Bayesian Inference in Model-Based Machine Vision
Artificial Intelligence
2013-04-11 v1
Abstract
This is a preliminary version of visual interpretation integrating multiple sensors in SUCCESSOR, an intelligent, model-based vision system. We pursue a thorough integration of hierarchical Bayesian inference with comprehensive physical representation of objects and their relations in a system for reasoning with geometry, surface materials and sensor models in machine vision. Bayesian inference provides a framework for accruing_ probabilities to rank order hypotheses.
Cite
@article{arxiv.1304.2720,
title = {Bayesian Inference in Model-Based Machine Vision},
author = {Thomas O. Binford and Tod S. Levitt and Wallace B. Mann},
journal= {arXiv preprint arXiv:1304.2720},
year = {2013}
}
Comments
Appears in Proceedings of the Third Conference on Uncertainty in Artificial Intelligence (UAI1987)