Enhancing 3D Scene Models Based on Automatic Context Analysis and Optimization Algorithm

Abstract

AbstractThis paper proposes a method for enhancing accuracy of scene model. The main contributions are threefold: first, the contex of the scene images are analyzed. Some objects which may have negative effect should be removed. For instance, the sky often appears as backgroud and moving objects appear in most of scene images. They are also one of reasons that causes the outliers. Second, the global rotations of images are computed based on correspondence between pair-wise images. These constraints are fed to the point clouds generation procedure. Third, in contrast with using only canonical bundle adjustment which yields unstable structure in small baseline geometry and local minima, the proposed method utilized known-rotation framework to compute the initial guess for bundle adjustment process. The patch-based multi-view stereopsis is applied to upgrade the reconstructed structure. The simulation results demonstrate the accuracy of structures by this method from scene images in outdoor environment.Keywordscontext analysisSIFTcorrespondenceRANSACglobal rotation estimationconvex optimizationPMVS