Towards a Unified Multimedia Metadata Management Solution

Towards a Unified Multimedia Metadata Management Solution

Samir Amir (University of Sciences and Technologies of Lille (USTL– Lille1), France), Ioan Marius Bilasco (University of Sciences and Technologies of Lille (USTL– Lille1), France), Md. Haidar Sharif (University of Sciences and Technologies of Lille (USTL– Lille1), France) and Chabane Djeraba (University of Sciences and Technologies of Lille (USTL– Lille1), France)
DOI: 10.4018/978-1-61350-126-9.ch011
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Abstract

With increasing use of multimedia in various domains, several metadata standards appeared these last decades in order to facilitate the manipulation of multimedia contents. These standards help consumers to search content they desire and to adapt the retrieved content according to consumers’ profiles and preferences. However, in order to extract information from a given standard, a user must have a pre-knowledge about this latest. This condition is not easy to satisfy due to the increasing number of available standards. In this chapter, we introduce some of the main de facto multimedia standards that cover the description, by means of metadata, of the content and of the use context (profiles, devices, networks…). We discuss then the benefits of proposing an integrated vision of multimedia metadata standards through the usage of a generic multimedia metadata integration system, and we expose the challenges of its implementation.
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Introduction

Nowadays, with the vast expansion of the World Wide Web, several standards (such as MPEG-7(Chang, 2001), MPEG-21(Pereira, 2001), TV-Anytime (TV-Anytime Forum, 2003), etc.) have appeared for enhancing the retrieval, the usage and the delivery of multimedia data over a variety of channels (Web, TV, mobile). Those standards introduce descriptions of the content itself and of the context in which the content was created or for which the content was designed. We call these descriptions metadata as they bring new knowledge about the content and the context seen as regular data. The metadata presented in various multimedia standards describe different kinds of multimedia contents (e.g., video, image, audio, etc.), devices consuming or transmitting these contents (e.g., networks, TV, mobile, etc.), services processing or dealing with them (e.g., search, adaptation, etc.) and finally environment of user consuming these contents (e.g., user profile, user preference, etc.).

The first category of metadata presented here above, which is about content, can be found in multimedia standards such as (MPEG-7, Dublin Core (Weibel, 1998) or TV Anytime), as well as in different ongoing research projects such as the one defended by the CAM4Home Consortium1 which proposes a dedicated content description schema called CAM Core Metadata (ITEA2-CAM4Home, 2008). This kind of metadata provides explicit knowledge about the features of the content (genre, appearing concepts, etc.) and about the physical properties of the content (required bandwidth, required decoders, file size, resolution, etc.). This knowledge improves the search processes as it enriches the signal-based characterization of content, with explicit knowledge closer to user criteria (such as, meaning-full keywords). The content-related metadata can also be used in order to propose adequate adaptation processes as, depending on the type of content, specific techniques might apply better.

The last three categories presented above are about the context in which the delivery of multimedia content takes place. Standards such as MPEG-21, CC/PP (Klyne, 2004) or description schemes like CAM Supplementary Metadata schema proposed by the CAM4Home Consortium1 cover context-related information. These metadata offer knowledge that can also be injected in search, retrieval and delivery processes. While doing search, systems could benefit from the information about the user access device in order to propose content that are compatible. While doing delivery, systems can interpret the capacity of the access device and the capacity of the delivery network and it can use this information in order to adapt by simplifying accordingly the content (doing transcoding or transrating for videos, doing resolution reduction for images, doing filtering for complex documents such as web pages, etc.).

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