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Comparative study for human activity recognition techniques / Amira Ali Bebars Ali ; Supervised Elsayed E. Hemayed

By: Contributor(s): Material type: TextTextLanguage: English Publication details: Cairo : Amira Ali Bebars Ali , 2014Description: 73 P. : facsimiles , photographs ; 30cmOther title:
  • دراسة مقارنة لطرق التعرف على النشاط البشرى [Added title page title]
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  • Issued also as CD
Dissertation note: Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Computer Engineering Summary: Human activity recognition is an active area of research in computer vision with wide scale applications in video surveillance, motion analysis, and virtual reality interfaces, robot navigation and recognition, sports video analysis etc. It consists of analyzing the characteristic features of various human actions and classifying them. Part - based approach is the main focus of this thesis, a general human action recognition framework that includes spatio - temporal interest point detection, building the descriptor, constructing the codebook, and testing on the pre - trained classifier. We focus on; detectors for accurately detecting the humman action, descriptors to describe information around interest points, and classifiers for performing accurate classification
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Item type Current library Home library Call number Copy number Status Barcode
Thesis Thesis قاعة الرسائل الجامعية - الدور الاول المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.13.06.M.Sc.2014.Am.C (Browse shelf(Opens below)) Not for loan 01010110063799000
CD - Rom CD - Rom مخـــزن الرســائل الجـــامعية - البدروم المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.13.06.M.Sc.2014.Am.C (Browse shelf(Opens below)) 63799.CD Not for loan 01020110063799000

Thesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Computer Engineering

Human activity recognition is an active area of research in computer vision with wide scale applications in video surveillance, motion analysis, and virtual reality interfaces, robot navigation and recognition, sports video analysis etc. It consists of analyzing the characteristic features of various human actions and classifying them. Part - based approach is the main focus of this thesis, a general human action recognition framework that includes spatio - temporal interest point detection, building the descriptor, constructing the codebook, and testing on the pre - trained classifier. We focus on; detectors for accurately detecting the humman action, descriptors to describe information around interest points, and classifiers for performing accurate classification

Issued also as CD

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