Visual scene understanding: A Bayesian approach
Abstract
Many methods for visual scene understanding rely on supervised training using very large data sets. While these methods can be succe"ssful in certain circumstances, they are very costly, brittle and provide little genuine understanding. Instead, we will develop a c"omputational framework for autonomous scene analysis that will learn object categories from a small number of observations. The proposed effort will use a Bayesian approach to learn object categories and relations between objects and object parts. Our approach will develop a framework for using both spatial and temporal contextual information and for integrating the two types of information during the learning and inference stages.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- May 05, 2017
- Source ID
- N000141712509
Entities
People
- Ernst Niebur
Organizations
- Johns Hopkins University
- Office of Naval Research
- United States Navy