Semi-Supervised Deep Vision-Based Localization Using Temporal Correlation between Consecutive Frames

Chu Tak Li, Wan Chi Siu, Daniel P.K. Lun

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)

Abstract

Vision-based localization is a temporal informative task in which we can obtain information about the ego-motion of a vehicle from the historical information via examining consecutive frames. Sufficient temporal information helps to reduce the search space of the next location. Hence, both efficiency and accuracy of the localization system can be enhanced. This paper presents a semi-supervised deep vision-based localization algorithm, using a novel tubing strategy to find the starting location of a vehicle. We group different number of consecutive frames as sets of tubes based on their temporal correlation to achieve pair searching with variable tube sizes. We also enhance an off-the-shelf network model with our modified training data generation method to improve the discrimination power of the features given by the model. Experimental results show that our proposed temporal correlation based initialization module can confidently localize the starting location of a vehicle (for a certain journey), and achieve 40% precision improvement over that of the conventional CNN approaches.

Original languageEnglish
Title of host publication2019 IEEE International Conference on Image Processing, ICIP 2019 - Proceedings
PublisherIEEE Computer Society
Pages1985-1989
Number of pages5
ISBN (Electronic)9781538662496
DOIs
Publication statusPublished - Sep 2019
Event26th IEEE International Conference on Image Processing, ICIP 2019 - Taipei, Taiwan
Duration: 22 Sep 201925 Sep 2019

Publication series

NameProceedings - International Conference on Image Processing, ICIP
Volume2019-September
ISSN (Print)1522-4880

Conference

Conference26th IEEE International Conference on Image Processing, ICIP 2019
Country/TerritoryTaiwan
CityTaipei
Period22/09/1925/09/19

Keywords

  • autonomous driving
  • deep learning
  • scene recognition
  • temporal correlation
  • Visual localization

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

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