Deduction of high level spatial relations

Kieronska, Dorota H. and Venkatesh, Svetha 1992, Deduction of high level spatial relations, in Proceedings : Technology for the Intelligent Factory /​ IEEE International Workshop on Emerging Technologies and Factory Automation, CRL Publishing, East Caulfield, Vic., pp. 684-687.

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Title Deduction of high level spatial relations
Author(s) Kieronska, Dorota H.
Venkatesh, Svetha
Conference name IEEE International Workshop on Emerging Technologies and Factory Automation (1st : 1992 : Melbourne, Vic.)
Conference location Melbourne, Vic.
Conference dates 11-14 Aug. 1992
Title of proceedings Proceedings : Technology for the Intelligent Factory /​ IEEE International Workshop on Emerging Technologies and Factory Automation
Editor(s) Dillon, Tharam S.
Zurawski, Richard.
Publication date 1992
Conference series IEEE International Workshop on Emerging Technologies and Factory Automation
Start page 684
End page 687
Total pages 4
Publisher CRL Publishing
Place of publication East Caulfield, Vic.
Keyword(s) Australia
data mining
geographic information systems
humans
large-scale systems
layout
object recognition
rough surfaces
surface roughness
surface topography
Summary The problem of deriving spatial relationships between objects in general requires high level abstract representation, and it would pose difficulties even for human observer. Based on a formalism for spatial layouts proposed earlier [KiV92, VeK921, we present methods for deducing high level spatial relations between objects by an active, sighted agent in a large-scale environment. The deduction of spatial relations is based on simple visual clues, and thus this technique is more feasible than schemes that rely on complex object recognition.
ISBN 0780308867
9780780308862
Language eng
Field of Research 089999 Information and Computing Sciences not elsewhere classified
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category E1.1 Full written paper - refereed
Persistent URL http://hdl.handle.net/10536/DRO/DU:30044902

Document type: Conference Paper
Collection: School of Information Technology
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