3D scene reconstruction enhancement method based on automatic context analysis and convex optimization

Abstract

This paper proposes a method for increasing accuracy of the scene model generation. Reconstruction of 3D scene model is strongly affected by moving objects both artificial and natural. In the proposed method context analysis is applied as a pre-filtering operation used to detect and remove objects which could negatively affect reconstruction process. Additionally, robust global rotation constraints are computed based on correspondence of image pairs. These constraints are fed to the model generation procedure. Finally, in contrast with using only canonical bundle adjustment which yields unstable structure in critical configuration and local minima, the proposed method utilized known-rotation frame work to compute the initial guess for bundle adjustment process which overcomes the drawback above. Moreover, the patch-based multi-view stereopsis is applied to upgrade the reconstructed structure. The simulation results demonstrate the tidy of structures reconstructed by this method from scene images in outdoor environment.