Title :
An eigenface approach for estimating driver pose
Author :
Watta, Paul ; Gandhi, Nitin ; Lakshmanan, Sridhar
Author_Institution :
Dept. of Electr. & Comput. Eng., Michigan Univ., Dearborn, MI, USA
Abstract :
In this paper, we present a non-parametric method which can be used to analyze facial video data of an automobile driver as he or she drives the vehicle. Each frame in the video sequence is classified using an eigenface representation. A database of face pose images is constructed, and experimental results are given which measure the performance of the method on a large test set. Variations in the performance as the number of faces used to train the classifier, as well as the number of eigen coefficients in the representation are varied, are also reported
Keywords :
face recognition; human factors; image sequences; psychology; traffic engineering computing; visual databases; automobile driver; database; driver pose estimation; eigen coefficients; eigenface representation; pattern classification; video sequence; Automotive engineering; Driver circuits; Fatigue; Feature extraction; Image databases; Intelligent transportation systems; Safety devices; Testing; Vehicle driving; Wheels;
Conference_Titel :
Intelligent Transportation Systems, 2000. Proceedings. 2000 IEEE
Conference_Location :
Dearborn, MI
Print_ISBN :
0-7803-5971-2
DOI :
10.1109/ITSC.2000.881091
