significant qualitative improvements in the absolute colors, as well as the color consistency, of the display.
AB - We describe a system that performs automatic, camerabased photometric projector calibration by adjusting hardware settings (e.g. brightness, contrast, etc.). The approach has two basic advantages over software-correction methods. First, there is no software interface imposed on graphical programs: all imagery displayed on the projector benefits from the calibration immediately, without render-time overhead or code changes. Secondly, the approach benefits from the fact that projector hardware settings typically are capable of expanding or shifting color gamuts (e.g. trading off maximum brightness versus darkness of black levels), something that software methods, which only shrink gamuts, cannot do. In practice this means that hardware settings can possibly match colors between projectors while maintaining a larger overall color gamut (e.g. better contrast) than software-only correction can. The prototype system is fully automatic. The space of hardware settings is explored by using a computercontrolled universal remote to navigate each projector's menu system. An off-the-shelf camera observes each projector's response curves. A cost function is computed for the curves based on their similarity to each other, as well as intrinsic characteristics, including color balance, black level, gamma, and dynamic range. An approximate optimum is found using a heuristic combinatoric search. Results show significant qualitative improvements in the absolute colors, as well as the color consistency, of the display.
UR - http://www.scopus.com/inward/record.url?scp=70449570770&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=70449570770&partnerID=8YFLogxK
U2 - 10.1109/CVPR.2009.5204322
DO - 10.1109/CVPR.2009.5204322
M3 - Conference contribution
AN - SCOPUS:70449570770
SN - 9781424439911
T3 - 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPR Workshops 2009
SP - 55
EP - 60
BT - 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPR Workshops 2009
T2 - 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPR Workshops 2009
Y2 - 20 June 2009 through 25 June 2009
ER -