CompAesth 13: Workshop on Computational Aesthetics

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https://diglib.eg.org/handle/10.2312/14888

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The Aesthetics of Rapidly-Exploring Random Trees
(ACM, 2013) Burch, Michael; Weiskopf, Daniel; Donald House and Cindy Grimm
Rapidly-Exploring Random Trees (RRTs) have been introduced as an algorithmic concept for the rapid exploration of configuration spaces targeting fast path planning, mainly applied in the field of robotics. Typically, such structured space organizations are only used on an algorithmic level but not for direct visual representation. In this paper, we illustrate the aesthetics of such RRTs by displaying them in a visual form that serves as a basis to generate algorithmic art. Apart from the visual encoding of such space-filling node-link diagrams, we demonstrate how these trees grow in the configuration space for RRT layouts with and without incremental distances from the initial point. Additionally, RRTs can be visually enhanced by several inherent tree metrics such as tree depth, subtree size, and branching factors to make the diagrams more aesthetically appealing and readable. We provide examples of different tree sizes and illustrate the effect of changes to several control parameters such as color coding, line segment thickness, layouts, and shape constraints.
Creating Contour Gradients using 3D Bevels
(ACM, 2013) Asente, Paul; Carr, Nathan; Donald House and Cindy Grimm
Contour gradients have color contours that follow the shape of the path being filled. Existing algorithms cannot create them in a resolution- and scale-independent way, causing visible rendering artifacts if enlarged. We describe a new method that approximates them with a set of paths filled by linear gradients. A 3D bevel of the path being filled gives both the shape of these paths and the information needed to compute gradient vectors for the linear gradients. Our representation is efficient, compact, and both resolution and scale independent.
Generating Knitting Patterns from a Sketch: a CSP Approach
(ACM, 2013) Kryven, Marta; Fourquet, Elodie; Donald House and Cindy Grimm
Graphic patterns in knitting are composed of relatively large pixels and create a picture when seen from a distance, while on close viewing the image falls apart into its constituent stitches. Such patterns are constrained in use of colors due to the nature of the medium and in spacing between pixels as a durability concern and are a challenge to create. This paper shows how to convert an arbitrary linedrawing or photograph to a constraint-compliant Fair-Isle knitting pattern for a programmable knitting machine or a manual knitter by formulating it as a Constraint Satisfaction Problem (CSP). First we generate a constraint-inconsistent starting pixel assignment. Then we produce a perceptually similar constraint compliant solution, by minimizing and randomly distributing pixel flips to preserve gestalt features of the original design. We evaluate ways of generating a starting assignment using thresholding and dithering and of solving the problem using pseudo-random texturing and search: Random Walk, GSAT and Min-Conflict. Two hybrid solutions that achieve an improved design-dependent result are described. To test the algorithms an interactive knitting pattern generator was implemented.
Generative Fluid Profiles for Interactive Media Arts Projects
(ACM, 2013) Forbes, Angus Graeme; Höllerer, Tobias; Legrady, George; Donald House and Cindy Grimm
This paper presents a real-time, interactive fluid simulation and vec- tor visualization technique that can be incorporated in media arts projects. These techniques- referred to collectively as the Fluid Automata system- have been adapted for various configurations, in- cluding mobile applications, interactive 2D and 3D projections, and multi-touch tables, and have been presented in a number of differ- ent environments- both academic and artistic- including galleries, conferences, and a virtual reality research lab. We describe specific details about the fluid simulation component, which, by changing a small number of parameters, allows users to quickly generate a vast number of ''fluid profiles'' and thus to explore a wide range of aesthetic possibilities that are easy to incorporate into media arts projects. In particular, we present this fluid simulation (and accom- panying visual representation) as an example of how media artists can create novel versions of existing visualization techniques in or- der to emphasize variability, experimentation, and interactivity.
How Self-Similar are Artworks at Different Levels of Spatial Resolution?
(ACM, 2013) Amirshahi, Seyed Ali; Redies, Christoph; Denzler, Joachim; Donald House and Cindy Grimm
Recent research has shown that a large variety of aesthetic paintings are highly self-similar. The degree of self-similarity seen in artworks is close to that observed for complex natural scenes, to which low-level visual coding in the human visual system is adapted. In this paper, we introduce a new measure of self-similarity, which we will refer to as the Weighted Self-Similarity (WSS). Using PHOG, which is a state-of-the-art technique from computer vision, WSS is derived from a measure that has been previously linked to aesthetic paintings and represents self-similarity on a single level of spatial resolution. In contrast, WSS takes into account the similarity values at multiple levels of spatial resolution. The values are linked to each other by using a weighting factor so that the overall self-similarity of an image reflects how self-similarity changes at different spatial levels. Compared to the previously proposed metric, WSS has the advantage that it also takes into account differences between selfsimilarity at different levels of spatial resolution with respect to one another. An analysis of a large image dataset of aesthetic artworks (the JenAesthetics dataset) and other categories of images reveals that artworks, on average, show a relatively high WSS. Similarly, high values for WSS were obtained for images of natural patterns that can be described as being fractal (for example, images of clouds, branches or lichen growth patterns). The analysis of the JenAesthetics dataset, which consists of paintings of Western provenance, yielded similar values of WSS for different art styles. In conclusion, self-similarity is uniformly high across different levels of spatial resolution in the artworks analyzed in the present study.
Morphable guidelines for the human head
(ACM, 2013) Gao, Shelley; Werner, Christopher; Gooch, Amy A.; Donald House and Cindy Grimm
We present a system to help users achieve better face warping on 2D portrait images. Faces can be difficult to warp accurately because the rotation of the head affects the shape of the facial features. We bypass this problem by utilizing the Loomis 'ball and plane' head drawing method as a proxy structure. The resulting 'morphable guidelines' consist of a simple 3D head model. This proxy model can be reshaped by the user to mimic the positioning and proportions of a face in their input image. The vertices of the model act as deformation points for a 2D image deformation algorithm. Thus, the user can seamlessly transform the face proportions in the 2D image by transforming the proportions of the morphable guidelines. This technique can be used for both retouching and caricature warping purposes, as it is well-suited for both subtle and extreme modifications. Our system is advantageous over previous work in face warping because our morphable guidelines can be used on a wide range of head orientations and do not require the generation and reintegration of a full 3D model.
Non-Photorealistic Rendering with Spot Colour
(ACM, 2013) Rosin, Paul L.; Lai, Yu-Kun; Donald House and Cindy Grimm
Colour is an important aspect of art. Not only does it give richness to images, but it always provides a means to highlight certain objects. This idea of spot colour has been used extensively in both fine art and commercial illustrations. Many non-photorealistic rendering (NPR) algorithms produce grayscale or monochromatic images with low saturations. In this paper we introduce the idea of spot colour to NPR and propose a simple and automatic algorithm to add spot colour to these rendering styles. The hue is thresholded into colour layers and the most appropriate layer is automatically determined based on factors such as layer region shape and salience. We also consider using an edge-based criterion to colourise the background, which is an effective means of making the foreground stand out. We demonstrate the effectiveness of our approach by adding spot colour to a diverse set of NPR styles.
Patch-Based Geometric Texture Synthesis
(ACM, 2013) AlMeraj, Zainab; Kaplan, Craig S.; Asente, Paul; Donald House and Cindy Grimm
Inspired by the results of recent studies on the perception of geometric textures, we present a patch-based geometric synthesis algorithm that mimics observed synthesis strategies. Our synthesis process first constructs an overlapping grid of copies of the exemplar, and then culls individual motifs based on overlaps and the enforcement of minimum distances.
Perceiving Complex Causation Through Interaction
(ACM, 2013) Ware, Colin; Donald House and Cindy Grimm
When we interact with a touch screen computational device we have the strong subjective impression that we are directly causing changes that occur on the screen. For example, sliding a finger on a screen causes scrolling of the information. But the current method for showing causal relationships derived from models is to use a causal network diagram with nodes representing entities and arrows represent causal relationships between those entities. Sometimes arrows are labeled to weight the connections. In such diagrams there is no immediate visual impression of causal links, just the perception of connections and the arrowhead symbol. Interactive touch screens would seem to offer the potential for creating interactive diagrams where the causal relationships are provided in a perceptually immediate and unequivocal fashion. This paper explores methods for creating interactive diagrams using multiple touches that go beyond simple positive causation to express complexities such as causal effect enhancement, causal effect reduction and causal effect blocking. A design rationale is presented with special attention to temporal constraints. Results from an evaluation study suggest that the design can be understood with minimal instruction by most people.
Preface and Table of Contents
(ACM, 2013) Donald House and Cindy Grimm
Real-Time Rendering of Water Surfaces with Cartography-Oriented Design
(ACM, 2013) Semmo, Amir; Kyprianidis, Jan Eric; Trapp, Matthias; Döllner, Jürgen; Donald House and Cindy Grimm
More than 70 percent of the Earth's surface is covered by oceans, seas, and lakes, making water surfaces one of the primary elements in geospatial visualization. Traditional approaches in computer graphics simulate and animate water surfaces in the most realistic ways. However, to improve orientation, navigation, and analysis tasks within 3D virtual environments, these surfaces need to be carefully designed to enhance shape perception and land-water distinction. We present an interactive system that renders water surfaces with cartography-oriented design using the conventions of mapmakers. Our approach is based on the observation that hand-drawn maps utilize and align texture features to shorelines with non-linear distance to improve figure-ground perception and express motion. To obtain local orientation and principal curvature directions, first, our system computes distance and feature-aligned distance maps. Given these maps, waterlining, water stippling, contour-hatching, and labeling are applied in real-time with spatial and temporal coherence. The presented methods can be useful for map exploration, landscaping, urban planning, and disaster management, which is demonstrated by various real-world virtual 3D city and landscape models.
Simple Art as Abstractions of Photographs
(ACM, 2013) Hall, Peter; Song, Yi-Zhe; Donald House and Cindy Grimm
This paper shows that it is possible to semi-automatically process photographs into Simple Art. Simple Art is a term that we use to refer to a group of artistic styles such a child art, cave art, and Fine Artists as exemplified by Joan Mir´o. None of these styles has been previously studied by the NPR community. Our contribution is to provide a process that makes them accessible. We describe a method that automatically constructs a hierarchical model of an input photograph, and asks a user to identify objects inside it. Each object is a sub-tree, which can be rendered under user control. The method is demonstrated using emulations of Simple Art. We include an assessment of our results against a set of norms recommended by a Cultural Historian. We conclude that producing Simple Art raises important technical questions, especially surrounding the interplay between computational modelling and human abstractions.
Virtual Photograph Based Saliency Analysis of High Dynamic Range Images
(ACM, 2013) Gao, Xihe; Brooksy, Stephen; Arnold, Dirk V.; Donald House and Cindy Grimm
Computational visual attention systems detect regions of interest in images. These systems have a broad range of applications in areas such as computer vision, computational aesthetics, and nonphotorealistic rendering. However, almost all the systems to date are designed for low dynamic range (LDR) images and may not be suitable for analyzing saliency in high dynamic range (HDR) images. We propose a novel algorithm for saliency analysis of HDR images that is based on virtual photographs. Taking virtual photographs is the inverse process of generating HDR images from multiple LDR exposures, and the virtual photograph sequence has the capacity to more comprehensively reveal salient content in HDR images. We demonstrate that our method can produce more consistently reliable results than existing methods.

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