Calibrating and Optimizing Poses of Visual Sensors in Distributed Platforms

  • Many novel multimedia, home entertainment, visual surveillance and health applications use multiple audio-visual sensors. We present a novel approach for position and pose calibration of visual sensors, i.e. cameras, in a distributed network of general purpose computing devices (GPCs). It complements our work on position calibration of audio sensors and actuators in a distributed computing platform [22]. The approach is suitable for a wide range of possible - even mobile - setups since (a) synchronization is not required, (b) it works automatically, (c) only weak restrictions are imposed on the positions of the cameras, and (d) no upper limit on the number of cameras and displays under calibration is imposed. Corresponding points across different camera images are established automatically. Cameras do not have to share one common view. Only a reasonable overlap between camera subgroups is necessary. The method has been sucessfully tested in numerous multi-camera environments with aMany novel multimedia, home entertainment, visual surveillance and health applications use multiple audio-visual sensors. We present a novel approach for position and pose calibration of visual sensors, i.e. cameras, in a distributed network of general purpose computing devices (GPCs). It complements our work on position calibration of audio sensors and actuators in a distributed computing platform [22]. The approach is suitable for a wide range of possible - even mobile - setups since (a) synchronization is not required, (b) it works automatically, (c) only weak restrictions are imposed on the positions of the cameras, and (d) no upper limit on the number of cameras and displays under calibration is imposed. Corresponding points across different camera images are established automatically. Cameras do not have to share one common view. Only a reasonable overlap between camera subgroups is necessary. The method has been sucessfully tested in numerous multi-camera environments with a varying number of cameras and has proven itself to work extremely accurate. Once all distributed visual sensors are calibrated, we focus on post-optimizing their poses to increase coverage of the space observed. A linear programming approach is derived that determines jointly for each camera the pan and tilt angle that maximizes the coverage of the space at a given sampling frequency. Experimental results clearly demonstrate the gain in visual coverage.show moreshow less

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Metadaten
Author:Eva HörsterGND, Rainer LienhartGND
URN:urn:nbn:de:bvb:384-opus4-3336
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/399
Series (Serial Number):Reports / Technische Berichte der Fakultät für Angewandte Informatik der Universität Augsburg (2006-19)
Type:Report
Language:English
Publishing Institution:Universität Augsburg
Release Date:2006/10/26
GND-Keyword:Dreidimensionale Bildverarbeitung; Kalibrieren <Messtechnik>; Verteiltes System
Institutes:Fakultät für Angewandte Informatik
Fakultät für Angewandte Informatik / Institut für Informatik
Fakultät für Angewandte Informatik / Institut für Informatik / Lehrstuhl für Multimedia und Maschinelles Sehen
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik