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Erschienen in:
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2020 | OriginalPaper | Buchkapitel

A Novel Multiple Object Tracking Algorithm for Autonomous Vehicles

verfasst von : Hai Deng, Ming Gao, Li-sheng Jin, Bai-cang Guo

Erschienen in: Green, Smart and Connected Transportation Systems

Verlag: Springer Singapore

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Abstract

Multiple object tracking is a vital task for autonomous vehicle environment perception. In this paper, we design a novel multi-object tracking method for autonomous vehicles. In the detection section, we utilize popular Faster-RCNN as our baseline method. Then, in data association, we combine appearance, motion, and interaction model to build a unified feature descriptor to explore the nature of tracking object. We evaluate our algorithm on a popular and standard benchmark and compare with the state-of-the-art methods. The results denote that our algorithm achieve good performance at high frame rates.

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Metadaten
Titel
A Novel Multiple Object Tracking Algorithm for Autonomous Vehicles
verfasst von
Hai Deng
Ming Gao
Li-sheng Jin
Bai-cang Guo
Copyright-Jahr
2020
Verlag
Springer Singapore
Buch
Green, Smart and Connected Transportation Systems

Print ISBN: 978-981-15-0643-7

Electronic ISBN: 978-981-15-0644-4

Copyright-Jahr: 2020

DOI
https://doi.org/10.1007/978-981-15-0644-4_65

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