Poster abstract: a machine learning approach for vehicle classification using passive infrared and ultrasonic sensors

Authors:
Ehsan Ullah Warriach;Christian Claudel
Affiliations:
University of Groningen, Groningen, Netherlands;King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
Venue:
Proceedings of the 12th international conference on Information processing in sensor networks
Year:
2013

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CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2

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Abstract

This article describes the implementation of four different machine learning techniques for vehicle classification in a dual ultrasonic/passive infrared traffic flow sensors. Using k-NN, Naive Bayes, SVM and KNN-SVM algorithms, we show that KNN-SVM significantly outperforms other algorithms in terms of classification accuracy. We also show that some of these algorithms could run in real time on the prototype system.