Ryoichi Ando

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We introduce a new method for efficiently simulating liquid with extreme amounts of spatial adaptivity. Our method combines several key components to drastically speed up the simulation of large-scale fluid phenomena: We leverage an alternative Eulerian tetrahedral mesh discretization to significantly reduce the complexity of the pressure solve while(More)
We present a new particle-based method that explicitly preserves thin fluid sheets for animating liquids. Our primary contribution is a meshless particle-based framework that splits at thin points and collapses at dense points to prevent the breakup of liquid. In contrast to existing surface tracking methods, the proposed framework does not suffer from(More)
This paper presents a particle-based model for preserving fluid sheets of animated liquids with an adaptively sampled Fluid-Implicit-Particle (FLIP) method. In our method, we preserve fluid sheets by filling the breaking sheets with particle splitting in the thin regions, and by collapsing them in the deep water. To identify the critically thin parts, we(More)
We propose a robust scene recognition system for baseball broadcast videos. This system is based on the data-driven approach which has been successful in continuous speech recognition. It uses a multi-stream hidden Markov model to model each scene and an unsupervised adaptation method to achieve robustness against differences in environmental conditions(More)
BACKGROUND Abdominal aortic calcification is a common complication and a predictor of cardiovascular mortality in dialysis patients. However, abdominal aortic calcification in pre-dialysis chronic kidney disease (CKD) is poorly understood. METHODS A cohort study of 101 adult Japanese patients (mean age 66.6 +/- 11.3 years old) with pre-dialysis CKD (18,(More)
We propose a robust scene recognition framework using scene context information for multimedia contents. Multimedia contents con-sist of scene sequences that are more likely to happen compared with other scene sequences. We employ a statistical approach to deal with this scene context information. We employ a hidden Markov model (HMM) to model each scene(More)
This paper presents a liquid simulation technique that enforces the incompressibility condition using a stream function solve instead of a pressure projection. Previous methods have used stream function techniques for the simulation of detailed single-phase flows, but a formulation for liquid simulation has proved elusive in part due to the free surface(More)