A Novel 3D Reconstruction Approach from Uncalibrated Multiple Views Based on Homography

Abstract

In this paper, we focus on a kind of 3D object shape reconstruction from images and put forward a metric approach to recover the object based on slicing planes by homography transformation and image consistency between multiple images. This approach done here eliminates the requirement for camera calibration, the estimation of the fundamental matrix, feature matches and pose estimation. We adopt a set of hypothetical planes to intersect the reconstructed object to obtain every slicing plane of the reconstructed object by homography transformation and recover it to 3D adding vanishing points by the constraints of silhouette and the scene. The experiment shows that the approach is much validated, and something useful is obtained. topological changes of 2D curves, we adopt a physically-based 2D level set model to animate the evolution and propagation of the interface. We build a level set equation to model the evolution of the interface. In addition, to handle the large scale virtual environment correctly in our physically-based level set model, an image-based 2D voxelization method is proposed in the paper. In the voxelization method, the virtual environment will be converted to boundary conditions when solving the level set equation. Finally, the water pollutants diffusion phenomenon is simulated on large scale water surface by merging the interface animation results as well as the large scale virtual environment. Animation results about the algae propagation phenomenon in Taihu Lake show that our method is intuitively to be implemented and very convenient to produce visually interesting results.