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Authors: James H. Niblock ; Jian-Xun Peng ; Karen R. McMenemy and George W. Irwin

Affiliation: Queen’s University Belfast, School of Electronics, Electrical Engineering and Computer Science, United Kingdom

Keyword(s): Model-based object tracking, camera position estimation.

Related Ontology Subjects/Areas/Topics: Applications ; Computer Vision, Visualization and Computer Graphics ; Feature Extraction ; Features Extraction ; Geometry and Modeling ; Human-Computer Interaction ; Image and Video Analysis ; Image-Based Modeling ; Informatics in Control, Automation and Robotics ; Methodologies and Methods ; Model-Based Object Tracking in Image Sequences ; Motion and Tracking ; Motion, Tracking and Stereo Vision ; Pattern Recognition ; Physiological Computing Systems ; Signal Processing, Sensors, Systems Modeling and Control ; Software Engineering

Abstract: The development of an autonomous system for the accurate measurement of the quality of aerodrome ground lighting (AGL) in accordance with current standards and recommendations is presented. The system is composed of an imager which is placed inside the cockpit of an aircraft to record images of the AGL during a normal descent to an aerodrome. Before the performance of the AGL is assessed, it is first necessary to uniquely identify each luminaire within the image and track it through the complete image sequence. A model-based (MB) methodology is used to ascertain the optimum match between a template of the AGL and the actual image data. Projective geometry, in addition to the image and real world location of the extracted luminaires, is then used to calculate the position of the camera at the instant the image was acquired. Algorithms are also presented which model the distortion apparent within the sensors optical system and average the camera’s intrinsic parameters over multiple f rames, so as to minimise the effects of noise on the acquired image data and hence make the camera’s estimated position and orientation more accurate. The positional information is validated using actual approach image data. (More)

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Paper citation in several formats:
H. Niblock, J.; Peng, J.; R. McMenemy, K. and W. Irwin, G. (2008). AUTONOMOUS MODEL-BASED OBJECT IDENTIFICATION & CAMERA POSITION ESTIMATION WITH APPLICATION TO AIRPORT LIGHTING QUALITY CONTROL. In Proceedings of the Third International Conference on Computer Vision Theory and Applications (VISIGRAPP 2008) - Volume 1: VISAPP; ISBN 978-989-8111-21-0; ISSN 2184-4321, SciTePress, pages 383-390. DOI: 10.5220/0001085503830390

@conference{visapp08,
author={James {H. Niblock}. and Jian{-}Xun Peng. and Karen {R. McMenemy}. and George {W. Irwin}.},
title={AUTONOMOUS MODEL-BASED OBJECT IDENTIFICATION & CAMERA POSITION ESTIMATION WITH APPLICATION TO AIRPORT LIGHTING QUALITY CONTROL},
booktitle={Proceedings of the Third International Conference on Computer Vision Theory and Applications (VISIGRAPP 2008) - Volume 1: VISAPP},
year={2008},
pages={383-390},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001085503830390},
isbn={978-989-8111-21-0},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the Third International Conference on Computer Vision Theory and Applications (VISIGRAPP 2008) - Volume 1: VISAPP
TI - AUTONOMOUS MODEL-BASED OBJECT IDENTIFICATION & CAMERA POSITION ESTIMATION WITH APPLICATION TO AIRPORT LIGHTING QUALITY CONTROL
SN - 978-989-8111-21-0
IS - 2184-4321
AU - H. Niblock, J.
AU - Peng, J.
AU - R. McMenemy, K.
AU - W. Irwin, G.
PY - 2008
SP - 383
EP - 390
DO - 10.5220/0001085503830390
PB - SciTePress