RTcams: A New Perspective on Nonphotorealistic Rendering from Photographs

Hall, Peter M.; Collomosse, John; Song, Yi-Zhe; Shen, Peiyi; Li, Chuan

doi:10.1109/tvcg.2007.1047

Cited by 18 publications

(8 citation statements)

References 25 publications

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“…Hall et al proposed the RTcam (rational tensor camera model) [200]. It essentially proceeds by first transforming 3D points via biquadratic rational functions, followed by a perspective projection to a 2D image plane (the full RTcam model is defined for arbitrary dimensions of scene and image).…”

Section: Polynomial and Rational Polynomial Modelsmentioning

confidence: 99%

Camera Models and Fundamental Concepts Used in Geometric Computer Vision

Sturm

2010

FNT in Computer Graphics and Vision

157

122

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A printed and bound version is available at a special discount price of US35 from Now Publishers. This can be obtained by entering the promotional code CGV006023 on https://www.nowpublishers.com/bookorder.aspx?doi=0600000023&product=CGVInternational audienceThis survey is mainly motivated by the increased availability and use of panoramic image acquisition devices, in computer vision and various of its applications. Different technologies and different computational models thereof exist and algorithms and theoretical studies for geometric computer vision ("structure-from-motion") are often re-developed without highlighting common underlying principles. One of the goals of this survey is to give an overview of image acquisition methods used in computer vision and especially, of the vast number of camera models that have been proposed and investigated over the years, where we try to point out similarities between different models. Results on epipolar and multi-view geometry for different camera models are reviewed as well as various calibration and self-calibration approaches, with an emphasis on non-perspective cameras. We finally describe what we consider are fundamental building blocks for geometric computer vision or structure-from-motion: epipolar geometry, pose and motion estimation, 3D scene modeling, and bundle adjustment. The main goal here is to highlight the main principles of these, which are independent of specific camera models

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Section: Polynomial and Rational Polynomial Modelsmentioning

confidence: 99%

Camera Models and Fundamental Concepts Used in Geometric Computer Vision

Sturm

2010

FNT in Computer Graphics and Vision

157

122

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“…Analysis of scene structure could enable manipulation of imagery at the composition level. Initial forays into composition indicate the potential of extending the gamut of IB-AR to include abstract styles such as Cubism [16], Futurism [49] and nonlinear projection [34]. The manipulation of global structure for abstraction has also been explored recently [169].…”

Section: Technical Directionsmentioning

confidence: 99%

State of the "Art”: A Taxonomy of Artistic Stylization Techniques for Images and Video

Kyprianidis

Collomosse

Wang

et al. 2013

IEEE Trans. Visual. Comput. Graphics

243

147

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“…A number of researchers have addressed the problem of creating projections that contain multiple viewpoints, either interactively [Agrawala et al 2000;Coleman and Singh 2004] or by combining multiple views along a camera path [Wood et al 1997;Rademacher and Bishop 1998;Popescu et al 2009]. Several researchers have proposed alternative projection models that go beyond the standard linear projection model, and they have used these models to produce artistic renderings [Yu and McMillan 2004;Hall et al 2007]. Unlike these methods our approach does not rely on access to 3D scene geometry.…”

Section: Related Workmentioning

confidence: 99%

Image warps for artistic perspective manipulation

Robert¹,

Agarwala²,

Agrawala³

2010

ACM SIGGRAPH 2010 Papers

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InputResult: Sharply converging lines Result: Weakly converging lines Figure 1: We present a tool for controlling the perspective in photographs by manipulating vanishing points and lines. We can constrain the lines to converge sharply as in a wide-angle image or more weakly as in a telephoto image ( Figure 2). Our perception of the room changes for each result; the former result feels more tightly enclosed and the later feels more spacious. AbstractPainters and illustrators commonly sketch vanishing points and lines to guide the construction of perspective images. We present a tool that gives users the ability to manipulate perspective in photographs using image space controls similar to those used by artists.Our approach computes a 2D warp guided by constraints based on projective geometry. A user annotates an image by marking a number of image space constraints including planar regions of the scene, straight lines, and associated vanishing points. The user can then use the lines, vanishing points, and other point constraints as handles to control the warp. Our system optimizes the warp such that straight lines remain straight, planar regions transform according to a homography, and the entire mapping is as shape-preserving as possible. While the result of this warp is not necessarily an accurate perspective projection of the scene, it is often visually plausible. We demonstrate how this approach can be used to produce a variety of effects, such as changing the perspective composition of a scene, exploring artistic perspectives not realizable with a camera, and matching perspectives of objects from different images so that they appear consistent for compositing.

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RTcams: A New Perspective on Nonphotorealistic Rendering from Photographs

Cited by 18 publications

References 25 publications

Camera Models and Fundamental Concepts Used in Geometric Computer Vision

Camera Models and Fundamental Concepts Used in Geometric Computer Vision

State of the "Art”: A Taxonomy of Artistic Stylization Techniques for Images and Video

Image warps for artistic perspective manipulation

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