研究生: |
吳加山 Jia-Shan Wu |
---|---|
論文名稱: |
使用尺度不變性特徵轉換與立體視覺之即時三維物體識別 Real-time 3-D Object Recognition by Using Scale Invariant Feature Transform and Stereo Vision |
指導教授: |
林其禹
Chyi-Yeu Lin |
口試委員: |
徐繼聖
G.S. Hsu 鍾國亮 Kuo-Liang Chung |
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: | 2008 |
畢業學年度: | 96 |
語文別: | 中文 |
論文頁數: | 65 |
中文關鍵詞: | 尺度不變性特徵轉換 、顯示卡 、對應矩陣 、不同平面旋轉角度 、立體視覺 、三維物體識別 、旋轉不變性 、機械手臂 |
外文關鍵詞: | Scale Invariant Feature Transform, GPU, homography, out-plane orientations, stereo vision, 3-D object recognition, rotation-invariant, robot arm |
相關次數: | 點閱:372 下載:1 |
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在電腦視覺的領域中,三維物體的辨識與立體視覺是一項重要的工作。在本論文中,我們使用尺度不變性特徵轉換(Scale Invariant Feature Transform, SIFT)來尋找三維物體的特徵,並利用顯示卡運算能力來達成即時運算能力。由於SIFT特徵本身良好的旋轉不變性、尺度不變性(scale-invariance)和抵抗背景雜訊的特性,我們的偵測器便可以達到旋轉不變性,並可以讓物體以不同大小出現時都能被偵測,因為每個物體都有其獨特的特徵,所以我們利用每個物體獨特的特徵來辨識物體,並利用對應矩陣來計算不同平面的旋轉角度。在本論文中,除了利用SIFT方法來即時辨識三維物體外,還加入了立體視覺原理來判斷三維物體與攝影機的距離,並利用物體的位置、不同平面角度與深度資訊來控制機械手臂指出物體。
3-D object recognition and stereo vision are important tasks in computer vision. In this thesis, we use Scale Invariant Feature Transform (SIFT) to search 3-D object features and use GPU to perform the real-time capability. Since SIFT has rotation-invariant, and scale-invariant characteristics, and can handle complex backgrounds, our detector can detect objects of different sizes based on its own unique feature. The corresponding homography is used to calculate the out-plane orientations. In this thesis, we implement the SIFT algorithm to recognize the 3-D objects and also use the stereo vision theorem to determine the distance form the cameras to the object. A robot arm is controlled to point to the object based on the orientations, and depth information of the object.
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