English  |  正體中文  |  简体中文  |  Items with full text/Total items : 62637/95499 (66%)
Visitors : 3036215      Online Users : 373
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/93529

    Title: Real-Time Feature Descriptor Matching via a Multi-Resolution Exhaustive Search Method
    Authors: Tsai, Chi-Yi;Tsao, An-Hung;Wang, Chuan-Wei
    Contributors: 淡江大學電機工程學系
    Keywords: descriptor matching;linear exhaustive search;L1 norm pyramid;multi-resolution examination
    Date: 2013-09
    Issue Date: 2014-01-21 15:12:11 (UTC+8)
    Publisher: Tortola: Academy Publisher
    Abstract: Feature descriptor matching plays an important role in many computer vision applications. This paper presents a novel fast linear exhaustive search algorithm combined with a multi-resolution candidate elimination technique to deal with this problem efficiently. The proposed algorithm is inspired from the existing multi-resolution image retrieval approaches, but releasing the requirement on a norm-sorted database with pre-computed multi-resolution tables. This helps to increase the applicability of the proposed method. Moreover, the computations of candidate elimination are fully performed using a simple L1 distance metric, which is able to speedup the entire search process without loss of accuracy. This property leads to an accurate feature descriptor matching algorithm with real-time performance, which will be validated in the experiments by testing with the matching of SURF descriptors.
    Relation: Journal of Software 8(9), pp.2197-2201
    DOI: 10.4304/jsw.8.9.2197-2201
    Appears in Collections:[Graduate Institute & Department of Electrical Engineering] Journal Article

    Files in This Item:

    File Description SizeFormat
    T048author__Biographies.pdf論文678KbAdobe PDF394View/Open

    All items in 機構典藏 are protected by copyright, with all rights reserved.

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - Feedback