Artificial evolution for computer graphics
Proceedings of the 18th annual conference on Computer graphics and interactive techniques
Spacetime constraints revisited
SIGGRAPH '93 Proceedings of the 20th annual conference on Computer graphics and interactive techniques
Hierarchical spacetime control
SIGGRAPH '94 Proceedings of the 21st annual conference on Computer graphics and interactive techniques
Generation of transfer functions with stochastic search techniques
Proceedings of the 7th conference on Visualization '96
Design galleries: a general approach to setting parameters for computer graphics and animation
Proceedings of the 24th annual conference on Computer graphics and interactive techniques
A morphable model for the synthesis of 3D faces
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
Volume Illustration: Nonphotorealistic Rendering of Volume Models
IEEE Transactions on Visualization and Computer Graphics
Multidimensional Transfer Functions for Interactive Volume Rendering
IEEE Transactions on Visualization and Computer Graphics
An automatic modeling of human bodies from sizing parameters
I3D '03 Proceedings of the 2003 symposium on Interactive 3D graphics
Artificial Intelligence: A Modern Approach
Artificial Intelligence: A Modern Approach
Cooperative, computer-aided design of scientific visualizations
VIS '91 Proceedings of the 2nd conference on Visualization '91
Improved use of continuous attributes in C4.5
Journal of Artificial Intelligence Research
Perceptually Linear Parameter Variations
Computer Graphics Forum
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In most graphics and visualization applications, the effects of the mapping parameters on the output domain are multidimensional, non-linear and discontinuous. The complexity of such mapping often makes it difficult for a user to manually explore and manipulate the design parameter space to produce the desired output. Computer assistance is therefore useful in setting the mapping parameter values to generate desired outputs. Existing systems rely on exploring the entire input parameter space, which can be time and resource-intensive, particularly if the number of input parameters is large. We introduce a new approach to handling a large number of mapping parameters more efficiently. The basis for our approach is the identification of a small and effective set of highlevel parameters that can be associated directly with the characteristics of the outputs. Users will have a better understanding of this small set of high-level parameters and can easily modify their values interactively to produce the desired outputs. We demonstrate this technique in manipulating mapping parameters for a non-photorealistic volume rendering application.