000			02213cam a2200325 a 4500
003			EG-GiCUC
005			20250223031200.0
008			150323s2014 ua he f m 000 0 eng d
040			_aEG-GiCUC _beng _cEG-GiCUC
041	0		_aeng
049			_aDeposite
097			_aM.Sc
099			_aCai01.13.06.M.Sc.2014.Ah.E
100	0		_aAhmed Mohamed Nagy
245	1	0	_aEnhancing 3D model reconstruction from long sequence of images / _cAhmed Mohamed Nagy ; Supervised Elsayed E. Hemayed
246	1	5	_aتحسين بناء نماذج ثلاثية الأبعاد من مجموعة كبيرة من الصور
260			_aCairo : _bAhmed Mohamed Nagy , _c2014
300			_a70 P. : _bfacsimiles , plans ; _c30cm
502			_aThesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Computer Engineering
520			_a3D models creation is one of the most attractive areas in computer vision. Robotics, gaming, simulation, virtual museums and preserving world heritage are just few examples of applications in which 3D models can be used. One of the most challenging tasks in this area is building the 3D model using set of images taken for a specific scene or object. In most practical cases, the software that intends to build the 3D model has no information about the camera movements or its internal parameters like focal length which can be all random and change from one image to another. Computer vision algorithms are applied to recover cameras projection matrices that holds information about both cameras relative movements and its internal parameters. The computational complexity of most common 3D modeling algorithm which is incremental structure from motion (SfM) is known to be of O (n⁴). In a long sequence of images extracted from video with couple of hundreds or thousands of images the computational cost of incremental SfM becomes impractical and subject to many problems
530			_aIssued also as CD
653		4	_a3D model
653		4	_aComputer vision
653		4	_aImage sequence
700	0		_aElsayed E. Hemayed , _eSupervisor
856			_uhttp://172.23.153.220/th.pdf
905			_aNazla _eRevisor
905			_aSamia _eCataloger
942			_2ddc _cTH
999			_c50009 _d50009