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Performance Evaluation of CNN Based Pedestrian and Cyclist Detectors On Degraded Images
Tomáš Zemcík, Lukáš Kratochvíla, Šimon Bilík, Ondrej Boštík, Pavel Zemcík, Karel Horák
Pages - 1 - 13 | Revised - 31-01-2021 | Published - 28-02-2021
Published in International Journal of Image Processing (IJIP)
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KEYWORDS
Object Detection, Image Degradation, Pedestrian Detection, Cyclist Detection, SSD, Faster R-CNN.
ABSTRACT
This paper evaluates the effects of input image degradation on performance of image object detectors. The purpose of the evaluation is to determine usability of the detectors trained on original images in adverse conditions. SSD and Faster R-CNN based pedestrian and cyclist detector performance with images degraded with motion blur, out-of-focus blur, and JPEG compression artefacts, most commonly occurring in mobile or static traffic systems. An experiment was designed to assess the effect of degradations on detection precision and cross class confusion. The paper describes the two datasets created for this evaluation, evaluation of a number of detectors on increasingly more degraded images, comparison of their performance, and assessment of their tolerance to different types of image degradation as well as a discussion of the results.
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Mr. Tomáš Zemcík
Faculty of Electrical Engineering and Communications, Dept. of Automation and Instrumentation, Brno University of Technology, Brno - Czech Republic
xzemci04@stud.feec.vutbr.cz
Mr. Lukáš Kratochvíla
Faculty of Electrical Engineering and Communications, Dept. of Automation and Instrumentation, Brno University of Technology, Brno - Czech Republic
Mr. Šimon Bilík
Faculty of Electrical Engineering and Communications, Dept. of Automation and Instrumentation, Brno University of Technology, Brno - Czech Republic
Mr. Ondrej Boštík
Faculty of Electrical Engineering and Communications, Dept. of Automation and Instrumentation, Brno University of Technology, Brno - Czech Republic
Professor Pavel Zemcík
Faculty of Information Technology, Dept. of Computer Graphics and Multimedia, Brno University of Technology, Brno - Czech Republic
Dr. Karel Horák
Faculty of Electrical Engineering and Communications, Dept. of Automation and Instrumentation, Brno University of Technology, Brno - Czech Republic
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