Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/77329
Title: Indoor localization with occlusion removal
Authors: Li, Y 
Baciu, G 
Han, Y 
Li, C 
Issue Date: 2017
Publisher: Institute of Electrical and Electronics Engineers Inc.
Source: Proceedings of 2017 IEEE 16th International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2017, 26-28 July 2017, 8109749, p. 191-198 How to cite?
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.
URI: http://hdl.handle.net/10397/77329
ISBN: 978-1-5386-0771-8 (electronic)
978-1-5386-0770-1 (CD-ROM)
978-1-5386-0772-5 (Print on Demand(PoD) )
DOI: 10.1109/ICCI-CC.2017.8109749
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