Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Interactive Object Segmentation for mono and stereo applications: Geodesic Prior Induced Graph Cut Energy minimization
Date
2011-11-13
Author
Tasli, H. Emrah
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
131
views
0
downloads
Cite This
This study proposes an interactive multi label object segmentation method and applications on mono and stereo images. The general segmentation problem is approached by an energy minimization on a Markov Random Field (MRF). The minimum energy potential labelling is the primary goal of the multi label segmentation algorithm. User inputs are used to determine object location and geodesic prior induced iterative graph cut energy minimization is used to define object boundaries. Segmented objects on mono images are used to generate stereo pairs for viewing on 3D displays. Segmented object pairs on stereo images are used for depth adjustment in order to achieve better visual quality. The assignment of relative depths on multiple objects is necessary for stereo image pair synthesis using conventional depth image based rendering (DIBR) techniques.
URI
https://hdl.handle.net/11511/53434
Collections
Department of Electrical and Electronics Engineering, Conference / Seminar
Suggestions
OpenMETU
Core
Depth assisted object segmentation in multi-view video
Cigla, Cevahir; Alatan, Abdullah Aydın (2008-01-01)
In this work, a novel and unified approach for multi-view video (MVV) object segmentation is presented. In the first stage, a region-based graph-theoretic color segmentation algorithm is proposed, in which the popular Normalized Cuts segmentation method is improved with some modifications on its graph structure. Segmentation is obtained by recursive bi-partitioning of a weighted graph of an initial over-segmentation mask. The available segmentation mask is also utilized during dense depth map estimation ste...
Surface Reconstruction from Multiple Images Filtering Non Lambert Regions
BÜYÜATALAY, Soner; BİRGÜL, ÖZLEM; Halıcı, Uğur (2009-09-10)
In this study a new algorithm for 3D surface reconstruction from multiple images using a modified photometric stereo method is proposed and tested. The new algorithm, Filtered Lambert Photometric Stereo (FLPS), determines the non-Lambert pixels in the available images using a linearity test and constructs filtering masks for each image that corresponds to specular and self or cast shadow regions. Then, the photometric stereo is applied after eliminating the points in these masks. Tests carried out on synthe...
Automatic image annotation by ensemble of visual descriptors
Akbaş, Emre (2007-06-22)
Automatic image annotation systems available in the literature concatenate color, texture and/or shape features in a single feature vector to learn a set of high level semantic categories using a single learning machine. This approach is quite naive to map the visual features to high level semantic information concerning the categories. Concatenation of many features with different visual properties and wide dynamical ranges may result in curse of dimensionality and redundancy problems. Additionally, it usu...
Dense depth map estimation for object segmentation in multi-view video
Çığla, Cevahir; Alatan, Abdullah Aydın; Department of Electrical and Electronics Engineering (2007)
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 w...
Performance Comparison of Different Sparse Array Configurations for Ultra-Wideband, Near-field Imaging Applications
Cetin, Beyzat Talat; Alatan, Lale (2017-03-24)
The aim of this study is to compare the performance of different multiple-input multiple-output (MIMO) array topologies, intended to be used in ultra-wideband (UWB) near-field imaging applications, by using an analysis method that does not include the effects of image reconstruction algorithm. For this purpose, maximum projection method, previously proposed for the analysis of UWB arrays under far-field conditions, is utilized and modified to obtain two way beam patterns of UWB arrays operating in the near-...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
H. E. Tasli and A. A. Alatan, “Interactive Object Segmentation for mono and stereo applications: Geodesic Prior Induced Graph Cut Energy minimization,” 2011, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/53434.