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| 003 | EG-GiCUC | ||
| 005 | 20250223031059.0 | ||
| 008 | 141026s2014 ua ho f m 000 0 eng d | ||
| 040 |
_aEG-GiCUC _beng _cEG-GiCUC |
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| 041 | 0 | _aeng | |
| 049 | _aDeposite | ||
| 097 | _aM.Sc | ||
| 099 | _aCai01.13.06.M.Sc.2014.Am.C | ||
| 100 | 0 | _aAmira Ali Bebars Ali | |
| 245 | 1 | 0 |
_aComparative study for human activity recognition techniques / _cAmira Ali Bebars Ali ; Supervised Elsayed E. Hemayed |
| 246 | 1 | 5 | _aدراسة مقارنة لطرق التعرف على النشاط البشرى |
| 260 |
_aCairo : _bAmira Ali Bebars Ali , _c2014 |
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| 300 |
_a73 P. : _bfacsimiles , photographs ; _c30cm |
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| 502 | _aThesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Computer Engineering | ||
| 520 | _aHuman 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 | ||
| 530 | _aIssued also as CD | ||
| 653 | 4 | _aHuman activity recognition | |
| 653 | 4 | _aMOSIFT descriptor | |
| 653 | 4 | _aMOSIFT detector | |
| 700 | 0 |
_aElsayed Eisa Hemayed , _eSupervisor |
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| 856 | _uhttp://172.23.153.220/th.pdf | ||
| 905 |
_aNazla _eRevisor |
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| 905 |
_aSamia _eCataloger |
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| 942 |
_2ddc _cTH |
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_c47951 _d47951 |
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