TY - GEN
T1 - Indoor localization with occlusion removal
AU - Li, Yushi
AU - Baciu, George
AU - Han, Yu
AU - Li, Chenhui
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/11/14
Y1 - 2017/11/14
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85040607418&partnerID=8YFLogxK
U2 - 10.1109/ICCI-CC.2017.8109749
DO - 10.1109/ICCI-CC.2017.8109749
M3 - Conference Proceeding
AN - SCOPUS:85040607418
T3 - Proceedings of 2017 IEEE 16th International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2017
SP - 191
EP - 198
BT - Proceedings of 2017 IEEE 16th International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2017
A2 - Wang, Yingxu
A2 - Hamdy, Freddie
A2 - Howard, Newton
A2 - Zadeh, Lotfi A.
A2 - Hussain, Amir
A2 - Widrow, Bernard
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 16th IEEE International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2017
Y2 - 26 July 2017 through 28 July 2017
ER -