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New Ordering-Based Pruning Metrics for Ensembles of Classifiers in Imbalanced Datasets Read chapter Read first chapter

2016 | OriginalPaper | Chapter

Real-Time Eye Detection and Tracking in the Near-Infrared Video for Drivers’ Drowsiness Control

Author : Bogusław Cyganek

Published in: Proceedings of the 9th International Conference on Computer Recognition Systems CORES 2015

Publisher: Springer International Publishing

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Abstract

This paper presents a visual system for real-time eye detection and tracking in the near-infrared (NIR) video streams for drivers’ monitoring. The system starts with crude eye position estimation based on an eye model suitable for NIR processing. In the next step, eye regions are verified with the classifier operating in the higher-order decomposition of the tensor of eye prototypes. Finally, the process is augmented with the linear tracker which facilitates eye detection and allows real-time operation necessary in the automotive environment. The reported experiments show high accuracy and real-time operation of the system in the car.

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Metadata
Title
Real-Time Eye Detection and Tracking in the Near-Infrared Video for Drivers’ Drowsiness Control
Author
Bogusław Cyganek
Copyright Year
2016
Book
Proceedings of the 9th International Conference on Computer Recognition Systems CORES 2015

Print ISBN: 978-3-319-26225-3

Electronic ISBN: 978-3-319-26227-7

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-26227-7_45

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