A morphable model for the synthesis of 3D faces
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
International Journal of Computer Vision - special issue on learning and vision at the center for biological and computational learning, Massachusetts Institute of Technology
Generalized barycentric coordinates on irregular polygons
Journal of Graphics Tools
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Anisotropic polygonal remeshing
ACM SIGGRAPH 2003 Papers
The space of human body shapes: reconstruction and parameterization from range scans
ACM SIGGRAPH 2003 Papers
Multidimensional Morphable Models
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
ACM SIGGRAPH 2004 Papers
ACM SIGGRAPH 2004 Papers
Journal of Cognitive Neuroscience
Example-based conceptual styling framework for automotive shapes
SBIM '07 Proceedings of the 4th Eurographics workshop on Sketch-based interfaces and modeling
A sketching interface for feature curve recovery of free-form surfaces
2009 SIAM/ACM Joint Conference on Geometric and Physical Modeling
Incorporating concept ontology into multi-level image indexing
Proceedings of the First International Conference on Internet Multimedia Computing and Service
A sketching interface for feature curve recovery of free-form surfaces
Computer-Aided Design
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New product development involves people with different backgrounds.Designers, engineers, and consumers all have different criteria, and these criteria interact.Early concepts evolve in this kind of collaborative context, and there is a need for dynamic visualization of the interaction between design shape and other shape-related design criteria. In this paper, a Morphable Model is defined from simplified representations of suitably chosen real cars, providing a continuous shape space to navigate, manipulate, and visualize. Physical properties and consumer-provided scores for the real cars (such as 'weight' and 'sportiness') are estimated for new designs across the shape space.This coupling allows one to manipulate the shape directly while reviewing the impact on estimated criteria, or conversely, to manipulate the criterial values of the current design to produce a new shape with more desirable attributes.