Vai al contenuto principale della pagina
Titolo: | Computer Vision - ACCV 2010 [[electronic resource] ] : 10th Asian Conference on Computer Vision, Queenstown, New Zealand, November 8-12, 2010, Revised Selected Papers, Part II / / edited by Ron Kimmel, Reinhard Klette, Akihiro Sugimoto |
Pubblicazione: | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2011 |
Edizione: | 1st ed. 2011. |
Descrizione fisica: | 1 online resource (XXI, 726 p. 384 illus., 324 illus. in color.) |
Disciplina: | 006.6 |
006.37 | |
Soggetto topico: | Optical data processing |
Pattern recognition | |
Artificial intelligence | |
Computer graphics | |
Algorithms | |
Mathematics | |
Visualization | |
Image Processing and Computer Vision | |
Pattern Recognition | |
Artificial Intelligence | |
Computer Graphics | |
Algorithm Analysis and Problem Complexity | |
Persona (resp. second.): | KimmelRon |
KletteReinhard | |
SugimotoAkihiro | |
Note generali: | Bibliographic Level Mode of Issuance: Monograph |
Nota di bibliografia: | Includes bibliographical references and index. |
Sommario/riassunto: | The four-volume set LNCS 6492-6495 constitutes the thoroughly refereed post-proceedings of the 10th Asian Conference on Computer Vision, ACCV 2009, held in Queenstown, New Zealand in November 2010. All together the four volumes present 206 revised papers selected from a total of 739 Submissions. All current issues in computer vision are addressed ranging from algorithms that attempt to automatically understand the content of images, optical methods coupled with computational techniques that enhance and improve images, and capturing and analyzing the world's geometry while preparing the higher level image and shape understanding. Novel gemometry techniques, statistical learning methods, and modern algebraic procedures are dealt with as well. |
Titolo autorizzato: | Computer Vision - ACCV 2010 |
ISBN: | 3-642-19309-9 |
Formato: | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione: | Inglese |
Record Nr.: | 996465675103316 |
Lo trovi qui: | Univ. di Salerno |
Opac: | Controlla la disponibilità qui |