Face Detection and Gesture Recognition for Human-Computer Interaction:
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:
| Hauptverfasser: | , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
New York, NY
Springer US
2001
|
| Ausgabe: | 1st ed. 2001 |
| Schriftenreihe: | The International Series in Video Computing
1 |
| 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 analyzing image sequences, or video understanding. Video understanding deals with understanding of video sequences, e. g. , recognition of gestures, activities, facial 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 (XII, 182 p) |
| ISBN: | 9781461514237 |
| DOI: | 10.1007/978-1-4615-1423-7 |
Internformat
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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 analyzing image sequences, or video understanding. Video understanding deals with understanding of video sequences, e. g. , recognition of gestures, activities, facial 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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Datensatz im Suchindex
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| author | Ming-Hsuan Yang Ahuja, Narendra |
| author_facet | Ming-Hsuan Yang Ahuja, Narendra |
| author_role | aut aut |
| author_sort | Ming-Hsuan Yang |
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| dewey-full | 006.37 006.6 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 006 - Special computer methods |
| dewey-raw | 006.37 006.6 |
| dewey-search | 006.37 006.6 |
| dewey-sort | 16.37 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| discipline_str_mv | Informatik |
| doi_str_mv | 10.1007/978-1-4615-1423-7 |
| edition | 1st ed. 2001 |
| format | Electronic eBook |
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| id | DE-604.BV047064224 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T16:12:22Z |
| indexdate | 2024-07-10T09:01:34Z |
| institution | BVB |
| isbn | 9781461514237 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-032471336 |
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| spelling | Ming-Hsuan Yang Verfasser aut Face Detection and Gesture Recognition for Human-Computer Interaction by Ming-Hsuan Yang, Narendra Ahuja 1st ed. 2001 New York, NY Springer US 2001 1 Online-Ressource (XII, 182 p) txt rdacontent c rdamedia cr rdacarrier The International Series in Video Computing 1 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 analyzing image sequences, or video understanding. Video understanding deals with understanding of video sequences, e. g. , recognition of gestures, activities, facial 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 User Interfaces and Human Computer Interaction Computer Imaging, Vision, Pattern Recognition and Graphics Artificial Intelligence Mechanical Engineering Optical data processing User interfaces (Computer systems) Artificial intelligence Mechanical engineering Bildverarbeitung (DE-588)4006684-8 gnd rswk-swf Gesicht (DE-588)4020687-7 gnd rswk-swf Gestik (DE-588)4157167-8 gnd rswk-swf Automatische Identifikation (DE-588)4206098-9 gnd rswk-swf Gesicht (DE-588)4020687-7 s Gestik (DE-588)4157167-8 s Automatische Identifikation (DE-588)4206098-9 s Bildverarbeitung (DE-588)4006684-8 s DE-604 Ahuja, Narendra aut Erscheint auch als Druck-Ausgabe 9780792374091 Erscheint auch als Druck-Ausgabe 9781461355465 Erscheint auch als Druck-Ausgabe 9781461514244 https://doi.org/10.1007/978-1-4615-1423-7 Verlag URL des Eerstveröffentlichers Volltext |
| spellingShingle | Ming-Hsuan Yang Ahuja, Narendra Face Detection and Gesture Recognition for Human-Computer Interaction Image Processing and Computer Vision User Interfaces and Human Computer Interaction Computer Imaging, Vision, Pattern Recognition and Graphics Artificial Intelligence Mechanical Engineering Optical data processing User interfaces (Computer systems) Artificial intelligence Mechanical engineering Bildverarbeitung (DE-588)4006684-8 gnd Gesicht (DE-588)4020687-7 gnd Gestik (DE-588)4157167-8 gnd Automatische Identifikation (DE-588)4206098-9 gnd |
| subject_GND | (DE-588)4006684-8 (DE-588)4020687-7 (DE-588)4157167-8 (DE-588)4206098-9 |
| title | Face Detection and Gesture Recognition for Human-Computer Interaction |
| title_auth | Face Detection and Gesture Recognition for Human-Computer Interaction |
| title_exact_search | Face Detection and Gesture Recognition for Human-Computer Interaction |
| title_exact_search_txtP | Face Detection and Gesture Recognition for Human-Computer Interaction |
| title_full | Face Detection and Gesture Recognition for Human-Computer Interaction by Ming-Hsuan Yang, Narendra Ahuja |
| title_fullStr | Face Detection and Gesture Recognition for Human-Computer Interaction by Ming-Hsuan Yang, Narendra Ahuja |
| title_full_unstemmed | Face Detection and Gesture Recognition for Human-Computer Interaction by Ming-Hsuan Yang, Narendra Ahuja |
| title_short | Face Detection and Gesture Recognition for Human-Computer Interaction |
| title_sort | face detection and gesture recognition for human computer interaction |
| topic | Image Processing and Computer Vision User Interfaces and Human Computer Interaction Computer Imaging, Vision, Pattern Recognition and Graphics Artificial Intelligence Mechanical Engineering Optical data processing User interfaces (Computer systems) Artificial intelligence Mechanical engineering Bildverarbeitung (DE-588)4006684-8 gnd Gesicht (DE-588)4020687-7 gnd Gestik (DE-588)4157167-8 gnd Automatische Identifikation (DE-588)4206098-9 gnd |
| topic_facet | Image Processing and Computer Vision User Interfaces and Human Computer Interaction Computer Imaging, Vision, Pattern Recognition and Graphics Artificial Intelligence Mechanical Engineering Optical data processing User interfaces (Computer systems) Artificial intelligence Mechanical engineering Bildverarbeitung Gesicht Gestik Automatische Identifikation |
| url | https://doi.org/10.1007/978-1-4615-1423-7 |
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