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Media Computing Computational Media Aesthetics 1st Edition Chitra Dorai

  • SKU: BELL-4199578
Media Computing Computational Media Aesthetics 1st Edition Chitra Dorai
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Media Computing Computational Media Aesthetics 1st Edition Chitra Dorai instant download after payment.

Publisher: Springer US
File Extension: PDF
File size: 9.84 MB
Pages: 198
Author: Chitra Dorai, Svetha Venkatesh (auth.), Chitra Dorai, Svetha Venkatesh (eds.)
ISBN: 9781461354031, 9781461511199, 146135403X, 1461511194
Language: English
Year: 2002
Edition: 1

Product desciption

Media Computing Computational Media Aesthetics 1st Edition Chitra Dorai by Chitra Dorai, Svetha Venkatesh (auth.), Chitra Dorai, Svetha Venkatesh (eds.) 9781461354031, 9781461511199, 146135403X, 1461511194 instant download after payment.

Traditionally, scientific fields have defined boundaries, and scientists work on research problems within those boundaries. However, from time to time those boundaries get shifted or blurred to evolve new fields. For instance, the original goal of computer vision was to understand a single image of a scene, by identifying objects, their structure, and spatial arrangements. This has been referred to as image understanding. Recently, computer vision has gradually been making the transition away from understanding single images to analyz­ ing image sequences, or video understanding. Video understanding deals with understanding of video sequences, e. g. , recognition of gestures, activities, fa­ cial expressions, etc. The main shift in the classic paradigm has been from the recognition of static objects in the scene to motion-based recognition of actions and events. Video understanding has overlapping research problems with other fields, therefore blurring the fixed boundaries. Computer graphics, image processing, and video databases have obvious overlap with computer vision. The main goal of computer graphics is to gener­ ate and animate realistic looking images, and videos. Researchers in computer graphics are increasingly employing techniques from computer vision to gen­ erate the synthetic imagery. A good example of this is image-based rendering and modeling techniques, in which geometry, appearance, and lighting is de­ rived from real images using computer vision techniques. Here the shift is from synthesis to analysis followed by synthesis.

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