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ICPR
2004
IEEE
16 years 7 months ago
Parameterisation Invariant Statistical Shape Models
In this paper novel theory to automate shape modelling is described. The main idea is to develop a theory that is intrinsically defined for curves, as opposed to a finite sample o...
Johan Karlsson, Anders Ericsson, Kalle Åstr&...
PG
2002
IEEE
15 years 11 months ago
Shape-Similarity Search of Three-Dimensional Models Using Parameterized Statistics
In this paper, we propose a method for shape-similarity search of 3D polygonal-mesh models. The system accepts triangular meshes, but tolerates degenerated polygons, disconnected ...
Ryutarou Ohbuchi, Tomo Otagiri, Masatoshi Ibato, T...
NAACL
1994
15 years 7 months ago
A Hybrid Approach to Adaptive Statistical Language Modeling
We desert'be our latest attempt at adaptive language modeling. At the heart of our approachis a Maximum Entropy(ME) modelwhich inc.orlxnatesmanyknowledgesources in a consiste...
Ronald Rosenfeld
ICCV
2003
IEEE
16 years 8 months ago
Inferring 3D Structure with a Statistical Image-Based Shape Model
We present an image-based approach to infer 3D structure parameters using a probabilistic "shape+structure" model. The 3D shape of an object class is represented by sets...
Kristen Grauman, Gregory Shakhnarovich, Trevor Dar...
AAAI
2008
15 years 8 months ago
Structure Learning on Large Scale Common Sense Statistical Models of Human State
Research has shown promise in the design of large scale common sense probabilistic models to infer human state from environmental sensor data. These models have made use of mined ...
William Pentney, Matthai Philipose, Jeff A. Bilmes