Active shape models—their training and application
Computer Vision and Image Understanding
EM algorithms for PCA and SPCA
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
A morphable model for the synthesis of 3D faces
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
Nonrigid 3-D/2-D Registration of Images Using Statistical Models
MICCAI '99 Proceedings of the Second International Conference on Medical Image Computing and Computer-Assisted Intervention
A Statistical Method for Robust 3D Surface Reconstruction from Sparse Data
3DPVT '04 Proceedings of the 3D Data Processing, Visualization, and Transmission, 2nd International Symposium
Pattern Recognition and Machine Learning (Information Science and Statistics)
Pattern Recognition and Machine Learning (Information Science and Statistics)
Atlas-based 3D-Shape Reconstruction from X-Ray Images
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 01
International Journal of Computer Vision
Reconstructing teeth with bite information
SCIA'07 Proceedings of the 15th Scandinavian conference on Image analysis
A novel deformation framework for face modeling from a few control points
RSKT'08 Proceedings of the 3rd international conference on Rough sets and knowledge technology
Reconstructing a whole face image from a partially damaged or occluded image by multiple matching
ICB'07 Proceedings of the 2007 international conference on Advances in Biometrics
MeshMed'12 Proceedings of the 2012 international conference on Mesh Processing in Medical Image Analysis
MCV'12 Proceedings of the Second international conference on Medical Computer Vision: recognition techniques and applications in medical imaging
Joint view-identity manifold for infrared target tracking and recognition
Computer Vision and Image Understanding
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Statistical shape models, and in particular morphable models, have gained widespread use in computer vision, computer graphics and medical imaging. Researchers have started to build models of almost any anatomical structure in the human body. While these models provide a useful prior for many image analysis task, relatively little information about the shape represented by the morphable model is exploited. We propose a method for computing and visualizing the remaining flexibility, when a part of the shape is fixed. Our method, which is based on Probabilistic PCA, not only leads to an approach for reconstructing the full shape from partial information, but also allows us to investigate and visualize the uncertainty of a reconstruction. To show the feasibility of our approach we performed experiments on a statistical model of the human face and the femur bone. The visualization of the remaining flexibility allows for greater insight into the statistical properties of the shape.