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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/106682


    Title: Real-Time Automatic Target Selection and Tracking Algorithm Using Keypoint-Based Template Matching
    Authors: Tsai, Chi-Yi;Yu, Cheng-Jui
    Keywords: Keypoint extraction;object detection;mean shift clustering;template matching;visual tracking
    Date: 2015/09/05
    Issue Date: 2016-04-27 11:20:54 (UTC+8)
    Publisher: IIAE
    Abstract: Object detection and tracking is an important function that helps bringing robots into real-world environments. Detection of an object-of-interest (OOI) from multiple stacking objects still holds certain degree of difficulty. In this paper, a novel target selection and tracking algorithm is proposed for detecting and tracking one OOI from multiple stacking objects. The proposed method first employs a keypoint extraction algorithm to compute control points from incoming images. Next, each OOI appeared in the image is extracted from the multiple stacking objects in a box by using mean shift clustering approach. Finally, a template-based visual tracking method is adopted to locate and track center position of the top OOI in the box. The proposed algorithm had been implemented on an Intel Core i5-4440 3.1GHz platform, achieving real-time performance about 30 frames per second at 640x480 image resolution in the experiments.
    Relation: Proceedings of the 3rd IIAE International Conference on Intelligent Systems and Image Processing 2015, pp.187-190
    DOI: 10.12792/icisip2015.036
    Appears in Collections:[電機工程學系暨研究所] 會議論文

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