Indoor localization with occlusion removal

Yushi Li, George Baciu, Yu Han, Chenhui Li

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

1 Citation (Scopus)

Abstract

A novel 3D image-based indoor localization system integrated with an obstacle removal component is proposed. In contrast with existing state-of-the-art localization techniques focusing on static outdoor or indoor environments, the adverse effects generated by moving obstacles, which are very common in busy indoor spaces, is considered in our work. In particular, this problem is converted into a separation of moving foreground and static background. We use a low-rank and sparse matrix decomposition approach to solve this problem efficiently. Our system has been tested on data sets established to emphasize the dynamic situations caused by deforming obstructions appearing in front of a static background scene that may contain useful features for localization. We demonstrate that the localization effectiveness is increased significantly after removing the dynamic occluding objects. The performance of our system is evaluated based on quantitative experimental results.
Original languageEnglish
Title of host publicationProceedings of 2017 IEEE 16th International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2017
PublisherIEEE
Pages191-198
Number of pages8
ISBN (Electronic)9781538607701
DOIs
Publication statusPublished - 14 Nov 2017
Event16th IEEE International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2017 - University of Oxford, Oxford, United Kingdom
Duration: 26 Jul 201728 Jul 2017

Conference

Conference16th IEEE International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2017
CountryUnited Kingdom
CityOxford
Period26/07/1728/07/17

ASJC Scopus subject areas

  • Cognitive Neuroscience
  • Information Systems
  • Computer Science (miscellaneous)

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