Limited-Anchor Deep Neural Network for Moving Object Detection

Chih Yang Lin, Han Yi Huang, Wei Yang Lin, Chuan Yu Chang, Wen Thong Chang, Yih Kuen Jan

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

Abstract

This paper proposes a new method that integrates a deep learning based object detection network into traditional background modeling to detect moving objects. The proposed method allows us to efficiently identify candidates that contain moving objects while only setting a small number of anchors in the moving area of the image through guidance from the traditional background modeling method. This paper overcomes the disadvantages of conventional background modeling methods and conventional deep learning based object detection methods in terms of dynamic backgrounds and objects' motion states.

Original languageEnglish
Title of host publication2020 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728173993
DOIs
StatePublished - 28 Sep 2020
Event7th IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020 - Taoyuan, Taiwan
Duration: 28 Sep 202030 Sep 2020

Publication series

Name2020 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020

Conference

Conference7th IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2020
Country/TerritoryTaiwan
CityTaoyuan
Period28/09/2030/09/20

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