Recovering Structure Uncertainties From Noisy Sense Data

This work examines closely the possibilities for errors, mistakes and uncertainties in sensing systems. We identify and suggest techniques for modeling, analyzing, and recovering these uncertainties. This work concentrates on uncertainties in visual sensing for manipulators. The goal is to recover three-dimensional structure and motion characteristics of the environments under observation from noisy measurements. We also conjecture that the approaches described here are suitable for other sensors and parameters to be recovered. The computed uncertainties are utilized for reconstructing the geometry, motion parameters, and structure parameters under observation.http://www.sciencedirect.com/science/article/pii/S004579060000019

Recovering Structure Uncertainties from Noisy Sense Data

This work examines closely the possibilities for errors, mistakes and uncertainties in sensing systems. We identify and suggest techniques for modeling, analyzing, and recovering these uncertainties. This work concentrates on uncertainties in visual sensing for manipulators. The goal is to recover 3-D structure and motion characteristics of the environments under observation from noisy measurements. We also conjecture that the approaches described here are suitable for other sensors and parameters to be recovered. The computed uncertainties are utilized for reconstructing the geometry, motion parameters, and structure parameters under observation. 1 Introduction In this work we discuss uncertainty modeling for sensor systems. In particular, we describe some techniques for measuring and computing the uncertainties in recovering some visual parameters. We concentrate on presenting the sources of uncertainty in two dimensional visual data. Then we proceed to identify methods by which the..