淡江大學機構典藏:Item 987654321/111812
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    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/111812


    Title: Low-complexity range tree for video synopsis system
    Authors: Chih-Hsien Hsia;Jen-Shiun Chiang;Chi-Fang Hsieh
    Keywords: Object detection;Video retrieval system;Gaussian mixture model;Low-complexity range tree;Video synopsis system
    Date: 2016-08
    Issue Date: 2017-10-25 02:10:25 (UTC+8)
    Publisher: Springer US
    Abstract: This work proposes an efficient video retrieval technique for video synopsis. In a video system, the Region of Interest (ROI) should be extracted in a long video effectively such that users can browse it quickly and easily. Focusing on the characteristics of objects in the foreground of real-world video sequences, this work employs the Gaussian Mixture Model (GMM) and color-histograms for object detection. In order to reduce the search time, a new video synopsis search approach, a low-complexity range tree algorithm, is proposed to improve the effectiveness of searches for objects of interest matching pre-set conditions. With the time and space redundancy-reducing techniques of video synopsis, the objects of interest can be displayed within a short time. Objects and events can be found and displayed quickly without allocating time to watching non-ROIs. For the test video sequences, the results show an accuracy rate of 97 % and a processing speed of 32 FPS (frames per second) in the online phase, and the time complexity of object searching is reduced from O(N) to O(logD-1N).
    Relation: Multimedia Tools & Applications 75(16), p.9885-9902
    DOI: 10.1007/s11042-015-2714-2
    Appears in Collections:[Graduate Institute & Department of Electrical Engineering] Journal Article

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