DocumentCode :
779288
Title :
Optimal strategic recognition of objects based on candidate discriminating graph with coordinated sensors
Author :
Tang, Y.C. ; Lee, C. S George
Author_Institution :
AT&T Bell Lab., Naperville, IN, USA
Volume :
22
Issue :
4
fYear :
1992
Firstpage :
647
Lastpage :
661
Abstract :
An approach to strategic recognition of objects using multiple sensors based on the candidate discriminating graph (CADIG) is presented. A CADIG represents the candidates of an unknown object and the complete discriminating relations between the candidates in terms of relevant discriminators (geometric features). Strategic recognition is decomposed into two interacting procedures: the information acknowledgement procedure (IAP) and the sensory acquisition procedure (SAP). The IAP identifies the critical information for recognition as a set of discriminators from the CADIG and receives sensory examinations of these discriminators to eliminate invalid candidates from the CADIG. The SAP coordinates multiple sensors to examine the critical information identified in the IAP. This coordination is formulated as a constraint satisfaction problem and solved by the backtracking algorithm. The unknown object is recognized through iterations of the IAP and SAP until there is only one candidate left in the CADIG. The IAP and SAP are further integrated to achieve the optimal strategic recognition of objects
Keywords :
graph theory; iterative methods; pattern recognition; CADIG; backtracking algorithm; candidate discriminating graph; coordinated sensors; discriminators; information acknowledgement procedure; iterative methods; sensory acquisition procedure; strategic pattern recognition; Computer simulation; Cost function; Data mining; Feature extraction; Intelligent sensors; Machine intelligence; Performance analysis; Reliability theory; Tactile sensors;
fLanguage :
English
Journal_Title :
Systems, Man and Cybernetics, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9472
Type :
jour
DOI :
10.1109/21.156578
Filename :
156578
Link To Document :
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