KAZE-BOF-based large vehicles detection at night

Yong Sheng Chen, Jong Chih Chien, Jiann Der Lee*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

Instead of a high-priced radar system, this paper proposes a camera-based system to detect large vehicles at night. Recognition rate is improved using KAZE-based Bag-of-Features component in the system. In our current setup, ROI are extracted from nighttime-driving videos using rear-lights detection, then a LBP-based Adaboost detector is used to detect the locations of large vehicles, finally the KAZE-based BOF classifier is used to improve classification accuracy. Preliminary experimental results shows that this idea is feasible and can help enhance the driver's safety while driving at night.

Original languageEnglish
Title of host publication2016 International Conference on Communication Problem-Solving, ICCP 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509013838
DOIs
StatePublished - 21 11 2016
Event2016 International Conference on Communication Problem-Solving, ICCP 2016 - Taipei, Taiwan
Duration: 07 09 201609 09 2016

Publication series

Name2016 International Conference on Communication Problem-Solving, ICCP 2016

Conference

Conference2016 International Conference on Communication Problem-Solving, ICCP 2016
Country/TerritoryTaiwan
CityTaipei
Period07/09/1609/09/16

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

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