Journal of Computer Sciences and Applications
ISSN (Print): 2328-7268 ISSN (Online): 2328-725X Website: http://www.sciepub.com/journal/jcsa Editor-in-chief: Minhua Ma, Patricia Goncalves
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Journal of Computer Sciences and Applications. 2019, 7(1), 1-9
DOI: 10.12691/jcsa-7-1-1
Open AccessReview Article

TV Stream Table of Content: A New Level in the Hierarchical Video Representation

Zein Al Abidin Ibrahim1,

1Lebanese University, Faculty of Sciences, Section I, Beirut, Lebanon

Pub. Date: December 28, 2018

Cite this paper:
Zein Al Abidin Ibrahim. TV Stream Table of Content: A New Level in the Hierarchical Video Representation. Journal of Computer Sciences and Applications. 2019; 7(1):1-9. doi: 10.12691/jcsa-7-1-1

Abstract

With the rapid development of nowadays technologies, TV could keep its position as one of the most important entertainment and sometimes educative utilities in our daily life. However, keeping this position required a lot of major changes to take place in order for the TV to follow up with the digital revolution, such as, digital broadcasting, High Definition TV, TV on demand. TV-REPLAY, WebTV, etc. This evolution accompanied with many other factors such as the vast spread of communication means and the low prices of storing media have all resulted in many other indispensable technologies for video content storing, structuring, searching and retrieval. Video content can be of various types: a sequence of frames, a sequence of shots, a sequence of scenes, or a sequence of programs which is what the TV stream is usually composed of. Video content structuring would be of a great benefit to help indexing searching and retrieving information from the content efficiently. For example, structuring a soccer game into Play/Break phases facilitates later the detection of goals or summarizing the soccer video. Another example is to structure a news program into stories where each story is composed of an anchorperson segment followed by a report, which facilitates later the search of a specific story or an intelligent navigation inside the news program. However, all the existing analysis methods are dedicated for one type of video content. Such methods generate very poor results if it is applied on a TV stream that is composed of several video programs. So, it is important to detect a priori the boundaries of each program and then identify the type of each program in order to run the dedicated analysis method based on the type. For a TV viewer, a TV stream is a sequence of programs (P) and breaks (B). Programs may be separated by breaks and may include also breaks. For analysis purpose, the stream can be considered as a sequence of audio and video frames with no markers of the start and end points of the included programs or breaks. Most of TV channels that produce TV streams provide a program guide about the broadcasted programs. However, such guides usually lack precision, especially with the existence of live programs which makes the prediction of their start and end very hard. Moreover, program guides do not include any information about the breaks (i.e. commercials). Hence, one of the important steps to structure TV video content is to segment it into different programs and then choose the appropriate method to segment each program separately based on its type. The TV stream structuring consists in detecting the start and end of all the programs and breaks in the stream and later trying to annotate automatically each program by some metadata that summarizes its content or identifies its type. This step can be performed by analyzing the metadata provided with the stream (EPG or EIT), or analyzing the audio-visual stream itself. In this article, we define what we call TvToC (TV stream table of content) that adds a new level in the hierarchical video decomposition (traditional video ToC). Then, we provide a comparative study of all the methods and techniques in the domain of TV stream segmentation. Besides, a comparison of the different approaches is done to highlight the advantages and the weaknesses of each of them.

Keywords:
TV stream structuring video structuring near duplicate detection classification

Creative CommonsThis work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

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