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
Multilingual Video Indexing and Retrieval Employing an Information Extraction Tool for Turkish News Texts: A Case Study
Date
2011-10-28
Author
Kucuk, Dilek
Yazıcı, Adnan
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
164
views
0
downloads
Cite This
In this paper, a multilingual video indexing and retrieval system is proposed which relies on an information extraction tool, a hybrid named entity recognizer, for Turkish to determine the semantic annotations for the considered videos. The system is executed on a set of news videos in English and encompasses several other components including an automatic speech recognition system for English, an English-to-Turkish machine translation system, a news video database, and a semantic video retrieval interface. The performance evaluation demonstrates that the system components achieve promising results which provides evidence for the applicability of the system. The proposed system and its application on the video set are significant as they constitute a plausible case study targeting at the problem of multilingual video indexing and retrieval utilizing information extraction as the central technique for semantic video indexing.
Subject Keywords
Machine translation
,
Automatic speech recognition
,
News video
,
Video retrieval
,
Automatic speech recognition system
URI
https://hdl.handle.net/11511/52926
Conference Name
9th International Conference on Flexible Query Answering Systems (FQAS 2011)
Collections
Department of Computer Engineering, Conference / Seminar
Suggestions
OpenMETU
Core
Bimodal automatic speech segmentation based on audio and visual information fusion
Akdemir, Eren; Çiloğlu, Tolga (2011-07-01)
Bimodal automatic speech segmentation using visual information together with audio data is introduced. The accuracy of automatic segmentation directly affects the quality of speech processing systems using the segmented database. The collaboration of audio and visual data results in lower average absolute boundary error between the manual segmentation and automatic segmentation results. The information from two modalities are fused at the feature level and used in a HMM based speech segmentation system. A T...
Ontological Video Annotation and Querying System for Soccer Games
Alan, Ozgur; Akpinar, Samet; Sabuncu, Orkunt; Cicekli, Nihan; Alpaslan, Ferda Nur (2008-10-29)
This paper describes a video annotation and querying system which is capable of semi-automatic annotation of videos from text. The extracted metadata is aligned with the corresponding video segments. This allows users to query videos according to their semantic content. We have chosen soccer domain to demonstrate the use of the system. The soccer videos are very suitable for our framework, since it is easy to find web-cast match reports for soccer games. The annotated videos are stored in MPEG-7 format in a...
An antology - driven video annotation and retrieval system
Demirdizen, Goncagül; Çiçekli, Fehime Nihan; Department of Computer Engineering (2010)
In this thesis, a system, called Ontology-Driven Video Annotation and Retrieval System (OntoVARS) is developed in order to provide a video management system which is used for ontology-driven semantic content annotation and querying. The proposed system is based on MPEG-7 ontology which provides interoperability and common communication platform with other MPEG-7 ontology compatible systems. The Rhizomik MPEG-7 ontology is used as the core ontology and domain specific ontologies are integrated to the core on...
Text Classification in the Turkish Marketing Domain for Context Sensitive Ad Distribution
Engin, Melih; Can, Tolga (2009-09-16)
In this paper, we construct and compare several feature extraction approaches in order to find a better solution for classification of Turkish web documents in the marketing domain. We produce our feature extraction techniques using characteristics of the Turkish language, structures of web documents and online content in the marketing domain. We form datasets in different feature spaces and we apply several Support Vector Machine (SVM) configurations on these datasets. We conduct our study considering the ...
FEATURE ENCODING MODELS FOR GEOGRAPHIC IMAGE RETRIEVAL AND CATEGORIZATION
Ozkan, Savas; Ates, Tayfun; Tola, Engin; Soysal, Medeni; Esen, Ersin (2014-04-25)
In this work, we survey the perormance of various feature encoding models for geographic image retrieval task Recently introduced Vector-of-Locally-Aggregated Descriptors (VLAD) and its Product Quantization encoded binary version VLAD-PQ are compared with the widely used Bag-of-Word (BoW) model. Evaluation results are shown on a publicly available 21-class LULC dataset. With experiments, it is shown that VLAD outperforms classical BoW representation albeit with some increases in the computation time. Additi...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
D. Kucuk and A. Yazıcı, “Multilingual Video Indexing and Retrieval Employing an Information Extraction Tool for Turkish News Texts: A Case Study,” Ghent, Belgium, 2011, vol. 7022, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/52926.
