Title :
An LVQ-based Automotive Occupant Classification System
Author :
Kennedy, Karl R. ; Nathan, John F. ; Shridhar, M.
Author_Institution :
Lear Corp., Southfield, MI
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;
Conference_Titel :
Pattern Recognition, 2006. ICPR 2006. 18th International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
0-7695-2521-0
DOI :
10.1109/ICPR.2006.261
