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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/78998


    Title: Moving Object Detection Using Monocular Vision
    Authors: Wang, Yin-tien;Chen, Kuo-wei;Chiou, Ming-jang
    Contributors: 淡江大學機械與機電工程學系
    Keywords: Moving object detection;simultaneous localization and mapping;speeded-up robust features;monocular vision
    Date: 2012-06-26
    Issue Date: 2012-11-17 12:33:06 (UTC+8)
    Publisher: Springer
    Abstract: This paper presents an algorithm for moving object detection (MOD) in robot visual simultaneous localization and mapping (SLAM). The algorithm is designed based on the defining epipolar constraint for the corresponding feature points on image plane. An essential matrix obtained using the state estimator is utilized to represent the pipolar constraint. Meanwhile, 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 and of moving objects in visual SLAM system. Experiment is carried out on a hand-held monocular camera to validate the performances of the proposed algorithm. The results show that the integration of MOD and SURF is efficient for
    robot navigating in dynamic environments.
    Relation: Intelligent Autonomous Systems 12: Proceedings of the 12th International Conference, pp.183-192
    DOI: 10.1007/978-3-642-33926-4_17
    Appears in Collections:[機械與機電工程學系暨研究所] 會議論文

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