Takuma Kawamura

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This paper describes a level-of-detail rendering technique for large-scale irregular volume datasets. It is well known that the memory bandwidth consumed by visibility sorting becomes the limiting factor when carrying out volume rendering of such datasets. To develop a sorting-free volume rendering technique, we previously proposed a particle-based(More)
In this paper, we propose a novel transfer function design technique for multivariate volume rendering. This technique generates a multidimensional transfer function by logical synthesis of variables and transfer functions. This technique enables analysts to extract correlation of variables and to combine multivariate surface and volume shapes. And this(More)
The Petaflow project aims to contribute to the use of high performance computational resources to the benefit of society. To this goal the emergence of adequate information and communication technologies with respect to high performance computing-networking-visualisation and their mutual awareness is required. The developed technology and algorithms will be(More)
In this paper, we present a sorting-free technique for volume rendering of an irregular volume dataset. Although the importance of our particle-based volume rendering is widely recognized, its low image quality has been pointed out. Especially when the viewing point is located near the volume dataset, the footprint of the particle may be visible. To solve(More)
In this article, we propose a technique for improving the image quality of particle-based volume rendering (PBVR). A large-scale unstructured volume dataset often contains multiple sub-volumes, which cannot be ordered by visibility. PBVR can handle this type of volume dataset. Sampling misses often occur when the transfer function undergoes drastic changes,(More)
In this paper, we evaluate the quality of images which are generated by using our particle-based volume rendering (PBVR) technique. We develop a technique for generating an image which is equivalent to a volume ray-casting image in the PBVR. First, we calculate a particle density from a transfer function and a length of the ray segment, both of which are(More)
With the recent development of supercomputers, it is required to efficiently visualize the result of super-large scale numerical simulations on a few hundreds to a few ten thousands of parallel processes. Conventional offline-processing of visualization give rise to difficult challenges such as transferring large-scale data and reassembly of extensive(More)