03908nam 2200625 a 450 991048494040332120200520144314.03-540-68795-510.1007/11957959(CKB)1000000000284034(SSID)ssj0000320441(PQKBManifestationID)11286220(PQKBTitleCode)TC0000320441(PQKBWorkID)10249490(PQKB)10856806(DE-He213)978-3-540-68795-5(MiAaPQ)EBC3068562(PPN)123140129(EXLCZ)99100000000028403420061109d2006 uy 0engurnn|008mamaatxtccrToward category-level object recognition /Jean Ponce ... [et al.] (eds.)1st ed. 2006.Berlin ;New York Springerc20061 online resource (XI, 620 p.) Lecture notes in computer science,0302-9743 ;4170LNCS sublibrary. SL 6, Image processing, computer vision, pattern recognition, and graphics"Outcome of two workshops that were held in Taormina in 2003 and 3004"--Pref.3-540-68794-7 Includes bibliographical references and index.pt. 1. Introduction -- pt. 2. Recognition of specific objects -- pt. 3. Recognition of object categories -- pt. 4. Recognition of object categories with geometric relations -- pt. 5. Joint recognition and segmentation.Although research in computer vision for recognizing 3D objects in photographs dates back to the 1960s, progress was relatively slow until the turn of the millennium, and only now do we see the emergence of effective techniques for recognizing object categories with different appearances under large variations in the observation conditions. Tremendous progress has been achieved in the past five years, thanks largely to the integration of new data representations, such as invariant semi-local features, developed in the computer vision community with the effective models of data distribution and classification procedures developed in the statistical machine-learning community. This volume is a post-event proceedings volume and contains selected papers based on presentations given, and vivid discussions held, during two workshops held in Taormina in 2003 and 2004. The main goals of these two workshops were to promote the creation of an international object recognition community, with common datasets and evaluation procedures, to map the state of the art and identify the main open problems and opportunities for synergistic research, and to articulate the industrial and societal needs and opportunities for object recognition research worldwide. The 30 thoroughly revised papers presented are organized in the following topical sections: recognition of specific objects, recognition of object categories, recognition of object categories with geometric relations, and joint recognition and segmentation.Lecture notes in computer science ;4170.LNCS sublibrary.SL 6,Image processing, computer vision, pattern recognition, and graphics.Computer visionCongressesPattern recognition systemsCongressesImage processingDigital techniquesCongressesObject-oriented methods (Computer science)CongressesComputer visionPattern recognition systemsImage processingDigital techniquesObject-oriented methods (Computer science)006.3/7Ponce Jean66811MiAaPQMiAaPQMiAaPQBOOK9910484940403321Toward category-level object recognition4187265UNINA