DocumentCode
457230
Title
An LVQ-based Automotive Occupant Classification System
Author
Kennedy, Karl R. ; Nathan, John F. ; Shridhar, M.
Author_Institution
Lear Corp., Southfield, MI
Volume
2
fYear
0
fDate
0-0 0
Firstpage
662
Lastpage
665
Abstract
This paper presents a description of a system designed to classify a passenger in an automobile into one of three classes: a) adult, b) children (6 years and younger) and infants in child seats and c) empty seat. The authors examine the application of neural networks (BP, LVQ etc.) for this occupant classification system (OCS)
Keywords
automotive engineering; image classification; learning (artificial intelligence); neural nets; vector quantisation; LVQ-based automotive occupant classification system; neural networks; passenger classification; Automobiles; Automotive engineering; Costs; Injuries; Pattern recognition; Pediatrics; Sensor arrays; Sensor systems; Testing; US Department of Transportation;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 2006. ICPR 2006. 18th International Conference on
Conference_Location
Hong Kong
ISSN
1051-4651
Print_ISBN
0-7695-2521-0
Type
conf
DOI
10.1109/ICPR.2006.261
Filename
1699292
Link To Document