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Artistic Rendering of Natural Environments

Margarita Bratkova

(U of Utah, Ph.D. Dissertation, May 2009)

Abstract

Mountain panorama maps are aerial view paintings that depict complex, three dimensional mensional landscapes in a pleasing and understandable way. Painters and cartographers have developed techniques to create such artistic landscapes for centuries, but the process remains difficult and time-consuming.

In this dissertation, we derive principles and heuristics for panorama map creation of mountainous terrain from a perceptual and artistic analysis of two panorama maps of Yellowstone National Park by Heinrich Berann and James Niehues. We then present methods to automatically produce landscape renderings in the visual style of the panorama map. Our algorithms rely on USGS terrain and classification data. Our surface textures are generated using perceptual metrics and artistic considerations, and use the structural information present in the terrain to guide the automatic placement of image space strokes for natural surfaces such as forests, cliffs, snow, and water.

An integral part of automatic rendering is choosing a viewpoint that is meaningful and representative of the landscape. In this dissertation we examine the automatic generation of well-composed and purposeful images in the context of mountainous terrain. We explore a set of criteria based on utility, perception, and aesthetics applicable to natural outdoor scenes. We also propose a method that uses the criteria to produce renderings of terrain scenes automatically.

Finally, arising from difficulties we encountered using color transfer to improve the final rendered colors of our panorama map renderings, we propose a novel color model, oRGB, that is based on opponent color theory. Like HSV, it is designed specifically for computer graphics. However, it is also designed to work well for computational applications such as color transfer, where HSV falters. Despite being geared towards computation, oRGB's natural axes facilitate HSV-style color selection and manipulation. oRGB also allows for new applications such as a quantitative cool-to-warm metric, intuitive color manipulations and variations, and simple gamut mapping. This new color model strikes a balance between simplicity and the computational qualities of color spaces such as CIE L*a*b*.


Artistic Rendering of Mountainous Terrain

Margarita Bratkova, Peter Shirley, and William B. Thompson

(ACM Transactions on Graphics, Vol. 28, Issue 4, 2009)

Abstract

Panorama maps are aerial view paintings that depict complex, three-dimensional landscapes in a pleasing and understandable way. Painters and cartographers have developed techniques to create such artistic landscapes for centuries, but the process remains difficult and time-consuming. In this work, we derive principles and heuristics for panorama map creation of mountainous terrain from a perceptual and artistic analysis of two panorama maps of Yellowstone National Park. We then present methods to automatically produce landscape renderings in the visual style of the panorama map. Our algorithms rely on USGS terrain and classification data. Our surface textures are generated using perceptual metrics and artistic considerations, and use the structural information present in the terrain to guide the automatic placement of image space strokes for natural surfaces such as forests, cliffs, snow, and water.


Automatic Views of Natural Scenes

Margarita Bratkova, William B. Thompson, and Peter Shirley

(Computational Aesthetics in Graphics, Visualization, and Imaging, 2009)

Abstract

Automatic generation of well-composed and purposeful images is useful in a variety of computer graphics applications. In this work, we explore a set of criteria based on utility, perception, and aesthetics applicable to natural outdoor scenes. We also propose a method that uses the criteria to produce renderings of terrain scenes automatically.

Note: The version here is the original CAe submission.

oRGB: A Practical Opponent Color Space for Computer Graphics

Margarita Bratkova, Solomon Boulos, and Peter Shirley

(Computer Graphics & Applications, Vol. 29, Issue 1, 2009)

Abstract

In the last several decades much psychological and physiological evidence has accumulated in support of the essentials of Hering's theory of opponent process color perception. This theory holds that colors are organized in a 3D space with a white-black, a yellow-blue, and a red-green axis. The end colors of the same axis are opponents in that neither can be simultaneously perceived (e.g., there is no reddish green). This paper presents a color model based on opponent theory. Like HSV, this model is designed specifically for computer graphics. However, it is also designed to work well for computational applications such as color transfer, where HSV falters. Its two-axis hue system also allow saturation to be adjusted independently on the red-green and blue-yellow axes. As a result of having well defined cool (green and blue) and warm (red and yellow) primaries, the oRGB model also has a quantitative concept of a color's degree of warmth. As this new color model is a relatively simple transform from RGB and has a convenient gamut boundary for processing, it strikes a balance between simplicity and the computational qualities of color spaces such as CIE L*a*b*.

Note: The version here is a pre-print of the final CG&A publication.

Expressive Rendering of Mountainous Terrain

Margarita Bratkova, Peter Shirley, and William Thompson

(School of Computing, University of Utah, Technical Report No. UUCS-07-001)

Abstract

Painters and cartographers have developed artistic landscape rendering techniques for centuries. Such renderings can visualize complex three-dimensional landscapes in a pleasing and understandable way. In this work we examine a particular type of artistic depiction, panorama maps, in terms of function and style, and we develop methods to automatically generate panorama map reminiscent renderings from GIS data. In particular, we develop image-based procedural surface textures for mountainous terrain. Our methods use the structural information present in the terrain and are developed with perceptual metrics and artistic considerations in mind.

Visual Quality of Computer Graphics and Its Effect on Distance Judgements

Margarita Bratkova, Bob Weaver, and William Thompson

(Undergraduate Honors Thesis, Department of Computer Science, Mount Holyoke College)

Abstract

Current state-of-the-art computer-generated images, despite impressive gains in visual realism, are still unable to convey an accurate sense of scale and distance. This is less the case for the real-world, for which human judgments of scale and distance are fairly good, at least up to distances of 15-20 meters. The disparity is particularly noticeable in judgments involving actual distances to locations in the world (as compared to judgments involving relative comparisons between distances to different objects or locations). In this work we are interested in the exploration of spatial cues which provide absolute depth information. We believe the visual properties of computer generated objects and environments carry and preserve spatial information that has a key role in improving depth perception in computer graphics. To our knowledge, there are no controlled experiments done to even verify that the quality of the visual properties of computer generated objects aids in depth judgments involving actual distances to virtual locations. Nothing at all is known about which aspects of visual quality are most significant in aiding such judgments. The purpose of this study is to explore the possible effects of improved geometric complexity and quality of illumination (two aspects of visual quality) on such depth judgements. Results were obtained by performing limited human subject tests, utilizing already developed evaluation methods. However, our experimental results are not conclusive. There are complex issues that have to be addressed before we can have convincing evidence for our hypothesis.

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last updated: sep 12, 2009