This paper describes a Bayesian approach for modeling 3D scenes as a collection of approximately planar layers that are arbitrarily positioned and oriented in the scene. In contra...
A probabilistic deformable model for the representation of brain structures is described. The statistically learned deformable model represents the relative location of head (skull...
Modeling environments with 3D feature based representations is a challenging issue in current mobile robotics. Fast and robust algorithms are required for applicability to navigati...
Adaptive sparse coding methods learn a possibly overcomplete set of basis functions, such that natural image patches can be reconstructed by linearly combining a small subset of t...
The Gauss map projects surface normals to a unit sphere, providing a powerful visualization of the geometry of a graphical object. It can be used to predict visual events caused b...
Bradley C. Lowekamp, Penny Rheingans, Terry S. Yoo