3D model reconstruction based on multiple view image capture

In this paper, a system is designed for three-dimensional model reconstruction. The proposed system uses a camera to take multiple images from the object and analyze those images using structure from motion (SFM) to obtain the camera parameters and sparse point clouds. Therefore, this system can work without any camera calibration prior to the experiments. In order to reconstruct the target object, the patch-based multi-view stereo is used to capture two target postures and compute the three-dimensional point clouds and color information from the target object. Then use the iterative closest point algorithm to register those two target postures. In the last step, the Poisson surfaces reconstruction technique is used to build the three-dimensional mesh model. Finally, the experimental results show that the study acquires proper practicability and robustness.