大規模観測対象のための幾何形状および光学情報統合システム

In this paper, we consider the geometric and photometric modeling of large-scale and intricately shaped objects, such as cultural heritage objects. When modeling a large-scale and intricately shaped object, a huge amount of data is required to model the object. We would like to propose two approaches to handling this amount of data : the parallel processing of merging range images and the adaptive algorithm of merging range images. First, we developed a parallel computation algorithm using a PC cluster which consists of two components, the distributed allocation of range images to multiple PCs, and the parallel traversal of sub-trees of octree. Second, we constructed a merged model in adaptive resolution according to the geometric and photometric attributes of range images for efficient use of computational resources. Moreover, we propose a novel method to construct a 3D model with an appearance by taking a consensus of the appearance changes of the target object from multiple range images.