Fundamentals of interactive computer graphics
Fundamentals of interactive computer graphics
A human factors study of color notation systems for computer graphics
Communications of the ACM
S an Interactive Environment for Data Analysis and Graphics
S an Interactive Environment for Data Analysis and Graphics
An inexpensive scheme for calibration of a colour monitor in terms of CIE standard coordinates
SIGGRAPH '83 Proceedings of the 10th annual conference on Computer graphics and interactive techniques
Tablet-based valuators that provide one, two, or three degrees of freedom
SIGGRAPH '81 Proceedings of the 8th annual conference on Computer graphics and interactive techniques
SIGGRAPH '78 Proceedings of the 5th annual conference on Computer graphics and interactive techniques
Color spaces for computer graphics
SIGGRAPH '78 Proceedings of the 5th annual conference on Computer graphics and interactive techniques
On the parameters of human visual performance: an investigation of the benefits of antialiasing
CHI '87 Proceedings of the SIGCHI/GI Conference on Human Factors in Computing Systems and Graphics Interface
ACM Transactions on Graphics (TOG)
Precision requirements for digital color reproduction
ACM Transactions on Graphics (TOG)
Experimental comparison of splines using the shape-matching paradigm
ACM Transactions on Graphics (TOG)
Do color models really make a difference?
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
ACM Transactions on Graphics (TOG)
Jagged edges: when is filtering needed?
ACM Transactions on Graphics (TOG)
ACM Transactions on Graphics (TOG)
Audio-visual data mapping for GIS-based data: an experimental evaluation
Proceedings of the 1999 workshop on new paradigms in information visualization and manipulation in conjunction with the eighth ACM internation conference on Information and knowledge management
IEEE Computer Graphics and Applications
Exploring gradient-based face navigation interfaces
GI '04 Proceedings of the 2004 Graphics Interface Conference
oRGB: a practical opponent color space for computer graphics
IEEE Computer Graphics and Applications - Special issue title on generating 3D building models a VR playground for teaching math
A scrubbing technique for the automatic detection of victims in urban search and rescue video
Proceedings of the 6th International Wireless Communications and Mobile Computing Conference
Stippling technique based on color analysis
PCM'05 Proceedings of the 6th Pacific-Rim conference on Advances in Multimedia Information Processing - Volume Part II
Machine learning to design full-reference image quality assessment algorithm
Image Communication
Combining color and haar wavelet responses for aerial image classification
ICAISC'12 Proceedings of the 11th international conference on Artificial Intelligence and Soft Computing - Volume Part I
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The increasing availability of affordable color raster graphics displays has made it important to develop a better understanding of how color can be used effectively in an interactive environment. Most contemporary graphics displays offer a choice of some 16 million colors; the user's problem is to find the right color.Folklore has it that the RGB color space arising naturally from color display hardware is user-hostile and that other color models such as the HSV scheme are preferable. Until now there has been virtually no experimental evidence addressing this point.We describe a color matching experiment in which subjects used one of two tablet-based input techniques, interfaced through one of five color models, to interactively match target colors displayed on a CRT.The data collected show small but significant differences between models in the ability of subjects to match the five target colors used in this experiment. Subjects using the RGB color model matched quickly but inaccurately compared with those using the other models. The largest speed difference occurred during the early convergence phase of matching. Users of the HSV color model were the slowest in this experiment, both during the convergence phase and in total time to match, but were relatively accurate. There was less variation in performance during the second refinement phase of a match than during the convergence phase.Two-dimensional use of the tablet resulted in faster but less accurate performance than did strictly one-dimensional usage.Significant learning occurred for users of the Opponent, YIQ, LAB, and HSV color models, and not for users of the RGB color model.