Automatic video categorization and summarization

Download

index.pdf

Date

2009

Author

Demirtaş, Kezban

Metadata

Show full item record

Item Usage Stats

160
views

49
downloads

In this thesis, we make automatic video categorization and summarization by using subtitles of videos. We propose two methods for video categorization. The first method makes unsupervised categorization by applying natural language processing techniques on video subtitles and uses the WordNet lexical database and WordNet domains. The method starts with text preprocessing. Then a keyword extraction algorithm and a word sense disambiguation method are applied. The WordNet domains that correspond to the correct senses of keywords are extracted. Video is assigned a category label based on the extracted domains. The second method has the same steps for extracting WordNet domains of video but makes categorization by using a learning module. Experiments with documentary videos give promising results in discovering the correct categories of videos. Video summarization algorithms present condensed versions of a full length video by identifying the most significant parts of the video. We propose a video summarization method using the subtitles of videos and text summarization techniques. We identify significant sentences in the subtitles of a video by using text summarization techniques and then we compose a video summary by finding the video parts corresponding to these summary sentences.

Subject Keywords

Computer enginnering., Communication of technical information.

URI

http://etd.lib.metu.edu.tr/upload/3/12611113/index.pdf
https://hdl.handle.net/11511/18824

Collections

Graduate School of Natural and Applied Sciences, Thesis

Suggestions

OpenMETU
Core

Automatic categorization and summarization of documentaries Demirtas, Kezban; Çiçekli, Fehime Nihan; ÇİÇEKLİ, İLYAS (2010-12-01) In this paper, we propose automatic categorization and summarization of documentaries using subtitles of videos. We propose two methods for video categorization. The first makes unsupervised categorization by applying natural language processing techniques on video subtitles and uses the WordNet lexical database and WordNet domains. The second has the same extraction steps but uses a learning module to categorize. Experiments with documentary videos give promising results in discovering the correct categori...
Hanolistic : a hierarchical automatic image annotation system using holistic approach Öztimur, Özge; Yarman Vural, Fatoş Tunay; Department of Computer Engineering (2008) Automatic image annotation is the process of assigning keywords to digital images depending on the content information. In one sense, it is a mapping from the visual content information to the semantic context information. In this thesis, we propose a novel approach for automatic image annotation problem, where the annotation is formulated as a multivariate mapping from a set of independent descriptor spaces, representing a whole image, to a set of words, representing class labels. For this purpose, a hiera...
Automatic web service composition with ai planning Kuzu, Mehmet; Çiçekli, Fehime Nihan; Department of Computer Engineering (2009) In this thesis, some novel ideas are presented for solving automated web service composition problem. Some possible real world problems such as partial observability of environment, nondeterministic effects of web services, service execution failures are solved through some mechanisms. In addition to automated web service composition, automated web service invocation task is handled in this thesis by using reflection mechanism. The proposed approach is based on AI planning. Web service composition problem i...
Automatic image annotation by ensemble of visual descriptors Akbaş, Emre; Yarman Vural, Fatoş Tunay; Department of Computer Engineering (2006) Automatic image annotation is the process of automatically producing words to de- scribe the content for a given image. It provides us with a natural means of semantic indexing for content based image retrieval. In this thesis, two novel automatic image annotation systems targeting dierent types of annotated data are proposed. The rst system, called Supervised Ensemble of Visual Descriptors (SEVD), is trained on a set of annotated images with predened class labels. Then, the system auto- matically annotates...
Exploiting information extraction techniques for automatic semantic video indexing with an application to Turkish news videos Kucuk, Dilek; Yazıcı, Adnan (Elsevier BV, 2011-08-01) This paper targets at the problem of automatic semantic indexing of news videos by presenting a video annotation and retrieval system which is able to perform automatic semantic annotation of news video archives and provide access to the archives via these annotations. The presented system relies on the video texts as the information source and exploits several information extraction techniques on these texts to arrive at representative semantic information regarding the underlying videos. These techniques ...

Citation Formats

K. Demirtaş, “Automatic video categorization and summarization,” M.S. - Master of Science, Middle East Technical University, 2009.