Abstract. A mobile robot that interacts with its environment needs a machineunderstandable representation of objects and their usages. We present an ontology of objects, with gener...
Eric Wang, Yong Se Kim, Hak Soo Kim, Jin Hyun Son,...
: This paper addresses the inference of probabilistic classification models using weakly supervised learning. The main contribution of this work is the development of learning meth...
We present a hierarchical generative model for object recognition that is constructed by weakly-supervised learning. A key component is a novel, adaptive patch feature whose width...
In real world scenes, objects to be classified are usually not visible from every direction, since they are almost always positioned on some kind of opaque plane. When moving a cam...
We have developed a generic ontology of objects, and a knowledge base of everyday physical objects. Objects are represented as assemblies of functional features and their spatial r...