Expressive

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2D Shading for Cel Animation
(ACM, 2018) Hudon, Matis; Pagés, Rafael; Grogan, Mairéad; Ondřej, Jan; Smolić, Aljoša; Aydın, Tunç and Sýkora, Daniel
We present a semi-automatic method for creating shades and self-shadows in cel animation. Besides producing attractive images, shades and shadows provide important visual cues about depth, shapes, movement and lighting of the scene. In conventional cel animation, shades and shadows are drawn by hand. As opposed to previous approaches, this method does not rely on a complex 3D reconstruction of the scene: its key advantages are simplicity and ease of use. The tool was designed to stay as close as possible to the natural 2D creative environment and therefore provides an intuitive and user-friendly interface. Our system creates shading based on hand-drawn objects or characters, given very limited guidance from the user. The method employs simple yet very efficient algorithms to create shading directly out of drawn strokes. We evaluate our system through a subjective user study and provide qualitative comparison of our method versus existing professional tools and state of the art.
3D Sketching for Interactive Model Retrieval in Virtual Reality
(ACM, 2018) Giunchi, Daniele; James, Stuart; Steed, Anthony; Aydın, Tunç and Sýkora, Daniel
We describe a novel method for searching 3D model collections using free-form sketches within a virtual environment as queries. As opposed to traditional sketch retrieval, our queries are drawn directly onto an example model. Using immersive virtual reality the user can express their query through a sketch that demonstrates the desired structure, color and texture. Unlike previous sketch-based retrieval methods, users remain immersed within the environment without relying on textual queries or 2D projections which can disconnect the user from the environment. We perform a test using queries over several descriptors, evaluating the precision in order to select the most accurate one. We show how a convolutional neural network (CNN) can create multi-view representations of colored 3D sketches. Using such a descriptor representation, our system is able to rapidly retrieve models and in this way, we provide the user with an interactive method of navigating large object datasets. Through a user study we demonstrate that by using our VR 3D model retrieval system, users can perform search more quickly and intuitively than with a naive linear browsing method. Using our system users can rapidly populate a virtual environment with specific models from a very large database, and thus the technique has the potential to be broadly applicable in immersive editing systems.
Abstract Depiction of Human and Animal Figures: Examples from Two Centuries of Art and Craft
(ACM, 2018) Dodgson, Neil A.; Aydın, Tunç and Sýkora, Daniel
The human figure is important in art. I discuss examples of the abstract depiction of the human figure and the challenge faced in attempting to mimic algorithmically what human artists can achieve. The challenge lies in the workings of the human brain: we have enormous knowledge about the world and a particular ability to make fine distinctions about other humans from posture, clothing and expression. This allows a human to make assumptions about human figures from a tiny amount of data, and allows a human artist to take advantage of this when creating art. We look at examples from impressionist and post-impressionist painting, from cross-stitch and knitting, from pixelated renderings in early video games, and from the stylisation used by the artists of children's books.
Abstract Shape Synthesis From Linear Combinations of Clelia Curves
(The Eurographics Association, 2019) Putnam, Lance; Todd, Stephen; Latham, William; Kaplan, Craig S. and Forbes, Angus and DiVerdi, Stephen
This article outlines several families of shapes that can be produced from a linear combination of Clelia curves. We present parameters required to generate a single curve that traces out a large variety of shapes with controllable axial symmetries. Several families of shapes emerge from the equation that provide a productive means by which to explore the parameter space. The mathematics involves only arithmetic and trigonometry making it accessible to those with only the most basic mathematical background. We outline formulas for producing basic shapes, such as cones, cylinders, and tori, as well as more complex families of shapes having non-trivial symmetries. This work is of interest to computational artists and designers as the curves can be constrained to exhibit specific types of shape motifs while still permitting a liberal amount of room for exploring variations on those shapes.
Aesthetically-Oriented Atmospheric Scattering
(The Eurographics Association, 2019) Shen, Yang; Mallett, Ian; Shkurko, Konstantin; Kaplan, Craig S. and Forbes, Angus and DiVerdi, Stephen
We present Aesthetically-Oriented Atmospheric Scattering (AOAS): an experiment into the feasibility of using real-time rendering as a tool to explore sky styles. AOAS provides an interactive design environment which enables rapid iteration cycles from concept to implementation to preview. Existing real-time rendering techniques for atmospheric scattering struggle to produce non-photorealistic sky styles within any 3D scene. To solve this problem, first, we simplify the geometric representation of atmospheric scattering to a single skydome to leverage the flexibility and simplicity of skydomes in compositing with 3D scenes. Second, we classify the essential and non-essential visual characteristics of the sky and allow AOAS to vary the latter, thus producing meaningful, non-photorealistic sky styles with real-time atmospheric scattering that are still recognizable as skies, but contain artistic stylization. We use AOAS to generate a wide variety of sky examples ranging from physical to highly stylized in appearance. The algorithm can be easily implemented on the GPU, and performs at interactive frame rates with low memory consumption and CPU usage.
Aesthetics of Curvature Bases for Sketches
(The Eurographics Association, 2019) Lippincott, Keith; Hatton, Ross L.; Grimm, Cindy; Kaplan, Craig S. and Forbes, Angus and DiVerdi, Stephen
In this work we propose a curve approximation method that operates in the curvature domain. The curvature is represented using one of several different types of basis functions (linear, quadratic, spline, sinusoidal, orthogonal polynomial), and the curve's geometry is reconstructed from that curvature basis. Our hypothesis is that different curvature bases will result in different aesthetics for the reconstructed curve. We conducted a user study comparing multiple curvature bases, both for aesthetics and similarity to the original curve, and found statistically significant differences in how people ranked the reconstructed curve's aesthetics and similarity. To support adaptive curve fitting we developed a fitting algorithm that matches the original curve's geometry and explicitly accounts for corners.
Approaches for Local Artistic Control of Mobile Neural Style Transfer
(ACM, 2018) Reimann, Max; Klingbeil, Mandy; Pasewaldt, Sebastian; Semmo, Amir; Döllner, Jürgen; Trapp, Matthias; Aydın, Tunç and Sýkora, Daniel
This work presents enhancements to state-of-the-art adaptive neural style transfer techniques, thereby providing a generalized user interface with creativity tool support for lower-level local control to facilitate the demanding interactive editing on mobile devices. The approaches are implemented in a mobile app that is designed for orchestration of three neural style transfer techniques using iterative, multi-style generative and adaptive neural networks that can be locally controlled by on-screen painting metaphors to perform location-based filtering and direct the composition. Based on first user tests, we conclude with insights, showing different levels of satisfaction for the implemented techniques and user interaction design, pointing out directions for future research.
Automatic Generation of Geological Stories from a Single Sketch
(ACM, 2018) Garcia, Maxime; Cani, Marie-Paule; Ronfard, Rémi; Gout, Claude; Perrenoud, Christian; Aydın, Tunç and Sýkora, Daniel
Describing the history of a terrain from a vertical geological cross-section is an important problem in geology, called geological restoration. Designing the sequential evolution of the geometry is usually done manually, involving many trials and errors. In this work, we recast this problem as a storyboarding problem, where the different stages in the restoration are automatically generated as storyboard panels and displayed as geological stories. Our system allows geologists to interactively explore multiple scenarios by selecting plausible geological event sequences and backward simulating them at interactive rate, causing the terrain layers to be progressively un-deposited, un-eroded, un-compacted, un-folded and un-faulted. Storyboard sketches are generated along the way. When a restoration is complete, the storyboard panels can be used for automatically generating a forward animation of the terrain history, enabling quick visualization and validation of hypotheses. As a proof-of-concept, we describe how our system was used by geologists to restore and animate cross-sections in real examples at various spatial and temporal scales and with different levels of complexity, including the Chartreuse region in the French Alps.
Brush Stroke Synthesis with a Generative Adversarial Network Driven by Physically Based Simulation
(ACM, 2018) Wu, Rundong; Chen, Zhili; Wang, Zhaowen; Yang, Jimei; Marschner, Steve; Aydın, Tunç and Sýkora, Daniel
We introduce a novel approach that uses a generative adversarial network (GAN) to synthesize realistic oil painting brush strokes, where the network is trained with data generated by a high-fidelity simulator. Among approaches to digitally synthesizing natural media painting strokes, methods using physically based simulation by far produce the most realistic visual results and allow the most intuitive control of stroke variations. However, accurate physics simulations are known to be computationally expensive and often cannot meet the performance requirements of painting applications. A few existing simulation-based methods have managed to reach real-time performance at the cost of lower visual quality resulting from simplified models or lower resolution. In our work, we propose to replace the expensive fluid simulation with a neural network generator. The network takes the existing canvas and new brush trajectory information as input and produces the height and color of the paint surface as output. We build a large painting sample training dataset by feeding random strokes from artists' recordings into a high quality offline simulator. The network is able to produce visual quality comparable to the offline simulator with better performance than the existing real-time oil painting simulator. Finally, we implement a real-time painting system using the trained network with stroke splitting and patch blending and show artworks created with the system by artists. Our neural network approach opens up new opportunities for real-time applications of sophisticated and expensive physically based simulation.
Computational Light Painting and Kinetic Photography
(ACM, 2018) Huang, Yaozhun; Tsang, Sze-Chun; Wong, Hei-Ting Tamar; Lam, Miu-Ling; Aydın, Tunç and Sýkora, Daniel
We present a computational framework for creating swept volume light painting and kinetic photography. Unlike conventional light painting technique using hand-held point light source or LED arrays, we move a flat-panel display with robot in a curved path. The display shows real-time rendered contours of a 3D object being sliced by the display plane along the path. All light contours are captured in a long exposure and constitute the virtual 3D object augmented in the real space. To ensure geometric accuracy, we use hand-eye calibration method to precisely obtain the transformation between the display and the robot. A path generation algorithm is developed to automatically yield the robot path that can best accommodate the 3D shape of the target model. To further avoid shape distortion due to asynchronization between the display's pose and the image content, we propose a real-time slicing method for arbitrary slicing direction. By organizing the triangular mesh into Octree data structure, the approach can significantly reduce the computational time and improve the performance of real-time rendering. We study the optimal tree level for different range of triangle numbers so as to attain competitive computational time.Texture mapping is also implemented to produce colored light painting. We extend our methodologies to computational kinetic photography, which is dual to light painting. Instead of keeping the camera stationary, we move the camera with robot and capture long exposures of a stationary display showing light contours. We transform the display path for light painting to the camera path for kinetic photography. A variety of 3D models are used to verify that the proposed techniques can produce stunning long exposures with high-fidelity volumetric imagery. The techniques have great potential for innovative applications including animation, visible light communication, invisible information visualization and creative art.
Context-based Sketch Classification
(ACM, 2018) Zhang, Jianhui; Chen, Yilan; Li, Lei; Fu, Hongbo; Tai, Chiew-Lan; Aydın, Tunç and Sýkora, Daniel
We present a novel context-based sketch classification framework using relations extracted from scene images. Most of existing methods perform sketch classification by considering individually sketched objects and often fail to identify their correct categories, due to the highly abstract nature of sketches. For a sketched scene containing multiple objects, we propose to classify a sketched object by considering its surrounding context in the scene, which provides vital cues for resolving its recognition ambiguity. We learn such context knowledge from a database of scene images by summarizing the inter-object relations therein, such as co-occurrence, relative positions and sizes.We show that the context information can be used for both incremental sketch classification and sketch co-classification. Our method outperforms the state-of-the-art single-object classification method, evaluated on a new dataset of sketched scenes.
Defining Hatching in Art
(The Eurographics Association, 2019) Philbrick, Greg; Kaplan, Craig S.; Kaplan, Craig S. and Forbes, Angus and DiVerdi, Stephen
We define hatching-a drawing technique-as rigorously as possible. A pure mathematical formulation or even a binary this-or-that definition is unreachable, but useful insights come from driving as close as we can. First we explain hatching's purposes. Then we define hatching as the use of patches: groups of roughly parallel curves that form flexible, simple patterns. After elaborating on this definition's parts, we briefly treat considerations for research in expressive rendering.
An ego-altruist society
(ACM, 2018) Cruz, Pedro M.; Cunha, André B.; Aydın, Tunç and Sýkora, Daniel
This artwork is an artificial life simulation that shows how a society of agents flourishes with the symbiotic interactions between the egotist and altruist extremes. Egotist agents seek and absorb energy. Altruist agents seek other agents, share energy and reproduce. They group into multi-agent organisms that adapt to the energy present in the system.
Enhancing Neural Style Transfer using Patch-Based Synthesis
(The Eurographics Association, 2019) Texler, Ondřej; Fišer, Jakub; Lukáč, Mike; Lu, Jingwan; Shechtman, Eli; Sýkora, Daniel; Kaplan, Craig S. and Forbes, Angus and DiVerdi, Stephen
We present a new approach to example-based style transfer which combines neural methods with patch-based synthesis to achieve compelling stylization quality even for high-resolution imagery. We take advantage of neural techniques to provide adequate stylization at the global level and use their output as a prior for subsequent patch-based synthesis at the detail level. Thanks to this combination, our method keeps the high frequencies of the original artistic media better, thereby dramatically increases the fidelity of the resulting stylized imagery. We also show how to stylize extremely large images (e.g., 340 Mpix) without the need to run the synthesis at the pixel level, yet retaining the original high-frequency details.
Expressive 2018: frontmatter
(ACM, 2018) Aydın, Tunç and Sýkora, Daniel
Fluid Brush
(ACM, 2018) Abraham, Sarah; Vouga, Etienne; Fussell, Donald; Aydın, Tunç and Sýkora, Daniel
Digital media allows artists to create a wealth of visually-interesting effects that are impossible in traditional media. This includes temporal effects, such as cinemagraph animations, and expressive fluid effects. Yet these flexible and novel media often require highly technical expertise, which is outside a traditional artist's skill with paintbrush or pen. Fluid Brush acts a form of novel, digital media, which retains the brush-based interactions of traditional media, while expressing the movement of turbulent and laminar flow. As a digital media controlled through a non-technical interface, Fluid Brush allows for a novel form of painting that makes fluid effects accessible to novice users and traditional artists. To provide an informal demonstration of the medium's effects, applications, and accessibility, we asked designers, traditional artists, and digital artists to experiment with Fluid Brush. They produced a variety of works reflective of their artistic interests and backgrounds.
Frontmatter: Expressive 2019
(The Eurographics Association, 2019) Kaplan, Craig S.; Forbes, Angus; DiVerdi, Stephen; Kaplan, Craig S. and Forbes, Angus and DiVerdi, Stephen
Generating Playful Palettes from Images
(The Eurographics Association, 2019) DiVerdi, Stephen; Lu, Jingwan; Echevarria, Jose; Shugrina, Maria; Kaplan, Craig S. and Forbes, Angus and DiVerdi, Stephen
Playful Palettes are a recent innovation in how artists can mix, explore, and choose colors in a user interface that combines the benefits of a traditional media painter's palette with non-destructive capabilities of digital tools. We present a technique to generate a Playful Palette that best represents the colors found in an input image, allowing the artist to select colors from the image's gamut, while maintaining full editability of the palette. We show that our approach outperforms recent work in terms of how accurately the image gamut is reproduced, and we present an approximation algorithm that is an order of magnitude faster with an acceptable loss in quality.
Implicit Representation of Inscribed Volumes
(ACM, 2018) Sahbaei, Parto; Mould, David; Wyvill, Brian; Aydın, Tunç and Sýkora, Daniel
We present an implicit approach for constructing smooth isolated or interconnected 3-D inscribed volumes which can be employed for volumetric modeling of various kinds of spongy or porous structures, such as volcanic rocks, pumice stones, Cancellus bones, liquid or dry foam, radiolarians, cheese, and other similar materials. The inscribed volumes can be represented in their normal or positive forms to model natural pebbles or pearls, or in their inverted or negative forms to be used in porous structures, but regardless of their types, their smoothness and sizes are controlled by the user without losing the consistency of the shapes. We introduce two techniques for blending and creating interconnections between these inscribed volumes to achieve a great flexibility to adapt our approach to different types of porous structures, whether they are regular or irregular. We begin with a set of convex polytopes such as 3-D Voronoi diagram cells and compute inscribed volumes bounded by the cells. The cells can be irregular in shape, scale, and topology, and this irregularity transfers to the inscribed volumes, producing natural-looking spongy structures. Describing the inscribed volumes with implicit functions gives us a freedom to exploit volumetric surface combinations and deformations operations effortlessly.
Irregular Pebble Mosaics with Sub-Pebble Detail
(The Eurographics Association, 2019) Javid, Ali Sattari; Doyle, Lars; Mould, David; Kaplan, Craig S. and Forbes, Angus and DiVerdi, Stephen
Pebble mosaics convey images through an irregular tiling of rounded pebbles. Past work used relatively uniform tile sizes. We show how to create detailed representations of input photographs in a pebble mosaic style; we first create pebble shapes through a variant of k-means, then compute sub-pebble detail with textured, two-tone pebbles.We use a custom distance function to ensure that pebble sizes adapt to local detail and orient to local feature directions, for an overall effect of high fidelity to the input photograph despite the constraints of the pebble style.

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