Dense depth map estimation for multiple view coding

Date

2006-01-01

Author

Ozkalayci, Burak
Alatan, Abdullah Aydın

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

190
views

0
downloads

In this paper the basics of a proposed method that handles the stereo and especially multiple view coding problem in a geometrical way, are explained. For this purpose, estimation of the depth maps of the multiple views, captured by fully calibrated cameras, are done. In depth map estimation problem Markov Random Field modelling is used to have a depth map in a desired smoothness and in an efficient coding fashion. The geometric structure which is acquired by the depth map estimation, is used to reconstruct the all camera views and the PSNR values of the reconstructed images are calculated for the coding aspects.

Subject Keywords

Image reconstruction, Cameras, PSNR, Markov random fields, Image coding, Distributed decision making

URI

https://hdl.handle.net/11511/47935

DOI

https://doi.org/10.1109/siu.2006.1659761

Collections

Department of Electrical and Electronics Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

Coarse-to-Fine Isometric Shape Correspondence by Tracking Symmetric Flips Sahillioğlu, Yusuf; Yemez, Y. (2013-02-01) We address the symmetric flip problem that is inherent to multi-resolution isometric shape matching algorithms. To this effect, we extend our previous work which handles the dense isometric correspondence problem in the original 3D Euclidean space via coarse-to-fine combinatorial matching. The key idea is based on keeping track of all optimal solutions, which may be more than one due to symmetry especially at coarse levels, throughout denser levels of the shape matching process. We compare the resulting den...
Distance-based discretization of parametric signal manifolds Vural, Elif (2010-06-28) The characterization of signals and images in manifolds often lead to efficient dimensionality reduction algorithms based on manifold distance computation for analysis or classification tasks. We propose in this paper a method for the discretization of signal manifolds given in a parametric form. We present an iterative algorithm for the selection of samples on the manifold that permits to minimize the average error in the manifold distance computation. Experimental results with image appearance manifolds d...
Numerical methods for multiphysics flow problems Belenli Akbaş, Mine; Kaya Merdan, Songül; Rebholz, Leo G.; Department of Mathematics (2016) In this dissertation, efficient and reliable numerical algorithms for approximating solutions of multiphysics flow problems are investigated by using numerical methods. The interaction of multiple physical processes makes the systems complex, and two fundamental difficulties arise when attempting to obtain numerical solutions of these problems: the need for algorithms that reduce the problems into smaller pieces in a stable and accurate way and for large (sometimes intractable) amount of computational resou...
Factor graph based linear minimum mean square error equalization for wireless communications / Şen, Pınar; Yılmaz, Ali Özgür; Department of Electrical and Electronics Engineering (2014) In this work, we have studied on a reduced complexity factor graph based linear minimum mean square error (LMMSE) filter as an equalizer for different wireless communication problems. First, we introduce an efficient way of computing extrinsic bit log-likelihood ratio (LLR) values for the LMMSE estimation through the previously presented graph structure in the literature compatible with higher order alphabets. In addition, we propose to adapt this graph structure so that it has the ability of including the ...
Wavelet-based multiple description coding of 3-D geometry Norkin, Andrey; Bici, M. Oguz; Bozdağı Akar, Gözde ; Gotchev, Atanas; Astola, Jaakko (2007-02-01) In this work, we present a multiple description coding (MDC) scheme for reliable transmission of compressed three dimensional (3-D) meshes. It trades off reconstruction quality for error resilience to provide the best expected reconstruction of 3-D mesh at the decoder side. The proposed scheme is based on multiresolution geometry compression achieved by using wavelet transform and modified SPIHT algorithm. The trees of wavelet coefficients are divided into sets. Each description contains the coarsest level ...

Citation Formats

B. Ozkalayci and A. A. Alatan, “Dense depth map estimation for multiple view coding,” 2006, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/47935.