A fast vehicle detection method by UAV using region feature gradient

Lei Yan, Jiulu Gong, Derong Chen*, Suoqi Zhang

*Corresponding author for this work

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

6 Citations (Scopus)

Abstract

In order to detect ground vehicles from UAV in real time, a fast detection method using region feature gradient (RFG) was proposed. The RFG, which included the gradient mean amplitude and main directions, was used to find the potential position of target and its rotations rapidly. The gradient mean amplitude was first used to find the potential position of target, and the gradient integral image would make this process be computed very quickly. And the main directions of the target and potential position, which was computed by gradient histogram, were compared to find the rotation of the target. Finally, traditional recognition method (such as HOG) was adopted to accurately detect the target. Experimental results obtained against the VIVID database demonstrate that the proposed method is ten times faster than the improved method of HOG, and maintains a high recognition rate at the same time.

Original languageEnglish
Title of host publicationProceedings of 2017 IEEE International Conference on Unmanned Systems, ICUS 2017
EditorsXin Xu
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages384-388
Number of pages5
ISBN (Electronic)9781538631065
DOIs
Publication statusPublished - 2 Jul 2017
Event2017 IEEE International Conference on Unmanned Systems, ICUS 2017 - Beijing, China
Duration: 27 Oct 201729 Oct 2017

Publication series

NameProceedings of 2017 IEEE International Conference on Unmanned Systems, ICUS 2017
Volume2018-January

Conference

Conference2017 IEEE International Conference on Unmanned Systems, ICUS 2017
Country/TerritoryChina
CityBeijing
Period27/10/1729/10/17

Keywords

  • HOG
  • UAV images
  • gradient integral image
  • region feature gradient
  • vehicle detection

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