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Volume 9 / Issue 6 / Abstract

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DOI:   10.3217/jucs-009-06-0510

Unified Access to Heterogeneous Audiovisual Archives

Y. Avrithis, G. Stamou, M. Wallace
(National Technical University of Athens (NTUA), Greece
iavr@image.ntua.gr, gstam@image.ntua.gr, wallace@image.ntua.gr)

F. Marques, P. Salembier, X. Giro
(Technical University of Catalonia (UPC), Spain
ferran@gps.tsc.upc.es, philippe@gps.tsc.upc.es, xgiro@gps.tsc.upc.es)

W. Haas, H. Vallant, M. Zufferey
(Joanneum Research, Austria
werner.haas@joanneum.at, heribert.vallant@joanneum.at, michael.zufferey@joanneum.at)

Abstract: In this paper, an integrated information system is presented that offers enhanced search and retrieval capabilities to users of heterogeneous digital audiovisual (a/v) archives. This innovative system exploits the advances in handlings a/v content and related metadata, as introduced by MPEG­4 and worked out by MPEG­7, to offer advanced services characterized by the tri­fold "semantic phrasing of the request (query)", "unified handling" and "personalized response". The proposed system is targeting the intelligent extraction of semantic information from a/v and text related data taking into account the nature of the queries that users my issue, and the context determined by user profiles. It also provides a personalization process of the response in order to provide end­users with desired information. From a technical point of view, the FAETHON system plays the role of an intermediate access server residing between the end users and multiple heterogeneous audiovisual archives organized according to the new MPEG standards.

Key Words: FAETHON, audiovisual archive, MPEG­4, MPEG­7, thesaurus, search engine, semantic query, personalization, user profile.

Category: H.2.5, H.3.1, H.3.3, H.5.1

1 Introduction

Digital archiving of multimedia content including video, audio, still images and various types of documents has been recognized by content holding organizations as a mature choice for the preservation, preview and partial distribution of their assets. The advance in computer and data networks along with the success of standardization efforts of MPEG and JPEG boosted the movement of the archives towards the conversion of their fragile and manually indexed material to digital computer accessible data. By the end of the last century, the attempt has been to develop intelligent and efficient human computer interaction systems, enabling the user to access vast amounts of heterogeneous information, stored in different sites and archives. In order to achieve this objective metadata are attached to the original data.

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Current and evolving international standardization activities, such as EBU, MPEG-4 [Koenen 2002], MPEG-7 [Manjunath et al. 2002], [FDIS 2001], or JPEG2000 [JPEG 2000] for still images, deal with aspects related to data structures and metadata. In particular, the new MPEG-4 and MPEG-7 standards are object-oriented, i.e., adopt video objects as information units instead of scenes and shots. The MPEG-7 standard, formally named "Multimedia Content Description Interface", provides a rich set of standardized audiovisual Description Tools (the metadata elements and their structure and relationships, that are defined by the standard in the form of Descriptors and Description Schemes) to describe multimedia content.

The Description Schemes (DSs) of MPEG-7 are organized, on the basis of their functionality, into groups of DSs, among which the Content Management and Content Description are the most important in terms of description of multimedia documents. Content Management DSs contain information concerning the Creation / Production, Usage and Media information of the content. On the other hand, Content Description DSs are classified into structural and conceptual (semantic) DSs. The structural DSs provide a low-level and machine oriented kind of description, while conceptual DSs express a high-level and human oriented kind of description. The use of the conceptual description for searching in multimedia databases has advantages over structural description, because of its proximity to human understanding of multimedia information. Moreover, a query based on semantic entities can be personalized, taking into account the individual user's interests and preferences, which cannot be directly included in a structural query.

The FAETHON system [Avrithis and Stamou 2001] performs a semantic unification of different archives by using an encyclopaedia which contains definitions of abstract classes. Creation of the encyclopaedia relies both on human experts and existing ontologies. The system correlates the specific semantic entities of the multimedia descriptions of the individual archives to the abstract ones of the encyclopaedia. When a user makes a query, the supplied keywords are translated into the semantic entities of the encyclopaedia. The documents whose descriptions have been correlated to the requested semantic entities are retrieved, and then filtered and ranked by taking into account the user's preferences in each semantic entity.

2 The FAETHON Architecture

From a technical point of view, the overall functionality of the proposed system is to offer a unified interface that will allow end-users to have efficient access to a number of individual audiovisual archives.

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Figure 1: The FAETHON system

In this sense FAETHON acts as an intermediate agent that undertakes the tasks of (1) receiving end-users queries, (2) translating the terms of the query in a set of semantic entities by means of the knowledge of the system, (3) searching the audiovisual archives for the existence of the above semantic entities, (4) receiving the produced responses and (5) presenting the latter to the end­user in order of importance, ranking them using the user profile. The above procedure is the typical information flow in a 3­tier environment. What is innovative in this flow is the semantic level of the resolution of the users' queries.

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Figure 2: Example of the representation of a taxonomic relation's structure in the encyclopaedia.

Based on the above process, FAETHON's users will be able to issue expressive semantic queries whose answers comprise "understanding" of the involved semantic entities and rapidly converge to the focus, i.e. to what the end user has in mind, understanding the context of the query by also using the information of the user profile [Ganter and Wille 1996].

The FAETHON system enables a user to perform a single query on multiple multimedia archives and receive the results in a uniform manner. Its operation has two distinct modes: the query and the update mode (working in parallel). In the query mode FAETHON system serves its end-users by exploiting (a) its already available knowledge, (b) pre-processed information previously extracted from the audiovisual archives and (c) the on-line access to the latter using the user profile and relevance feedback. The continuous arrows in Figure 1 present the system operation in query mode. In its update mode, FAETHON system enhances its knowledge and gathers information from the audiovisual archives, processes this acquired information and stores it for subsequent use. Moreover, it updates user profiles translating the usage history into user preferences. The dotted arrows in Figure 1 present the system operation in update mode.

3 The Knowledge of the System

The knowledge of FAETHON contains the encyclopaedia and the user profiles. Among other actions, it allows:

  1. Structured storage of semantic entity descriptions and relations defined by experts.
  2. Forming complex concepts and events (composite entities) by the combination of simple ones through a set of relations.
  3. Expanding the user query by looking for related concepts to those words contained in the semantic part of the query.

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Three types of information are included in the encyclopaedia, providing the information needed for these actions: semantic entities (SEs), semantic relations (SRs) and the thesaurus.

Semantic entities are entities such as objects, events, concepts, thematic categories, agents and semantic places and times. Each semantic entity can contain textual annotation, including keywords defining the entity, sub-entities and their relations and low-level descriptors. A special kind of semantic entity is the thematic category, which corresponds to concepts such as 'sports' or 'news reports'. The purpose of this special semantic entity is to provide the context for a user's query.

Semantic relations are the relations linking related concepts as well as the relations between simple entities to allow forming composite ones. The description of all relationships among the SEs in the encyclopaedia, using the semantic relations, forms a graph structure (Figure 2). The graph nodes correspond to the SEs, whereas graph links represent the type of relationship between the nodes connected by them. This graph structure is represented in FAETHON by means of a SemanticEntities DS and a SemanticRelations DS. All relations are, in principle, fuzzy, and each relation value can be any number between 0 and 1. In practice, all relations are sparse (each entity is related to only a small number of entities), and are represented by a sparse matrix.

The thesaurus provides simplified views of the knowledge that is contained in the encyclopaedia, to be used for specific tasks. Thus, the thesaurus contains relations that are intended to facilitate query expansion, personalization, detection of thematic categories etc. The thesaurus is generated automatically from the semantic relations of the encyclopaedia. The concept of Thesaurus is unique to FAETHON and, therefore, DSs additional to those of MPEG­7 are specified.

4 Semantic Unification and Search

The role of semantic unification is to correlate the multimedia document descriptions provided by the archives with the semantic entities stored in the encyclopaedia. The result is, on one hand, the semantic index, containing the correlations between multimedia documents and semantic entities, and on the other hand, the thesaurus. The semantic unification is performed with the aid of the Detection of Thematic Categories (DTC) and the Detection of Events and Composite Objects (DECO) modules (Figure 1).

The DTC module, which is further presented in section 4.1, maps the description of a multimedia document to the set of thematic categories, and stores the relevance values in the semantic index.

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The DECO module maps the description of a multimedia document to the set of semantic entities. It is similar in operation to the DTC module, but it is capable of matching composite semantic entities (entities that contain sub-entities) to sets of consecutive DSs found in the description of the document.

The semantic index produced by DTC and DECO provides a fuzzy mapping between the set of the semantic entities of the encyclopaedia and the set of the document locators of the documents of all the archives. It therefore contains degrees of relevance between semantic entities and documents. It is used to locate documents that match the user query without searching in the archives at query time. The searching procedure takes as input the keywords that consist of the semantic part of the user's querqy and the metadata the user has provided. The processing of the user's query consists of the query interpretation and the query expansion phases. In query interpretation, each keyword is transformed into a fuzzy set defined on the set of semantic entities. On the other hand, in query expansion, the above sets are expanded using the information of the fuzzy thesaurus. Finally, the search engine uses the semantic entities involved in the expanded query and returns the associated document locators based on the information of the semantic index.

4.1 Thematic Categorization of Documents

The intelligent module of DTC accepts as input the Semantic Index I. This is in fact a fuzzy relation between documents D and semantic entities S.

I : D × S -> [0, 1]

The semantic index must be normal for each document, i.e.:

such that I(s, d) = 1

Based on this relation, and the knowledge contained in the available semantic relations Ri, the module aims to detect the degree to which a given document d D is related to a thematic category tc TC. We will refer to this degree as RTC(tc, d). In other words, the module attempts to calculate the relation:

RTC : TC x D -> [0, 1]

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Figure 3: Personalization of the archive response.

In designing an algorithm that is able to calculate this relation, in a meaningful manner, a series of issues need to be tackled:

  1. A semantic entity may be related to multiple, unrelated thematic categories.
  2. A document may be related to multiple, unrelated thematic categories.
  3. The semantic index may have been created in an automated manner. Thus, existence of random, and therefore misleading semantic entities cannot be excluded.
  4. Semantic relations are always a matter of degree. Therefore, correlation between a document and a thematic category is also a matter of degree.

According to issue 1, it is necessary for the algorithm to be able to determine which thematic categories are indeed related to a given document. In order for this task to be performed in a meaningful manner, the common meaning of the remaining entities that index the given document needs to be considered as well. This is accomplished through the consideration of the context of the document [Wallace et al. 2003]. On the other hand, when a document is related to more than one, unrelated thematic categories, as issue 2 points out, we should not expect all the terms that index it to be related to one another, or to each one of the thematic categories in question. Quite the contrary, we should expect most entities to be related to just one of these thematic categories. Therefore, a clustering of semantic entities, based on the their common meaning, needs to be applied. In this process, entities that are misleading will probably not be found similar with other entities that index a document. Therefore, the cardinality of the clusters may be used to tackle issue 3. Finally, issue 4 is easily solved by allowing the algorithm to be fuzzy.

5 Personalization

The FAETHON system is designed to simultaneously access several a/v archives. Thus, when expressing a query, users may get thousands of matches as a response; this is essentially a result of the increase in detailed metadata information that will accompany the a/v content. So a personalized view on the query result is an important issue for the system.

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User related information is fundamental to the personalization of user queries and archive responses [Soltysiak and Crabtree 1998]. FAETHON supports both passive and active user profiling. The former is an automatic update of the user profile, which is further analyzed in section 5.1, whereas the latter requires active user involvement. The user profile consists of two major parts: the user preferences and the user history, which contains the information relative to the user-FAETHON system interactions

During the registration process, the user manually specifies his profile settings consisting of metadata and semantic related preferences. For each preference, he defines a weight indicating his interests (like/dislike value). During the presentation process a ranking of the retrieved records is performed by using the user semantic preferences (audio/visual classification module) and the user metadata preferences (presentation filtering module). Each module produces independently a ranked list of documents, which are successively merged by taking into account the weighting performed by these modules and the importance of the each module itself within the personalization process. In Figure 3 this personalization process of an archive response is shown.

5.1 Extraction of User Preferences

Based on the analysis of DTC, FAETHON detects the topics that are related to each one of the documents in a user's history. Still, this does not render the problem of semantic user preference extraction trivial. What remains is the determination of the following:

  1. How should a user be modelled?
  2. Which of these topics are indeed of interest to the user, and which are found in the history due to coincidental reasons?
  3. To which degree is each one of these topics of interest to the user?

As far as the user model is concerned, main prinicples may be summarized in the following [Wallace et al. 2002]: (1) special care must be taken for the representation of negative preferences, (2) it is necessary to store negative preferences separately from positive ones, so that they may be processed separately, (3) each positive interest needs to be stored separately. As far as detection of preferences is concerned, the main points to consider may be summarized in the following: (1) A user may be interested in multiple, unrelated topics, (2) not all topics that are related to a document in the usage history are necessarily of interest to the user.

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These are tackled using similar tools and principles, as the ones used to tackle the corresponding problems in detection of thematic categories. Thus, once more, the basis on which the extraction of preferences is built is the context. The common topics of documents are used in order to determine which of them are of interest to the user and which exist in the usage history coincidentally. Extraction of metadata preferences is based on similar principles [Wallace and Stamou 2002].

6 Conclusions

This paper presented an integrated information system that offers enhanced search and retrieval capabilities to users of heterogeneous digital audiovisual archives. The proposed system focuses on intelligent extraction of semantic information from a/v and text related data taking into account the nature of the queries that users my issue, and the context determined by user profiles. It also provides a personalization process of the response.

All of the system's intelligent operations are based on a novel encyclopaedia that contains both the definitions of abstract concepts and specific events and objects (semantic entities), as well as the relations that exist among them. A first version of the FAETHON prototype, with a limited encyclopaedia, has been developed and is currently undergoing testing.

Future work includes extension of the encyclopaedia, as to cover more topics and to a greater extent. Moreover, more work shall be done towards the integration of the system with a robust implementation of the DECO module. More information on the status and goals of FAETHON can be found at the project's home page (http://www.image.ece.ntua.gr/faethon/).


This work was partially funded by the EC IST­1999­20502 FAETHON project and by the grant CICYT TIC2001­0996 of the Spanish Government.


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