Moving Object Detction in 2D and 3D Scenes

Sırtkaya, Salim
This thesis describes the theoretical bases, development and testing of an integrated moving object detection framework in 2D and 3D scenes. The detection problem is analyzed in stationary and non-stationary camera sequences and different algorithms are developed for each case. Two methods are proposed in stationary camera sequences: background extraction followed by differencing and thresholding, and motion detection using optical flow field calculated by أKanade-Lucas Feature Trackerؤ. For non-stationary camera sequences, different algorithms are developed based on the scene structure and camera motion characteristics. In planar scenes where the scene is flat or distant from the camera and/or when camera makes rotations only, a method is proposed that uses 2D parametric registration based on affine parameters of the dominant plane for independently moving object detection. A modified version of the 2D parametric registration approach is used when the scene is not planar but consists of a few number of planes at different depths, and camera makes translational motion. Optical flow field segmentation and sequential registration are the key points for this case. For 3D scenes, where the depth variation within the scene is high, a parallax rigidity based approach is developed for moving object detection. All these algorithms are integrated to form a unified independently moving object detector that works in stationary and non-stationary camera sequences and with different scene and camera motion structures. Optical flow field estimation and segmentation is used for this purpose.


3D face recognition
Üstün, Bülend; Halıcı, Uğur; Department of Electrical and Electronics Engineering (2007)
In this thesis, the effect of registration process is evaluated as well as several methods proposed for 3D face recognition. Input faces are in point cloud form and have noises due to the nature of scanner technologies. These inputs are noise filtered and smoothed before registration step. In order to register the faces an average face model is obtained from all the images in the database. All the faces are registered to the average model and stored to the database. Registration is performed by using a rigi...
3D fracture network dynamics in reservoirs, faults and salt tectonic systems
Tuncay, Kağan; Payne, D; Ortoleva, P (2003-01-01)
A unique 3D computer simulator is used to predict natural fracture network characteristics in the subsurface. The model is based on the numerical solution of rock deformation processes coupled to the myriad of other basin reaction, transport and mechanical (RTM) processes. The model integrates seismic, well log and surface geological data to arrive at a quantitative picture of the distribution of fractures, stress, petroleum and porosity, grain size and other textural information. An important component of...
Numerical investigation of rotor wake-stator interaction
Gürak, Derya; Akmandor, İbrahim Sinan; Department of Aerospace Engineering (2004)
In this thesis, numerical solutions of a 2D stator compressor cascade at a given inlet Mach number (0.7) and four values of incidence (49°, 51°, 53° and 55°) are obtained. Reynolds averaged, thin layer, compressible Navier Stokes equations are solved. Different grid types have been generated. Finite differencing approach and LU - ADI splitting technique are used. Three block parallel Euler and Navier Stokes solutions are compared with the experimental results. Baldwin-Lomax turbulence model is used in the t...
Properties of BaYO3 perovskite and hydrogen storage properties of BaYO3Hx
Gencer, Ayşenur; Surucu, Gokhan (Elsevier BV, 2020-03-27)
In this study, Density Functional Theory (DFT) calculations have been performed for BaYO3 perovskite with the generalized gradient approximation (GGA) as implemented in Vienna Ab-initio Simulation Package (VASP). The structural optimization of BaYO3 perovskite have been studied for the five possible phases: cubic, tetragonal, hexagonal, orthorhombic and rhombohedral to determine the most stable phase of BaYO3 perovskite. It has been found that the cubic phase is the most stable one and electronic and mechan...
Well test model identification by artificial neural networks
Kök, Mustafa Verşan (Informa UK Limited, 2000-01-01)
The aim of this research is to investigate the performance of artificial neural networks computing technology, to identify preliminary well test interpretation model based on derivative plot. The approach is based on training the neural network simulator uses back-propagation as the learning algorithm for a predefined range of analytically generated well test response. The trained network is then requested to identify the well test identification model for test data, which is not used during training sessio...
Citation Formats
S. Sırtkaya, “Moving Object Detction in 2D and 3D Scenes,” M.S. - Master of Science, Middle East Technical University, 2004.