標題: 利用攝影機校正、表面反投影以及二維模型比對技巧從單張影像中擷取物體形狀及表面資料作立體物辨認
RECOGNITION OF 3D OBJECTS BY SINGLE CAMERA VIEWS USING CAMERA CALIBRATION, SURFACE BACKPROJECTION, AND 2D MODEL MATCHING TECHNIQUES BASED ON OBJECT SHAPE AND SURFACE PATTERN INFORMATION
作者: 劉政雄
Liu, Cheng Hsiung
蔡文祥
Prof. Tsai, Wen Hsiang
資訊科學與工程研究所
關鍵字: 攝影機校正;表面反投影;二維模型比對;距離加權相關度;camera calibration; surface backprojection; 2D model matching; distance weighted correlation
公開日期: 1992
摘要: 本論文提出結合攝影機校正、表面反投影以及二維模型比對技巧從單張影 像中辨認三種不同立體物之新方法。三種不同之立體物包括在商品以及工 業元件中常見之長方體、圓柱體以及正角柱體。本論文不只利用物體之形 狀資料並利用了物體之表面資料來辨認物體。對每類物體,不同大小尺寸 或者不同表面資料之物體皆可加以辨認。要辨識待辨認物體,首先利用待 辨認物體之單張影像資料求出攝影機參數以及物體大小之公式解。此公式 解能比其他方法更快速求出攝影機參數。此攝影機校正技巧,基本上是利 用物體表面之直線或是曲線資料求得。而後利用表面反投影技巧將物體之 表面重建;此技巧將三度空間之表面資料轉換成一些二度空間之平面資料 ,如此使得接下去之模型比對得以在二度空間進行。最後,在模型比對步 驟中每一平面資料根據(DWC)從資料庫中找出最適當之模型,將此待 辨認之物體認定為此模型。實驗數據顯示此方法確實可行。 A new approach to recognition of three different classes of 3D objects by single camera views using a combination of camera calibration, surface backprojection, and 2D model matching techniques are proposed. The three classes of 3D objects are cuboids, cylinders, and regular prisms, which are commonly seen in commercial products and industrial parts. Not only the silhouette shape but also the surface pattern of the object are utilized in the recognition scheme. For each class, objects of both different sizes and different surface patterns can be recognized. To recognize an input object of each class, a new camera calibration technique is first employed to compute the camera parameters as well as the object dimension parameters analytically using a single camera view of the object. The availability of the analytical solutions of the camera parameters makes the proposed technique faster in parameter computation than other camera calibration approaches requiring iterative parameter computation processes. The calibration technique is based on the use of the information of the lines or curves formed by the intersections of the object surfaces. A surface backprojection technique is then adopted to reconstruct the pattern on each surface patch of the input object. This technique transforms the 3D surface data into a set of 2D surface patch patterns, which make the subsequent model matching process becomes 2D in nature. Finally, in the model matching process, each surface patch pattern is matched with those of each object model using the distance weighted correlation measure. Experimental results show the feasibility of the proposed approach.
URI: http://140.113.39.130/cdrfb3/record/nctu/#NT810392002
http://hdl.handle.net/11536/56728
Appears in Collections:Thesis