03278nam 2200613 450 991048063570332120170822144511.00-8218-9110-3(CKB)3360000000464089(EBL)3114401(SSID)ssj0000888921(PQKBManifestationID)11456893(PQKBTitleCode)TC0000888921(PQKBWorkID)10866997(PQKB)10241592(MiAaPQ)EBC3114401(PPN)195419189(EXLCZ)99336000000046408920150415h20112011 uy 0engur|n|---|||||txtccrExtended graphical calculus for categorified quantum sl(2) /Mikhail Khovano [and three others]Providence, Rhode Island :American Mathematical Society,2011.©20111 online resource (87 p.)Memoirs of the American Mathematical Society,0065-9266 ;Volume 219, Number 1029"September 2012, Volume 219, Number 1029 (second of 5 numbers)."0-8218-8977-X Includes bibliographical references.""Contents""; ""Abstract""; ""Chapter 1. Introduction""; ""1.1. The algebra ""; ""1.2. Categorification""; ""1.3. Diagrammatics for the Karoubi envelope ""; ""1.4. Categorification and symmetric functions""; ""1.5. Relations to other categorifications""; ""Chapter 2. Thick calculus for the nilHecke ring""; ""2.1. The nilHecke ring and its diagrammatics""; ""2.2. Boxes, thick lines, and splitters""; ""2.3. Partitions, symmetric functions, and their diagrammatics""; ""2.4. Splitter equations, explosions, and idempotents""; ""2.5. The nilHecke algebra as a matrix algebra over its center""""Chapter 3. Brief review of calculus for categorified sl(2)""""3.1. The algebra ""; ""3.2. The 2-category ""; ""3.3. Box notation for ""; ""3.4. Karoubi envelope""; ""Chapter 4. Thick calculus and ""; ""4.1. Thick lines oriented up or down""; ""4.2. Splitters as diagrams for the inclusion of a summand""; ""4.3. Adding isotopies via thick caps and cups""; ""4.4. Thin bubble slides""; ""4.5. Thick bubbles""; ""4.6. Thick bubble slides and some key lemmas""; ""Chapter 5. Decompositions of functors and other applications""; ""5.1. Decomposition of â?°^{( )}â?°^{( )}1_{ }""""5.2. Decomposition of â?°^{( )}â?±^{( )}1_{ }""""5.3. Indecomposables over â??""; ""5.4. Bases for HOMs between some 1-morphisms""; ""Bibliography""Memoirs of the American Mathematical Society ;Volume 219, Number 1029.Categories (Mathematics)Quantum groupsSymmetric functionsFinite fields (Algebra)Electronic books.Categories (Mathematics)Quantum groups.Symmetric functions.Finite fields (Algebra)512/.482Khovanov MikhailMiAaPQMiAaPQMiAaPQBOOK9910480635703321Extended graphical calculus for categorified quantum sl(2)2158590UNINA02336oam 2200409zu 450 991014100140332120241212220051.01-4244-8834-6(CKB)2670000000082935(SSID)ssj0000668748(PQKBManifestationID)12278218(PQKBTitleCode)TC0000668748(PQKBWorkID)10700406(PQKB)11308052(NjHacI)992670000000082935(EXLCZ)99267000000008293520160829d2010 uy engur|||||||||||txtccr2010 IEEE Applied Imagery Pattern Recognition Workshop[Place of publication not identified]IEEE20101 online resource illustrationsBibliographic Level Mode of Issuance: Monograph1-4244-8833-8 Activity recognition has been applied to many varied applications ranging from surveillance to medical analysis. Interpreting human actions is often a complex problem for computer vision. Actions can be classified through shape, motion or region based algorithms. While all have their distinct advantages, we consider a feature extraction approach using convexity defects. This algorithmic approach offers a unique method for identifying actions by extracting features from hull convexity defects. Specifically, we create a hull around the segmented silhouette of interest in which the regions that exist in the hull are recognized. A feature database is created through a dataset of features for multiple individuals. These feature points are registered between progressive frames and then normalized for analysis. Using Principal Component Analysis (PCA), the feature points are classified to different poses. From there testing and training is performed to observe the classification into major human activities. This approach offers a robust and accurate method to identify actions and is invariant to size and human shape.Optical pattern recognitionCongressesOptical pattern recognition006.42IEEE StaffPQKBPROCEEDING99101410014033212010 IEEE Applied Imagery Pattern Recognition Workshop2496190UNINA