04008nam 22007335 450 991029897010332120220404214026.03-662-45000-310.1007/978-3-662-45000-0(CKB)3710000000332321(EBL)1966908(OCoLC)908086378(SSID)ssj0001424475(PQKBManifestationID)11778068(PQKBTitleCode)TC0001424475(PQKBWorkID)11368474(PQKB)10542950(MiAaPQ)EBC1966908(DE-He213)978-3-662-45000-0(PPN)183518160(EXLCZ)99371000000033232120150105d2014 u| 0engur|n|---|||||txtccrFeature coding for image representation and recognition /by Yongzhen Huang, Tieniu Tan1st ed. 2014.Berlin, Heidelberg :Springer Berlin Heidelberg :Imprint: Springer,2014.1 online resource (80 p.)SpringerBriefs in Computer Science,2191-5768Description based upon print version of record.3-662-44999-4 Includes bibliographical references.1. Introduction -- 2. Taxonomy -- 3. Representative Feature Coding Algorithms -- 4. Evolution of Feature Coding -- 5. Experimental Study of Feature Coding -- 6. Enhancement via Integrating Spatial Information -- 7. Enhancement via Integrating High Order Coding Information -- 8. Conclusion.This brief presents a comprehensive introduction to feature coding, which serves as a key module for the typical object recognition pipeline. The text offers a rich blend of theory and practice while reflects the recent developments on feature coding, covering the following five aspects: (1) Review the state-of-the-art, analyzing the motivations and mathematical representations of various feature coding methods; (2) Explore how various feature coding algorithms evolve along years; (3) Summarize the main characteristics of typical feature coding algorithms and categorize them accordingly; (4) Discuss the applications of feature coding in different visual tasks, analyze the influence of some key factors in feature coding with intensive experimental studies; (5) Provide the suggestions of how to apply different feature coding methods and forecast the potential directions for future work on the topic. It is suitable for students, researchers, practitioners interested in object recognition.SpringerBriefs in Computer Science,2191-5768Pattern recognitionOptical data processingArtificial intelligenceAlgorithmsPattern Recognitionhttps://scigraph.springernature.com/ontologies/product-market-codes/I2203XImage Processing and Computer Visionhttps://scigraph.springernature.com/ontologies/product-market-codes/I22021Artificial Intelligencehttps://scigraph.springernature.com/ontologies/product-market-codes/I21000Algorithm Analysis and Problem Complexityhttps://scigraph.springernature.com/ontologies/product-market-codes/I16021Pattern recognition.Optical data processing.Artificial intelligence.Algorithms.Pattern Recognition.Image Processing and Computer Vision.Artificial Intelligence.Algorithm Analysis and Problem Complexity.004005.1006.3006.37Huang Yongzhenauthttp://id.loc.gov/vocabulary/relators/aut918911Tan Tieniuauthttp://id.loc.gov/vocabulary/relators/autBOOK9910298970103321Feature Coding for Image Representation and Recognition2060905UNINA