No abstract

Abstract

No abstract

This paper presents an overview of our research project on digital preservation of cultural heritage objects and digital restoration of the original appearance of these objects. As an example of these objects, this project focuses on the preservation and restoration of the Great Buddhas. These are relatively large objects existing outdoors and providing various technical challenges. Geometric models of the great Buddhas are digitally achieved through a pipeline, consisting of acquiring data, aligning multiple range images, and merging these images. We have developed two alignment algorithms: a rapid simultaneous algorithm, based on graphics hardware, for quick data checking on site, and a parallel alignment algorithm, based on a PC cluster, for precise adjustment at the university. We have also designed a parallel voxel-based merging algorithm for connecting all aligned range images. On the geometric models created, we aligned texture images acquired from color cameras. We also developed two texture mapping methods. In an attempt to restore the original appearance of historical objects, we have synthesized several buildings and statues using scanned data and a literature survey with advice from experts.

In this paper, we propose an active scanning system using multiple projectors and cameras to acquire a dense entire shape of the object with a single scan (a.k.a. oneshot scan). One of the potential application of the system is to capture a moving object with high frame-rate. Since the pattern used for oneshot scan is usually complicated and those patterns interfere each other if they are projected on the same object, it is difficult to use multiple sets of them for entire shape acquisition. In addition, at the end of the closed loop, errors on each scan are accumulated, resulting in large gaps between shapes. To solve the problem, we propose a oneshot shape reconstruction method using a projector projecting a static pattern of parallel lines with one or two colors. Since each projector projects just parallel lines with a small number of colors, those patterns are easily decomposed and detected even if those patterns are projected multiple times on the same object. We also propose a kind of multi-view reconstruction algorithm for the proposed projector-camera system. In the experiment, we actually built a system which consists of six projectors and six cameras and dense shapes of entire objects were successfully reconstructed.

No abstract

No abstract

3D scanning of moving objects has many applications, for example, marker-less motion capture, analysis on fluid dynamics, object explosion and so on. One of the approach to acquire accurate shape is a projector-camera system, es pecially the methods that reconstructs a shape by using a single image with static pattern is suitable for capturing fast moving object. In this paper, we propose a method that uses a grid pattern consisting of sets of parallel lines. The pattern is spatially encoded by a periodic color pat tern. While informations are sparse in the camera image, the proposed method extracts the dense (pixel-wise) phase informations from the sparse pattern. As the resuit, con tinuous regions in the camera images can be extracted by analyzing the phase. Since there remain one DOF for each region, we propose the linear solution to eliminate the DOF by using geometric informations of the devices, i.e. epipo lar constraint. In addition, solution space is .finite because projected pattern consists of parallel lines with same inter vals, the linear equation can be efficiently solved by integer least square method. In this paper, the formulations for both single and multiple projectors are presented. We evaluated the accuracy of correspondences and showed the compari son with respect to the number of projectors by simulation. Finally, the dense 3D reconstruction of moving objects are presented in the experiments.