Vision-based moving objects detection for intelligent automobiles and a robustness enhancing method

Ting Fung Ju*, Wei Min Lu, Kuan Hung Chen, Jiun-In  Guo

*Corresponding author for this work

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

5 Scopus citations

Abstract

This paper presents a vision-based moving objects detection work which attracts much attention in intelligent automobile applications recently. Vision-based objects detection provides object behavior information of objects and is an intuitive detection method similar to human visual perception. Besides, vision-based objects detection methods are much low-cost compared with detection methods such as RADAR (Radio Detection And Ranging), or LiDAR (Light Detection And Ranging). However, current vision-based objects detection methods still suffer from several challenges such as high false alarms and unstable detection rate which limit their value in practical applications. Accordingly, this paper presents a robustness enhancing method for vision-based moving objects detection.

Original languageEnglish
Title of host publicationDigest of Technical Papers - IEEE International Conference on Consumer Electronics
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages75-76
Number of pages2
ISBN (Electronic)9781479938308
DOIs
StatePublished - 18 Sep 2014
Event1st IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2014 - Taipei, Taiwan
Duration: 26 May 201428 May 2014

Publication series

NameDigest of Technical Papers - IEEE International Conference on Consumer Electronics
ISSN (Print)0747-668X

Conference

Conference1st IEEE International Conference on Consumer Electronics - Taiwan, ICCE-TW 2014
CountryTaiwan
CityTaipei
Period26/05/1428/05/14

Keywords

  • intelligent automobile
  • intelligent vision
  • object detection
  • pedestrian detection

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