A new language and inference algorithm for stochastic modeling is presented. This work refines and generalizes the stochastic functional language originally proposed by [1]. The l...
Generating 3D models of real world objects is a common task during development of any augmented reality application. This paper describes how ProFORMA (Probabilistic Feature-based...
We propose a method to learn heterogeneous models of object classes for visual recognition. The training images contain a preponderance of clutter and learning is unsupervised. Ou...
Model Abstraction from Examples Yakov Keselman, Member, IEEE, and Sven Dickinson, Member, IEEE The recognition community has typically avoided bridging the representational gap bet...
— Recent research has shown that robots can model their world with Multi-Level (ML) surface maps, which utilize ‘patches’ in a 2D grid space to represent various environment ...
Cesar Rivadeneyra, Isaac Miller, Jonathan R. Schoe...