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We introduce Group Motion Graphs, a data-driven animation technique for groups of discrete agents, such as flocks, herds, or small crowds. Group Motion Graphs are conceptually similar to motion graphs constructed from motion-capture data, but have some important differences: we assume simulated motion; transition nodes are found by clustering group(More)
Finite element method (FEM) analysis has become a common method to analyze the lesion formation during temperature-controlled radiofrequency (RF) cardiac ablation. We present a process of FEM modeling a system including blood, myocardium, and an ablation catheter with a thermistor embedded at the tip. The simulation used a simple proportional-integral (PI)(More)
Manga are a popular artistic form around the world, and artists use simple line drawing and screentone to create all kinds of interesting productions. Vectorization is helpful to digitally reproduce these elements for proper content and intention delivery on electronic devices. Therefore, this study aims at transforming scanned Manga to a vector(More)
We present Metropolis Photon Sampling (MPS), a visual importance-driven algorithm for populating photon maps. Photon Mapping and other particle tracing algorithms fail if the photons are poorly distributed. Our approach samples light transport paths that join a light to the eye, which accounts for the viewer in the sampling process and provides information(More)
This work presents a novel global illumination algorithm which concentrates computation on important light transport paths and automatically adjusts energy distributed area for each light transport path. We adapt statistical framework of Population Monte Carlo into global illumination to improve rendering efficiency. Information collected in previous(More)
Tumor initiating cells (TICs) possessing cancer stemness were shown to be enriched after therapy, resulting in the relapse and metastasis of head and neck squamous cell carcinomas (HNC). An effective therapeutic approach suppressing the HNC-TICs would be a potential method to improve the treatments for HNC. We observed that the treatment of silibinin (SB)(More)
Hemispherical integrals are important for the estimation of direct lighting which has a major impact on the results of global illumination. This work proposes the population Monte Carlo hemispherical integral (PMC-HI) sampler to improve the efficiency of direct lighting estimation. The sampler is unbiased and derived from the population Monte Carlo(More)
We present the Optimizing Control Variate (OCV) estimator, a new estimator for Monte Carlo rendering. Based upon a deterministic sampling framework, OCV allows multiple importance sampling functions to be combined in one algorithm. Its optimizing nature addresses a major problem with control variate estimators for rendering: users supply a generic(More)
Current MCMC algorithms are limited from achieving high rendering efficiency due to possibly high failure rates in caustics perturbations and stratified exploration of the image plane. In this paper we improve the MCMC approach significantly by introducing new lens perturbation and new path-generation methods. The new lens perturbation method simplifies the(More)