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Image and Video-Based Artistic Stylisation

by Rosin, Paul.
Authors: Collomosse, John.%editor. | SpringerLink (Online service) Series: Computational Imaging and Vision, 1381-6446 ; . 42 Physical details: XII, 399 p. 217 illus., 158 illus. in color. online resource. ISBN: 1447145194 Subject(s): Computer science. | Computer vision. | Computer graphics. | Computer Science. | Computer Imaging, Vision, Pattern Recognition and Graphics. | Image Processing and Computer Vision. | Computer Graphics.
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E-Book E-Book AUM Main Library 006.6 (Browse Shelf) Not for loan

Stroke Based Painterly Rendering -- A Brush Stroke Synthesis Toolbox -- Halftoning and Stippling -- Non-Photorealistic Shading and Hatching -- Artistic Stylization by Nonlinear Filtering -- NPR for Traditional Artistic Genres -- Region-based Abstraction -- Gradient Art: Creation and Vectorization -- Depiction using geometric constraints -- Artificial Mosaic Generation -- Non-Photorealistic Rendering with Reduced Colour Palettes -- Artistic Rendering of Portraits -- Temporally Coherent Video Stylization -- Computer-assisted Repurposing of Existing Animations -- Evaluating and Validating Non-Photorealistic and Illustrative Rendering -- Don’t measure – appreciate! -- NPR seen through the prism of Art History -- NPR in the Wild.

Non-photorealistic rendering (NPR) is a combination of computer graphics and computer vision that produces renderings in various artistic, expressive or stylized ways such as painting and drawing. This book focuses on image and video based NPR, where the input is a 2D photograph or a video rather than a 3D model. 2D NPR techniques have application in areas as diverse as consumer and professional digital photography and visual effects for TV and film production. The book covers the full range of the state of the art of NPR with every chapter authored by internationally renowned experts in the field, covering both classical and contemporary techniques. It will enable both graduate students in computer graphics, computer vision or image processing and professional developers alike to quickly become familiar with contemporary techniques, enabling them to apply 2D NPR algorithms in their own projects.

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