3D reconstruction of transparent and specular objects is a very challenging topic in computer vision. The goal is to get the 3D information of the points on the surface of a transparent or specular object and accumulate the points to form the reconstructed surface. For opaque objects, the structured light methods can be used with good results. For transparent and specular objects, which have complex interior and exterior structures that can reflect and refract light in a complex fashion, it is difficult, if not impossible, to use the traditional structured light methods to do the reconstruction.;In this thesis, a frequency-based 3D reconstruction method based on the frequency-based matting method is introduced. Similar to the structured light methods, a set of frequency-based patterns are projected to the object, and a camera captures the scene at the same time. Each pixel of a captured image is analyzed along the time axis and the signal is transformed to the frequency-domain using the Discrete Fourier Transformation. Since the frequency is only determined by the source that creates it, the frequency of the signal can uniquely identify the location of the pixel in the patterns. In this way, the correspondences between the pixels in the captured images and the points in the patterns can be acquired. Using a new labelling procedure developed in this research, the surface of transparent and specular objects can be reconstructed with very encouraging results.
展开▼
