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dc.contributor.authorWu, Bing-Feien_US
dc.contributor.authorJen, Cheng-Lungen_US
dc.contributor.authorTsou, Tai-Yuen_US
dc.contributor.authorChen, Po-Yenen_US
dc.date.accessioned2017-04-21T06:48:53Z-
dc.date.available2017-04-21T06:48:53Z-
dc.date.issued2014en_US
dc.identifier.isbn978-1-4799-3840-7en_US
dc.identifier.issn1062-922Xen_US
dc.identifier.urihttp://hdl.handle.net/11536/135001-
dc.description.abstractRecently, several robotic wheelchairs have been proposed that employ autonomous functions. In designing wheelchairs, it is important to reduce the accompanist load. To provide such a task, the mobile robot needs to recognize and track people. In this paper, we propose to utilize the multisensory data fusion to track a target accompanist. First, the simultaneous localization and map building is achieved by using the laser range finder (LRF) and inertial sensors with the extended Kalman filter recursively. To track the target person robustly, the accompanist, are tracked by fusing laser and vision data. The human objects are detected by LRF, and the identity of accompanist is recognized using a PTZ camera with a pre-defined signature using the speed-up robust features algorithm. The proposed system can adaptively search visual signature and track the accompanist by dynamically zooming the PTZ camera based on LRF detection results to enlarge the range of human following. The experimental results verified and demonstrated the performance of the proposed system.en_US
dc.language.isoen_USen_US
dc.subjectSLAMen_US
dc.subjectExtended Kalman filteren_US
dc.subjectLaser range finderen_US
dc.subjectPan-Tilt-Zoom (PTZ) Cameraen_US
dc.titleAccompanist Recognition and Tracking for Intelligent Wheelchairsen_US
dc.typeProceedings Paperen_US
dc.identifier.journal2014 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS (SMC)en_US
dc.citation.spage2138en_US
dc.citation.epage2143en_US
dc.contributor.department電控工程研究所zh_TW
dc.contributor.departmentInstitute of Electrical and Control Engineeringen_US
dc.identifier.wosnumberWOS:000370963702043en_US
dc.citation.woscount1en_US
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