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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/58125


    Title: Detection and Tracking of Moving Objects in SLAM using Vision Sensors
    Authors: Wang, Yin-tien;Feng, Ying-chieh;Hung, Duen-yan
    Contributors: 淡江大學機械與機電工程學系
    Keywords: Simultaneous Localization and Mapping;SLAM;Speeded Up Robust Features;SURF;Moving Object Detection;MOD;Vision Sensor
    Date: 2011-05-10
    Issue Date: 2011-09-29 14:58:51 (UTC+8)
    Publisher: IEEE
    Abstract: This paper presents algorithms for improving the detection of moving objects in robot visual simultaneous localization and mapping (SLAM). The method of speeded-up robust feature (SURF) is employed in the algorithm to provide a robust detection for image features as well as a better description of landmarks in the map of a visual SLAM system. Meanwhile, a moving object detection (MOD) is designed based on the correspondence constraint of the essential matrix for the feature points on image plane. Experiments are carried out on a hand-held camera sensor to verify the performances of the proposed algorithms. The results show that the integration of SURF and MOD is efficient to improve the robustness of robot SLAM.
    Relation: Instrumentation and Measurement Technology Conference (I2MTC), 2011 IEEE, pp.1-5
    DOI: 10.1109/IMTC.2011.5944059
    Appears in Collections:[機械與機電工程學系暨研究所] 會議論文

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