研究生: |
李家欣 Chia-hsin Lee |
---|---|
論文名稱: |
多視點輔助定位系統 Positioning System with Multi-View Aiding |
指導教授: |
高維文
Wei-Wen Kao |
口試委員: |
陳亮光
none 張淑淨 Shwu-Jing CHANG |
學位類別: |
碩士 Master |
系所名稱: |
工程學院 - 機械工程系 Department of Mechanical Engineering |
論文出版年: | 2007 |
畢業學年度: | 95 |
語文別: | 中文 |
論文頁數: | 94 |
中文關鍵詞: | 多視點 、極線幾何 、特徵點 、定位 |
外文關鍵詞: | multi-view, Epipolar geometry, feature, location |
相關次數: | 點閱:310 下載:6 |
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現今的社會上,具有照相及GPS功能的手機日漸普及。當身處於一個陌生的城市時,使用個人導航的功能也不再是難事。但由於衛星訊號常受到地形的遮蔽,或是天候因素的影響。若同時身處於無法獲得城市中有建立資料的地標建築物的3D GIS資訊之處,則利用現有的手機照像功能,以視覺為基礎的定位導航,即成為最符合成本又不失精度的方法。
本論文利用投影幾何的方法,結合多視點的三維重建以及方位推估法累加的過程,建構出以視覺為基礎的路徑重建系統。本論文架構的系統僅需要一台消費型的數位像機,和運算用的電腦設備。在未知的環境下,透過取得所行經的路徑上之連續影像,便可以以SIFT演算法擷取出連續影像間的所對應的特徵點,並以LMedS演算法加以除錯。經由重建特徵點的三維座標,以計算兩兩取像位置間的相對位置變換,再經由方位推估法的累加兩兩影像間的路徑估測,逐步推估出所行經的路徑。
Mobile phones with Camera and GPS functions onboard are becoming popular day by day and personal navigation in a strange city is no longer a dream. However, in GPS-based systems, the satellite signal is often blocked in the urban areas or influenced of the weather and these limit the usages of the systems. Some other systems utilize existing cell-phone Camera function and 3D GIS landmark model of building to provide localization based on vision processing. However in places that lack the 3D GIS information such systems also have limitations. This research focus on vision-based navigation system that can be used to deal with above limitations and still provide desired accuracy and reliability.
The geometric projection method is combined with the three-dimension rebuilding method and Dead-Reckoning method to construct the route based on vision processing. The system only needs a consumer grade digital camera and a computer device for processing image data. A set of feature points shown in consecutive images that are taken on the route are picked and screened by using SIFT algorithm with LMEDS criteria under the unknown environment. Three-dimensional coordinate of the corresponding feature points are calculate to find the relative movements between the two images. Dead-Reckoning method can then be used to accumulate these relative movements by using a sequence of images that are taken on the routes and the passenger path can be deduced progressively.
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