Recognition by Linear Combinations of Models
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part I
Surface reconstruction from unorganized points
SIGGRAPH '92 Proceedings of the 19th annual conference on Computer graphics and interactive techniques
Numerical recipes in C (2nd ed.): the art of scientific computing
Numerical recipes in C (2nd ed.): the art of scientific computing
SIGGRAPH '93 Proceedings of the 20th annual conference on Computer graphics and interactive techniques
SIGGRAPH '96 Proceedings of the 23rd annual conference on Computer graphics and interactive techniques
Surface simplification using quadric error metrics
Proceedings of the 24th annual conference on Computer graphics and interactive techniques
Progressive simplicial complexes
Proceedings of the 24th annual conference on Computer graphics and interactive techniques
Multidimensional Morphable Models: A Framework for Representing and Matching Object Classes
International Journal of Computer Vision
A morphable model for the synthesis of 3D faces
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Generalized Image Matching: Statistical Learning of Physically-Based Deformations
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume II - Volume II
Topologically adaptable snakes
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Linear Object Classes and Image Synthesis from a Single Example Image
Linear Object Classes and Image Synthesis from a Single Example Image
Recognition and Structure from one 2D Model View: Observations on Prototypes, Object Classes and Symmetries
Projective Structure from two Uncalibrated Images: Structure from Motion and Recognition
Projective Structure from two Uncalibrated Images: Structure from Motion and Recognition
Example Based Image Analysis and Synthesis
Example Based Image Analysis and Synthesis
A Bootstrapping Algorithm for Learning Linear Models of Object Classes
A Bootstrapping Algorithm for Learning Linear Models of Object Classes
Three-Dimensional Correspondence
Three-Dimensional Correspondence
Recovering articulated object models from 3D range data
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
Object correspondence as a machine learning problem
ICML '05 Proceedings of the 22nd international conference on Machine learning
Symbolic Signatures for Deformable Shapes
IEEE Transactions on Pattern Analysis and Machine Intelligence
Navigating in a Shape Space of Registered Models
IEEE Transactions on Visualization and Computer Graphics
Deformation-driven shape correspondence
SGP '08 Proceedings of the Symposium on Geometry Processing
Automatic registration for articulated shapes
SGP '08 Proceedings of the Symposium on Geometry Processing
Shape analysis using a point-based statistical shape model built on correspondence probabilities
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention - Volume Part I
Comparison of primate prefrontal and premotor cortex neuronal activity during visual categorization
Journal of Cognitive Neuroscience
3D active shape models using gradient descent optimization of description length
IPMI'05 Proceedings of the 19th international conference on Information Processing in Medical Imaging
Semi-supervised facial landmark annotation
Computer Vision and Image Understanding
Time course of shape and category selectivity revealed by eeg rapid adaptation
Journal of Cognitive Neuroscience
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We describe a novel automatic technique for finding a dense correspondence between a pair of n-dimensional surfaces with arbitrary topologies. This method employs a different formulation than previous correspondence algorithms (such as optical flow) and includes images as a special case. We use this correspondence algorithm to build Morphable Surface Models (an extension of Morphable Models) from examples. We present a method for matching the model to new surfaces and demonstrate their use for analysis, synthesis, and clustering.