Chain Shape Matching for Simulating Complex Hairstyles

Animations of hair dynamics greatly enrich the visual attractiveness of human characters. Traditional simulation techniques handle hair as clumps or continuum for efficiency; however, the visual quality is limited because they cannot represent the fine-scale motion of individual hair strands. Although a recent mass-spring approach tackled the problem of simulating the dynamics of every strand of hair, it required a complicated setting of springs and suffered from high computational cost. In this paper, we base the animation of hair on such a fine-scale on Lattice Shape Matching (LSM), which has been successfully used for simulating deformable objects. Our method regards each strand of hair as a chain of particles, and computes geometrically derived forces for the chain based on shape matching. Each chain of particles is simulated as an individual strand of hair. Our method can easily handle complex hairstyles such as curly or afro styles in a numerically stable way. While our method is not physically based, our GPU-based simulator achieves visually plausible animations consisting of several tens of thousands of hair strands at interactive rates

A Kite Simulation System using Position-based Method

Thesis (Master of Information Scienc)--University of Tsukuba, no. 37782, 2017.3.2

A Kinematic Approach for Efficient and Robust Simulation of the Cardiac Beating Motion

Computer simulation techniques for cardiac beating motions potentially have many applications and a broad audience. However, most existing methods require enormous computational costs and often show unstable behavior for extreme parameter sets, which interrupts smooth simulation study and make it difficult to apply them to interactive applications. To address this issue, we present an efficient and robust framework for simulating the cardiac beating motion. The global cardiac motion is generated by the accumulation of local myocardial fiber contractions. We compute such local-to-global deformations using a kinematic approach; we divide a heart mesh model into overlapping local regions, contract them independently according to fiber orientation, and compute a global shape that satisfies contracted shapes of all local regions as much as possible. A comparison between our method and a physics-based method showed that our method can generate motion very close to that of a physics-based simulation. Our kinematic method has high controllability; the simulated ventricle-wall-contraction speed can be easily adjusted to that of a real heart by controlling local contraction timing. We demonstrate that our method achieves a highly realistic beating motion of a whole heart in real time on a consumer-level computer. Our method provides an important step to bridge a gap between cardiac simulations and interactive applications

Computer-assisted animation creation techniques for hair animation and shade, highlight, and shadow

制度:新 ; 報告番号:甲3062号 ; 学位の種類:博士(工学) ; 授与年月日:2010/2/25 ; 早大学位記番号:新532

Realistic Hair Simulation: Animation and Rendering

International audienceThe last five years have seen a profusion of innovative solutions to one of the most challenging tasks in character synthesis: hair simulation. This class covers both recent and novel research ideas in hair animation and rendering, and presents time tested industrial practices that resulted in spectacular imagery

Photo-Realistic Rendering of Fiber Assemblies

In this thesis we introduce a novel uniform formalism for light scattering from filaments, the Bidirectional Fiber Scattering Distribution Function (BFSDF). Similar to the role of the Bidirectional Surface Scattering Reflectance Distribution Function (BSSRDF) for surfaces, the BFSDF can be seen as a general approach for describing light scattering from filaments. Based on this theoretical foundation, approximations for various levels of abstraction are derived allowing for efficient and accurate rendering of fiber assemblies, such as hair or fur. In this context novel rendering techniques accounting for all prominent effects of local and global illumination are presented. Moreover, physically-based analytical BFSDF models for human hair and other kinds of fibers are derived. Finally, using the model for human hair we make a first step towards image-based BFSDF reconstruction, where optical properties of a single strand are estimated from "synthetic photographs" (renderings) a full hairstyle

Pluralistic Aging Diffusion Autoencoder

Face aging is an ill-posed problem because multiple plausible aging patterns may correspond to a given input. Most existing methods often produce one deterministic estimation. This paper proposes a novel CLIP-driven Pluralistic Aging Diffusion Autoencoder (PADA) to enhance the diversity of aging patterns. First, we employ diffusion models to generate diverse low-level aging details via a sequential denoising reverse process. Second, we present Probabilistic Aging Embedding (PAE) to capture diverse high-level aging patterns, which represents age information as probabilistic distributions in the common CLIP latent space. A text-guided KL-divergence loss is designed to guide this learning. Our method can achieve pluralistic face aging conditioned on open-world aging texts and arbitrary unseen face images. Qualitative and quantitative experiments demonstrate that our method can generate more diverse and high-quality plausible aging results.Comment: Accepted by ICCV 202