以PTZ相機與移動鏡球之三維場景重建系統

Abstract

以二維影像重建三維場景，在機器人學與電腦視覺中有許多的應用，例如：機器人導航技術、三維物件辨識……等。其中，寬廣的視角對於此項技術是十分必要的。然而，通常一般相機所能提供的視角有限，因此，在此篇論文中，我們利用可旋轉式攝影機（Pan-Tilt-Zoom camera）與鏡球結合可增加視角的特性，來實現三維場景重建，並且進而考慮環境%@A%垺不確定性。移動鏡球偵側與定位的不確定性，我們以大量樣本（sample）來表示，之後，結合兩張不同影像之樣本，來獲取特徵點位置資訊。而我們以高斯分佈表示每一個特徵點位置，並利用卡爾曼濾波器（Kalman filter）作更新。實驗結果驗證了此方法的可行性。

Three-dimensional scene reconstruction from 2D images can serve as a foundation for solving a number of robotics and computer vision problems such as robot navigation and 3D object recognition in which covering a large field of view could be critical. As conventional cameras have limited fields of view, we propose an approach to reconstruct large 3D scene models using a combination of a pan-tilt-zoom (PTZ) camera and a moving spherical mirror. The proposed system provides uncertainty estimates of the scene model. The uncertainty of moving spherical mirror detection and localization is represented using samples. Two images are used to compute a location measurement of a 3D point in the scene in which the combinations of the sample sets of the two mirror locations are exploited and location measurements of 3D points are represented using Gaussian distributions. Localization of 3D points in the scene is done using a Kalman filter. The experimental results demonstrate the feasibility of the proposed system.