Study On 3D Digitization Based On Structured Light And NRSFM

3D digital reconstruction technology of rigid-object and non-rigid object has important practical value in the aspects of military, artificial intelligence research, historical relics. Therefore, this paper does some research on 3D reconstruction of the rigid and non-rigid objects. Because many objects in daily life are no texture or weak texture, so their 3D reconstruction is very difficult. This paper uses the method of binocular vision and structured light to do the static object reconstruction, put forward using a projector instead of the traditional camera in the reconstruction and obtained very good results. For the 3D reconstruction of non-rigid objects, this paper uses the non-rigid structure from motion(Non-rigid structure from motion, NRSFM) method. This paper does some research of 3D digital reconstruction. The work can be summarized as follows:(1) Using the technology of binocular vision and gray code to reconstruct objects’ 3D structure of all aspects. By comparing the reconstruction results with the real object, we know that the experiment is good.(2) This paper uses a projector instead of one camera in traditional binocular vision model, then calibrating the camera and the projector. Finally, realizes the reconstruction of the static objects with a single camera, a projector and gray code technology. The experimental results show that, this method has a good effect for the 3D reconstruction of static object.(3) The current method of recovering objects’ structure from motion is mainly based on the existing data set, and in this paper we collected a data set using the optical flow, and reconstructed the non-rigid objects in the space of shape and in the space of trajectory with the factorization method.Experimental results show that the gray code method can recover the 3D shape of static object. But it is not effective for dead angle of measurement. While the NRSFM method using the factorization method and trajectory method can be used for non-rigid 3D digitization. But three-dimensional point obtained by this method is still not populated, so we still should do some more research on this study.