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Planning of a Multi Sensor System for Human Activities Space – Aspects of Iso-disparrity Surface
Responsible organisation
2007 (English)Conference paper, Published paper (Refereed) Published
Abstract [en]

The Intelligent Vision Agent System, IVAS, is a system for automatic target detection, identification and information processing for use in human activities surveillance. This system consists of multiple sensors, and with control of their deployment and autonomous servo. Finding the optimal configuration for these sensors in order to capture the target objects and their environment to a required specification is a crucial problem. With a stereo pair of sensors, the 3D space can be discretized by an iso-disparity surface, and the depth reconstruction accuracy of the space is closely related to the iso-disparity curve positions. This paper presents a method to enable planning the position of these multiple stereo sensors in indoor environments. The proposed method is a mathematical geometry model, used to analyze the iso-disparity surface. We will show that the distribution of the iso-disparity surface and the depth reconstruction accuracy are controllable by the parameters of such model. This model can be used to dynamically adjust the positions, poses and baselines lengths of multiple stereo pairs of cameras in 3D space in order to get sufficient visibility and accuracy for surveillance tracking and 3D reconstruction. We implement the model and present uncertainty maps of depth reconstruction calculated while varying the baseline length, focal length, stereo convergence angle and sensor pixel length. The results of these experiments show how the depth reconstruction uncertainty depends on stereo pair’s baseline length, zooming and sensor physical properties.

Place, publisher, year, edition, pages
Florence: SPIE--The International Society for Optical Engineering , 2007.
Keyword [en]
iso-disparity surface, multiple surveillance sensors, stereo vision, sensor configuration, 3D reconstruction
National Category
Signal Processing Computer Science
Identifiers
URN: urn:nbn:se:bth-8858DOI: 10.1117/12.738138ISI: 000253668100012Local ID: oai:bth.se:forskinfo6D518FE339192203C12573B9007CB60FOAI: oai:DiVA.org:bth-8858DiVA: diva2:836613
Conference
SPIE Europe, Security and Defence Conference
Note
http://spiedl.aip.org/getabs/servlet/GetabsServlet?prog=normal&id=PSISDG00673900 000167390D000001&idtype=cvips&gifs=yesAvailable from: 2012-09-18 Created: 2007-12-22 Last updated: 2016-09-20Bibliographically approved

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fulltext(346 kB)156 downloads
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a80bf662a237222158b7c3edc428b1c2cd9a5cfd96ce988f7f0324400d8840d6f097057ae4ee3a2e2db3806b1e77038b9b79d22563d013aeab3792c46aff9cb6
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Khatibi, SiamakKulesza, Wlodek
Signal ProcessingComputer Science

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf