Visual metrics for the evaluation of sensor data quality in outdoor perception

Authors:
Christopher Brunner;Thierry Peynot
Affiliations:
The University of Sydney, Australia;The University of Sydney, Australia
Venue:
Proceedings of the 10th Performance Metrics for Intelligent Systems Workshop
Year:
2010

Citing 4
Cited 0

Information Theory, Inference & Learning Algorithms

Information Theory, Inference & Learning Algorithms
DCT-domain blind measurement of blocking artifacts in DCT-coded images

ICASSP '01 Proceedings of the Acoustics, Speech, and Signal Processing, 2001. on IEEE International Conference - Volume 03
Error modeling and calibration of exteroceptive sensors for accurate mapping applications

Journal of Field Robotics - Three-Dimensional Mapping, Part 3
The Marulan Data Sets: Multi-sensor Perception in a Natural Environment with Challenging Conditions

International Journal of Robotics Research

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper proposes an experimental study of quality metrics that can be applied to visual and infrared images acquired from cameras onboard an unmanned ground vehicle (UGV). The relevance of existing metrics in this context is discussed and a novel metric is introduced. Selected metrics are evaluated on data collected by a UGV in clear and challenging environmental conditions, represented in this paper by the presence of airborne dust or smoke.