動態場景光束法平差

Abstract

本論文提出一項應用於動態環境下之光線束法平差演算法。根據一個或多個相機的影像，本演算法可重建相機的3D軌跡，以及環境中之靜態與動態物體的3D位置。我們提出一個高效率的低維度表示形式，藉此描述物體與攝影機的軌跡。每一物體的軌跡由一系列基軌跡的線性組合近似而成。我們提出的方法不須倚賴任何對於物體移動方式的事前了解，甚至不須知道物體為靜止與否。同時，與其他方法不同的是，我們可以處理不完全，並具有雜訊的資料。經由模擬與實際測試驗證，本文提出的方法可以有效重建物體與相機的3D軌跡。

This work proposes an extension of Bundle Adjustment to dynamic scenes. In the setting of one or multiple cameras moving in a dynamic environment, the camera pose and the 3D positions of static and moving objects are reconstructed from the captured image sequences. An efficient, low- dimensional representation of the scene is introduced, which is based on approximating trajectories by linear combinations of trajectory bases. Our reconstruction approach requires no knowledge about the objects, not even which are moving or static and is, in difference to other approaches, able to deal with incomplete and noisy data. Experimental evaluation in simulation as well as with real data shows its effectiveness in reconstructing dynamic scenes from moving cameras.