A Pattern Recognition System for Detecting Use of Mobile Phones While Driving
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It is estimated that 80 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 use the image datasets for training classifiers in real situations. Periods of 3 seconds were correctly classified at 87.43
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