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
A Graph-Based Approach for Video Scene Detection
Date
2008-04-22
Author
Sakarya, Ufuk
Telatar, Zjya
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
215
views
0
downloads
Cite This
In this paper, a graph-based method for video scene detection is proposed. The method is based on a weighted undirected graph. Each shot is a vertex on the graph. Edge weights among the vertices are evaluated by using spatial and temporal similarities of shots. By using the complete information of the graph, a set of the vertices mostly similar to each other and dissimilar to the others is detected. Temporal continuity constraint is achieved on this set. This set is the first detected video scene. The vertices of the video scene are extracted from the graph and the process is repeated by a certain number. The certain number of the video scenes whose boundaries are determined are placed in the temporal domain. Each temporal pail between two detected scenes is accepted as a video scene.
Subject Keywords
Segmentation
URI
https://hdl.handle.net/11511/64606
DOI
https://doi.org/10.1109/siu.2008.4632545
Collections
Unclassified, Conference / Seminar
Suggestions
OpenMETU
Core
An image retrieval system based on region classification
Ozcanli, OC; Yarman-Vural, F (2004-01-01)
In this study, a content based image retrieval (CBIR) system to query the objects in an image database is proposed. Images are represented as collections of regions after being segmented with Normalized Cuts algorithm. MPEG-7 content descriptors are used to encode regions in a 239-dimensional feature space. User of the proposed CBIR system decides which objects to query and labels exemplar regions to train the system using a graphical interface. Fuzzy ARTMAP algorithm is used to learn the mapping between fe...
A Trie-structured Bayesian Model for Unsupervised Morphological Segmentation
Kurfalı, Murathan; Ustun, Ahmet; CAN BUĞLALILAR, BURCU (2017-04-23)
In this paper, we introduce a trie-structured Bayesian model for unsupervised morphological segmentation. We adopt prior information from different sources in the model. We use neural word embeddings to discover words that are morphologically derived from each other and thereby that are semantically similar. We use letter successor variety counts obtained from tries that are built by neural word embeddings. Our results show that using different information sources such as neural word embeddings and letter s...
Prediction of multiphase flow properties from nuclear magnetic resonance imaging
Karaman, Türker; Akın, Serhat; Department of Petroleum and Natural Gas Engineering (2009)
In this study a hybrid Pore Network (PN) model that simulates two-phase (water-oil) drainage and imbibition mechanisms is developed. The developed model produces Nuclear Magnetic Resonance (NMR) T2 relaxation times using correlations available in the literature. The developed PN was calibrated using experimental relative permeability data obtained for Berea Sandstone, Kuzey Marmara Limestone, Yeniköy Dolostone and Dolomitic Limestone core plugs. Pore network body and throat parameters were obtained from ser...
QUALITY EVALUATION OF STEREOSCOPIC VIDEOS USING DEPTH MAP SEGMENTATION
Sarikan, Selim S.; Olgun, Ramazan F.; Akar, Gözde (2011-09-09)
This paper presents a new quality evaluation model for stereoscopic videos using depth map segmentation. This study includes both objective and subjective evaluation. The goal of this study is to understand the effect of different depth levels on the overall 3D quality. Test sequences with different coding schemes are used. The results show that overall quality has a strong correlation with the quality of the background, where disparity is smaller relative to the foreground. The results also showed that con...
Image segmentation with unified region and boundary characteristics within recursive shortest spanning tree
Esen, E.; Alp, Y. K. (2007-06-13)
The lack of boundary information in region based image segmentation algorithms resulted in many hybrid methods that integrate the complementary information sources of region and boundary, in order to increase the segmentation performance. In compliance with this trend, we propose a novel method to unify the region and boundary characteristics within the canonical Recursive Shortest Spanning Tree algorithm. The main idea is to incorporate the boundary information in the distance metric of RSST with minor cha...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
U. Sakarya and Z. Telatar, “A Graph-Based Approach for Video Scene Detection,” 2008, p. 34, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/64606.