NDLI: Vision detection of vehicle occupant classification with Legendre moments and Support Vector Machine

Content Provider	IEEE Xplore Digital Library
Author	Zhenhai Gao Lifei Duan
Copyright Year	2010
Description	Author affiliation: State Key Laboratory of Automobile Dynamics Simulation, Jilin University, Changchun, China (Zhenhai Gao; Lifei Duan)
Abstract	Intelligent airbag system can control its deploy time and force according to different types of occupant in different sitting position. The accurate detection of vehicle occupant is the precondition and plays an important role in such system. This paper presents a vision detection method using low-cost CMOS camera and pattern recognition algorithm for the classification of different occupant classes. First, in view of the relative fixed passenger room, pre-processing algorithm and occupant edge detection method for the measurement space of occupant image are established; then, principal feature of occupant image edge in the measurement space is described using Legendre moments; at last, classifier of vehicle occupant is obtained using Support Vector Machine so that the classification of vehicle occupant is made possible.
Starting Page	1979
Ending Page	1983
File Size	913309
Page Count	5
File Format	PDF
ISBN	9781424465132
e-ISBN	9781424465163
DOI	10.1109/CISP.2010.5646680
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-10-16
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines Legendre moments support vector machine Image edge detection vision detection Feature extraction Extraterrestrial measurements Cameras intelligent airbag system Classification algorithms occupant classification Vehicles
Content Type	Text
Resource Type	Article

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