使用非線性輪廓套合演算法於基於CAD模型之三維物體姿態估測

CAD Model-based 3D Object Pose Estimation using a Nonlinear Contour Fitting Algorithm

王瑋毅(Wei-Yi Wang)

指導教授 ： 蔡奇謚

淡江大學/工學院/電機工程學系碩士班/碩士(2015年)

https://doi.org/10.6846/TKU.2015.01126

摘要

本論文提出了一個目標物的三維模型建置與視覺追蹤方法，可幫助機器人完成更困難的物體三維姿態估測和強健型物體追蹤。本論文所提出的方法分為兩部份:第一部分為提出一個三維電腦輔助設計(CAD)模型的建置方法，以協助後續的追蹤應用；第二部份為提出基於三維CAD模型的物體姿態估測方法，達到強健三維目標物追蹤的實現。本論文第一部份利用Micorsoft Kinect感測器來擷取物體的點雲資料，並找出物體的平面資訊。接著，利用平面幾何特性得到物體各頂點的資訊，即可將物體三維CAD模型建立出來。本論文第二部分則是將物體三維CAD模型投影在影像平面上的輪廓資訊進行物體追蹤應用，其透過目標物的影像輪廓資訊，利用三維CAD模型的投影輪廓結果計算兩者之間的最佳擬合的姿態，達到物體三維姿態估測及視覺追蹤的目的。

關鍵字

基於模型追蹤 ； 三維CAD模型重建 ； 建立多邊形模型

並列摘要

This thesis presents a three-dimensional (3D) model building method and a model-based visual tracking method for an object-of-interest. The proposed methods can help robots to accomplish more difficult tasks, such as 3D pose estimation and robust visual tracking of a rigid object. The contents of this thesis are divided into two parts. The first part presents the design of a 3D computer-aided design (CAD) model building algorithm, which produces a 3D CAD model of a geometrical object to facilitate the subsequent visual tracking task. The second part presents the design of a CAD-model based object pose estimation algorithm to implement the function of robust 3D object tracking. We first used Microsoft Kinect to capture the point cloud data of an object-of-interest for extracting its planar features. Then, its 3D CAD model was produced by vertex information of the object found by using geometrical characteristics of the object planar features. Next, a robust CAD-model based visual tracking method was implemented by fitting the contour of the projection of the 3D CAD model to the object contour on the image plane, which also can provide 3D pose information of the object during the visual tracking task.

並列關鍵字

model-based tracking ； 3D CAD model reconstruction ； build polygon model

參考文獻

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