Media Computing: Computational Media Aesthetics
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...
Gespeichert in:
| Weitere Verfasser: | , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
New York, NY
Springer US
2002
|
| Ausgabe: | 1st ed. 2002 |
| Schriftenreihe: | The International Series in Video Computing
4 |
| Schlagworte: | |
| Online-Zugang: | UBY01 Volltext |
| Zusammenfassung: | 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 |
| Beschreibung: | 1 Online-Ressource (XXIII, 198 p) |
| ISBN: | 9781461511199 |
| DOI: | 10.1007/978-1-4615-1119-9 |
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| 520 | |a 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 | ||
| 650 | 4 | |a Image Processing and Computer Vision | |
| 650 | 4 | |a Data Structures and Information Theory | |
| 650 | 4 | |a Computer Imaging, Vision, Pattern Recognition and Graphics | |
| 650 | 4 | |a Multimedia Information Systems | |
| 650 | 4 | |a Information Storage and Retrieval | |
| 650 | 4 | |a Optical data processing | |
| 650 | 4 | |a Data structures (Computer science) | |
| 650 | 4 | |a Multimedia information systems | |
| 650 | 4 | |a Information storage and retrieval | |
| 700 | 1 | |a Dorai, Chitra |4 edt | |
| 700 | 1 | |a Venkatesh, Svetha |4 edt | |
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| discipline | Informatik |
| discipline_str_mv | Informatik |
| doi_str_mv | 10.1007/978-1-4615-1119-9 |
| edition | 1st ed. 2002 |
| format | Electronic eBook |
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| illustrated | Not Illustrated |
| index_date | 2024-07-03T16:12:22Z |
| indexdate | 2024-07-10T09:01:34Z |
| institution | BVB |
| isbn | 9781461511199 |
| language | English |
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| spelling | Media Computing Computational Media Aesthetics edited by Chitra Dorai, Svetha Venkatesh 1st ed. 2002 New York, NY Springer US 2002 1 Online-Ressource (XXIII, 198 p) txt rdacontent c rdamedia cr rdacarrier The International Series in Video Computing 4 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 Image Processing and Computer Vision Data Structures and Information Theory Computer Imaging, Vision, Pattern Recognition and Graphics Multimedia Information Systems Information Storage and Retrieval Optical data processing Data structures (Computer science) Multimedia information systems Information storage and retrieval Dorai, Chitra edt Venkatesh, Svetha edt Erscheint auch als Druck-Ausgabe 9781461354031 Erscheint auch als Druck-Ausgabe 9781402071027 Erscheint auch als Druck-Ausgabe 9781461511205 https://doi.org/10.1007/978-1-4615-1119-9 Verlag URL des Eerstveröffentlichers Volltext |
| spellingShingle | Media Computing Computational Media Aesthetics Image Processing and Computer Vision Data Structures and Information Theory Computer Imaging, Vision, Pattern Recognition and Graphics Multimedia Information Systems Information Storage and Retrieval Optical data processing Data structures (Computer science) Multimedia information systems Information storage and retrieval |
| title | Media Computing Computational Media Aesthetics |
| title_auth | Media Computing Computational Media Aesthetics |
| title_exact_search | Media Computing Computational Media Aesthetics |
| title_exact_search_txtP | Media Computing Computational Media Aesthetics |
| title_full | Media Computing Computational Media Aesthetics edited by Chitra Dorai, Svetha Venkatesh |
| title_fullStr | Media Computing Computational Media Aesthetics edited by Chitra Dorai, Svetha Venkatesh |
| title_full_unstemmed | Media Computing Computational Media Aesthetics edited by Chitra Dorai, Svetha Venkatesh |
| title_short | Media Computing |
| title_sort | media computing computational media aesthetics |
| title_sub | Computational Media Aesthetics |
| topic | Image Processing and Computer Vision Data Structures and Information Theory Computer Imaging, Vision, Pattern Recognition and Graphics Multimedia Information Systems Information Storage and Retrieval Optical data processing Data structures (Computer science) Multimedia information systems Information storage and retrieval |
| topic_facet | Image Processing and Computer Vision Data Structures and Information Theory Computer Imaging, Vision, Pattern Recognition and Graphics Multimedia Information Systems Information Storage and Retrieval Optical data processing Data structures (Computer science) Multimedia information systems Information storage and retrieval |
| url | https://doi.org/10.1007/978-1-4615-1119-9 |
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