English  |  正體中文  |  简体中文  |  Items with full text/Total items : 52375/87459 (60%)
Visitors : 9156238      Online Users : 205
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: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/88146

    Title: 基於SURF之實體物件辨識及其應用
    Other Titles: SURF-based object recognition and its application
    Authors: 邱俊銘;Chiu, Chung-Ming
    Contributors: 淡江大學電機工程學系碩士班
    謝景棠;Hsieh, Ching-Tang
    Keywords: 加速強健特徵;Camshift演算法;擴增實境;無標誌;SURF;Camshift;Augmented Reality;Markerless
    Date: 2012
    Issue Date: 2013-04-13 12:02:51 (UTC+8)
    Abstract: 博物館一直以來都具有重要的地位,收藏有意義之歷史古蹟、文物、作品,隨著時代演變至今,多媒體影音媒體已成為資訊來源的另一起新秀,其在聲光影音部份都為過去平面書籍所無法提供,如須呈現動態3D、影音呈現的內容時,書籍依然受傳統印刷形式限制而無法呈現上述形式的資訊。因此本文以淡江大學海事博物館為例,期以達到多元的影音經驗與資訊。

    本論文以加速強健特徵(speeded-up robust features, SURF)為基礎,使用CamShift (Continuously Adaptive Mean Shift)對SURF 特徵區域做追蹤。SURF 是在尺度空間(scale space)中尋找穩定點,計算其主要方向,用於匹配特徵點的對齊,而後在鄰近區域內的Haar 小波響應當作紋理特徵進而對特徵點加以描述,因此可以克服物件辨識中影像的縮放大小、旋轉變化、光影變幻等干擾,再利用CamShift來追蹤使用者響導覽的物件,進而顯示擴增實境令使用者有不同的視覺感受.
    The museum has important status in all the time, collection of significant historical sites, artifacts, works with the changing times so far,but along with the time evolution, the multimedia has until now become the information to originate together is in addition beautiful, it all was unable in the acousto-optic video and music part for the past plane books to provide, when like had to present the content which dynamic 3D, the video and music presented, the books still received the traditional printing form to limit to are unable to present the above form the information.

    In this thesis, in order to accelerate the robust features (speeded-up robust features, SURF), based on use CamShift (Continuously Adaptive Mean Shift) SURF feature regions to follow them. SURF is to find a stable point in the scale space (scale space), to calculate the main direction of alignment for matching feature points, then the Haar wavelet response in the neighboring area and then the feature point described as the texture features, so you can overcome the interference of object recognition, image zoom size, rotate, changing light and shadow, re-use CamShift to track the user sound guide to the object, and then display the augmented reality users have different visual experience.
    Appears in Collections:[電機工程學系暨研究所] 學位論文

    Files in This Item:

    File SizeFormat

    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