Transport-Based Neural Style Transfer for Smoke Simulations

Artistically controlling fluids has always been a challenging task. Optimization techniques rely on approximating simulation states towards target velocity or density field configurations, which are often handcrafted by artists to indirectly control smoke dynamics. Patch synthesis techniques transfer image textures or simulation features to a target flow field. However, these are either limited to adding structural patterns or augmenting coarse flows with turbulent structures, and hence cannot capture the full spectrum of different styles and semantically complex structures. In this paper, we propose the first Transport-based Neural Style Transfer (TNST) algorithm for volumetric smoke data. Our method is able to transfer features from natural images to smoke simulations, enabling general content-aware manipulations ranging from simple patterns to intricate motifs. The proposed algorithm is physically inspired, since it computes the density transport from a source input smoke to a desired target configuration. Our transport-based approach allows direct control over the divergence of the stylization velocity field by optimizing incompressible and irrotational potentials that transport smoke towards stylization. Temporal consistency is ensured by transporting and aligning subsequent stylized velocities, and 3D reconstructions are computed by seamlessly merging stylizations from different camera viewpoints.Comment: ACM Transaction on Graphics (SIGGRAPH ASIA 2019), additional materials: http://www.byungsoo.me/project/neural-flow-styl

A Process to Create Dynamic Landscape Paintings Using Barycentric Shading with Control Paintings

In this work, we present a process that uses a Barycentric shading method to create dynamic landscape paintings that change based on the time of day. Our process allows for the creation of dynamic paintings for any time of the day using simply a limited number of control paintings. To create a proof of concept, we have used landscape paintings of Edgar Payne, one of the leading landscape painters of the American West. His specific style of painting that blends Impressionism with the style of other painters of the AmericanWest is particularly appropriate for the demonstration of the power of our Barycentric shading method

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

A Process to Create Dynamic Landscape Paintings Using Barycentric Shading with Control Paintings

In this work, we present a process that uses a Barycentric shading method to create dynamic landscape paintings that change based on the time of day. Our process allows for the creation of dynamic paintings for any time of the day using simply a limited number of control paintings. To create a proof of concept, we have used landscape paintings of Edgar Payne, one of the leading landscape painters of the American West. His specific style of painting that blends Impressionism with the style of other painters of the AmericanWest is particularly appropriate for the demonstration of the power of our Barycentric shading method

Emerging images

Figure 1: This image, when stared at for a while, can reveal four instances of a familiar figure. Two of the figures are easier to detect than the others. Locally there is little meaningful information, and we perceive the figures only when observing the whole figures. Emergence refers to the unique human ability to aggregate information from seemingly meaningless pieces, and to perceive a whole that is meaningful. This special skill of humans can constitute an effective scheme to tell humans and machines apart. This paper presents a synthesis technique to generate images of 3D objects that are detectable by humans, but difficult for an automatic algorithm to recognize. The technique allows generating an infinite number of images with emerging figures. Our algorithm is designed so that locally the synthesized images divulge little useful information or cues to assist any segmentation or recognition procedure. Therefore, as we demonstrate, computer vision algorithms are incapable of effectively processing such images. However, when a human observer is presented with an emergence image, synthesized using an object she is familiar with, the figure emerges when observed as a whole. We can control the difficulty level of perceiving the emergence effect through a limited set of parameters. A procedure that synthesizes emergence images can be an effective tool for exploring and understanding the factors affecting computer vision techniques.

Revealing the Invisible: On the Extraction of Latent Information from Generalized Image Data

The desire to reveal the invisible in order to explain the world around us has been a source of impetus for technological and scientific progress throughout human history. Many of the phenomena that directly affect us cannot be sufficiently explained based on the observations using our primary senses alone. Often this is because their originating cause is either too small, too far away, or in other ways obstructed. To put it in other words: it is invisible to us. Without careful observation and experimentation, our models of the world remain inaccurate and research has to be conducted in order to improve our understanding of even the most basic effects. In this thesis, we1 are going to present our solutions to three challenging problems in visual computing, where a surprising amount of information is hidden in generalized image data and cannot easily be extracted by human observation or existing methods. We are able to extract the latent information using non-linear and discrete optimization methods based on physically motivated models and computer graphics methodology, such as ray tracing, real-time transient rendering, and image-based rendering

Toward a Perceptually-relevant Theory of Appearance

Two approaches are commonly employed in Computer Graphics to design and adjust the appearance of objects in a scene. A full 3D environment may be created, through geometrical, material and lighting modeling, then rendered using a simulation of light transport; appearance is then controlled in ways similar to photography. A radically different approach consists in providing 2D digital drawing tools to an artist, whom with enough talent and time will be able to create images of objects having the desired appearance; this is obviously strongly similar to what traditional artists do, with the computer being a mere modern drawing tool.In this document, I present research projects that have investigated a third approach, whereby pictorial elements of appearance are explicitly manipulated by an artist. On the one side, such an alternative approach offers a direct control over appearance, with novel applications in vector drawing, scientific illustration, special effects and video games. On the other side, it provides an modern method for putting our current knowledge of the perception of appearance to the test, as well as to suggest new models for human vision along the way