NDLI: A pattern recognition system for detecting use of mobile phones while driving

Content Provider	IEEE Xplore Digital Library
Author	Berri, Rafael A. Silva, Alexandre G. Parpinelli, Rafael S. Girardi, Elaine Arthur, Rangel
Copyright Year	2014
Description	Author affiliation: College of Techological Science, Santa Catarina State University (UDESC), Joinville, Brazil (Berri, Rafael A.; Silva, Alexandre G.; Parpinelli, Rafael S.; Girardi, Elaine) \|\| Faculty of Technology, University of Campinas (Unicamp), Limeira, Brazil (Arthur, Rangel)
Abstract	It is estimated that 80% of crashes and 65% of near collisions involved drivers inattentive to traffic for three seconds before the event. This paper develops an algorithm for extracting characteristics allowing the cell phones identification used during driving a vehicle. Experiments were performed on sets of images with 100 positive images (with phone) and the other 100 negative images (no phone), containing frontal images of the driver. Support Vector Machine (SVM) with Polynomial kernel is the most advantageous classification system to the features provided by the algorithm, obtaining a success rate of 91.57% for the vision system. Tests done on videos show that it is possible to use the image datasets for training classifiers in real situations. Periods of 3 seconds were correctly classified at 87.43% of cases.
Starting Page	411
Ending Page	418
File Size	13067724
Page Count	8
File Format	PDF
ISBN	9789897581335
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-01-05
Publisher Place	Portugal
Access Restriction	Subscribed
Rights Holder	SCITEPRESS
Subject Keyword	Genetic Algorithm Cell Phones Machine Learning Support Vector Machines Driver Distraction Vehicles Videos Support vector machines Accuracy Cellular phones Skin Segmentation Mathematical model Computer Vision Kernel
Content Type	Text
Resource Type	Article

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