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2019 | OriginalPaper | Chapter

SVM and SSD for Classification of Mobility Actors on the Edge

Authors : Andrés Heredia, Gabriel Barros-Gavilanes

Published in: Applications of Computational Intelligence

Publisher: Springer International Publishing

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Abstract

In the context of video processing, transmission to a remote server is not always possible nor suitable. Video processing on the edge could offer a solution. However, lower processing capacities constraint the number of techniques available for devices, in this work we report the performance of two techniques for classification from video on a minicomputer. The implementation of a real-time vehicle counting and classification system is evaluated through Support Vector Machine (SVM) and the Single Shot Detector Framework (SSD) in a minicomputer. We compare two SVM bases techniques, IPHOG and a MBF using Scale Invariant Features. The obtained results show that with a video resolution of 1280 \(\times \) 720 pixels and using SVM, precision and recognition rates of 86% and 94% are obtained respectively, while with SSD 93% and 67% rates are reached with times of processing higher than SVM.

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Title: SVM and SSD for Classification of Mobility Actors on the Edge
Authors: Andrés Heredia
Gabriel Barros-Gavilanes
Publisher: Springer International Publishing
Book: Applications of Computational Intelligence
Print ISBN: 978-3-030-36210-2

Electronic ISBN: 978-3-030-36211-9

Copyright Year: 2019
DOI: https://doi.org/10.1007/978-3-030-36211-9_1

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