Dense depth map estimation for object segmentation in multi-view video

Çığla, Cevahir
In this thesis, novel approaches for dense depth field estimation and object segmentation from mono, stereo and multiple views are presented. In the first stage, a novel graph-theoretic color segmentation algorithm is proposed, in which the popular Normalized Cuts 59H[6] segmentation algorithm is improved with some modifications on its graph structure. Segmentation is obtained by the recursive partitioning of the weighted graph. The simulation results for the comparison of the proposed segmentation scheme with some well-known segmentation methods, such as Recursive Shortest Spanning Tree 60H[3] and Mean-Shift 61H[4] and the conventional Normalized Cuts, show clear improvements over these traditional methods. The proposed region-based approach is also utilized during the dense depth map estimation step, based on a novel modified plane- and angle-sweeping strategy. In the proposed dense depth estimation technique, the whole scene is assumed to be region-wise planar and 3D models of these plane patches are estimated by a greedy-search algorithm that also considers visibility constraint. In order to refine the depth maps and relax the planarity assumption of the scene, at the final step, two refinement techniques that are based on region splitting and pixel-based optimization via Belief Propagation 62H[32] are also applied. Finally, the image segmentation algorithm is extended to object segmentation in multi-view video with the additional depth and optical flow information. Optical flow estimation is obtained via two different methods, KLT tracker and region-based block matching and the comparisons between these methods are performed. The experimental results indicate an improvement for the segmentation performance by the usage of depth and motion information.


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Kalyoncu, Özden; SÜnver, Zafer; Department of Electrical and Electronics Engineering (2007)
In this thesis work, time-frequency filtering of nonstationary signals in noise using Wigner-Ville Distribution is investigated. Continuous-time, discrete-time and discrete Wigner Ville Distribution definitions, their relations, and properties are given. Time-Frequency Peak Filtering Method is presented. The effects of different parameters on the performance of the method are investigated, and the results are presented. Time-Varying Wiener Filter is presented. Using simulations it is shown that the performa...
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Yaşar, Temel Kaya; Tuncer, Temel Engin; Department of Electrical and Electronics Engineering (2006)
In this thesis a new approach is proposed for non-uniform linear arrays (NLA) which employs conventional subspace methods to improve the direction of arrival (DOA) estimation performance. Uniform linear arrays (ULA) are composed of evenly spaced sensor elements located on a straight line. ULA's covariance matrix have a Vandermonde matrix structure, which is required by fast subspace DOA estimation algorithms. NLA differ from ULA only by some missing sensor elements. These missing elements cause some gaps in...
FPGA implementation of graph cut method for real time stereo matching
Sağlık Özsaraç, Havva; Ünver, Baki Zafer; Ulusoy, İlkay; Department of Electrical and Electronics Engineering (2010)
The present graph cut methods cannot be used directly for real time stereo matching applications because of their recursive structure. Graph cut method is modified to change its recursive structure so that making it suitable for real time FPGA (Field Programmable Gate Array) implementation. The modified method is firstly tested by MATLAB on several data sets, and the results are compared with those of previous studies. Although the disparity results of the modified method are not better than other methods’,...
A comparative performance evaluation of scale invariant interest point detectors for infrared and visual images
Emir, Erdem; Alatan, Abdullah Aydın; Department of Electrical and Electronics Engineering (2008)
In this thesis, the performance of four state-of-the-art feature detectors along with SIFT and SURF descriptors in matching object features of mid-wave infrared, long-wave infrared and visual-band images is evaluated across viewpoints and changing distance conditions. The utilized feature detectors are Scale Invariant Feature Transform (SIFT), multiscale Harris-Laplace, multiscale Hessian-Laplace and Speeded Up Robust Features (SURF) detectors, all of which are invariant to image scale and rotation. Feature...
RF coil system design for MRI applications inhomogeneous main magnetic field
Yılmaz, Ayhan Ozan; Aşkar, Murat; Department of Electrical and Electronics Engineering (2007)
In this study, RF coil geometries are designed for MRI applications using inhomogeneous main magnetic fields. The current density distributions that can produce the desired RF magnetic field characteristics are obtained on predefined cubic, cylindrical and planar surfaces and Tikhonov, CGLS, TSVD and Rutisbauer regularization methods are applied to match the desired and generated magnetic fields. The conductor paths, which can produce the current density distribution calculated for each surface selection an...
Citation Formats
C. Çığla, “Dense depth map estimation for object segmentation in multi-view video,” M.S. - Master of Science, Middle East Technical University, 2007.