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Table of contents

The AREM approach has been experimentally verified by practical application of the AREPS system in a number scenarios across the cultural heritage and education domains. Factors that stimulate development of such environments are: A limiting factor is the high cost of creation, maintenance and development of interactive 3D content for multiuser virtual environments.

A commonly recognized solution to this problem is user-generated content. Such content is not only cheaper to develop but also more authentic and closer to users.

Introduction to Interactive 3D Multimedia Content

Therefore, modern virtual environments are not only multiuser and multi-access but also interactive, behavior-rich, highly dynamic and based on user-contributed content. Traditional, coarse-grained and geometry-centric access control and privilege modeling methods are not sufficient for such environments. Protection should concern geometrical models, their relationships and structure, as well as inter-object behavioral interactions.

To protect behavioral data, effective but unobtrusive and flexible access control model using privileges based on interactions between objects in a persistently running virtual environment is needed. Possible interactions can be thoroughly analyzed by taking into account the call range of object methods.

Simple interactive 3D modeling for all

Access control model should be expressive enough to provide for inter-object dependencies and their semantics, as objects are created not only from scratch but also as compositions of preexisting objects coming from different sources. The privilege system should automatically encompass newly created objects and follow the evolution of virtual environment data. Privileges should be manageable and understandable by human operator and—at the same time—should be applicable at a fine-grained level. The SSM method consists of two elements.

The SSM method enables modeling privileges for virtual environment behavioral resources with respect to their semantics. The SSM method is based on the concept of semantic operations. Semantic operations are generated at run-time from the virtual environment data model and are applicable to the access control model as a part of a privilege. Semantic consistency of the privilege set is forced by a two-phase regeneration and validation mechanism, so that user privileges can still be expressed in a precise, semantically accurate and flexible way.

This problem originates from the growing demand for interactive 3D applications. Time required to prepare such applications depends heavily on availability of reusable 3D objects with embedded behavior. Effective search for interactive 3D objects needed for new applications requires object metadata that cover not only object geometry and semantics but also its behavior. Existing metadata standards define different schemes for describing objects. General metadata standards such as Dublin Core or XMP enable storing basic information about an object—e.

The missing metadata fragment, not included in the existing metadata standards, is metadata of object behavior. Such information should be stored in a format that permits efficient search for objects with specific interaction properties. The proposed approach is based on two main elements: Based on these two elements, a special query sub-language has been implemented. The sub-language enables efficient usage of interaction metadata.

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A model of 3D object interactions , called Multimedia Interaction Model—MIM, enables decomposition of object interaction capabilities into components. These components are described by distinct metadata structures. The structure of interaction metadata makes it possible to use both semantic textual descriptions and formal mathematical descriptions.

Semantic descriptions can be used at different levels of the metadata structure, providing both general and specific descriptions.

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General descriptions concern the interaction as a whole, while specific descriptions concern particular details of the interaction. Moreover, semantic descriptions can be linked with an ontology specific to a given application domain.

Interactive 3D Multimedia Content: Models for Creation, Management, Search - Google Книги

This possibility increases the informational value of interaction metadata and quality of search results. Mathematical descriptions are used for metadata that enable calculating a new state of an object after the interaction. The new state can be used as a starting point for next interactions. Therefore, mathematical descriptions enable search engines to run searches for interactive objects based not only on current object state but also on object states resulting from an interaction. The MIM model is the basis for a new approach to metadata design. In the proposed approach, interactive objects are treated as elements of a computer program, instead of static items.

The foundation of such approach is the concept of Interaction Interface—II. The structure of the interaction interface is fixed, and there are specific rules for defining new interaction interfaces. Interaction interfaces, as a part of interaction metadata, provide detailed semantics of parameters related to interaction.

Extended semantic information contained in the interaction metadata facilitates searches for objects with specific interaction properties. An example area, where such information often appears, is cultural heritage. In the cultural heritage domain, concepts related to cultural objects are dependent on geographical location and time, can evolve over time and have different meanings in different locations and at different periods. As a result, search methods developed so far, both keyword-based and semantically oriented, fail when applied to cultural heritage because of the imprecision of the data contained in museum knowledgebases, as well as those specified in user queries.

So far none of the keyword search and semantic search methods developed within a single research have been able to retrieve the results with sufficient precision and recall.

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Keyword search will return inaccurate results because terms—especially used for expressing time—are ambiguous in the cultural heritage context. Also, a purely semantic search method would return inaccurate results, because some concepts are not explicitly connected to each other, but they relate only through their temporal and geographical coincidence.

The TSTSM method is based on a new similarity measure , called TST, that allows assessing the distance between different concepts in a semantic, spatiotemporal dataset. During the evaluation of this measure, for each concept in the knowledgebase a fuzzy set of points in the time-space continuum is constructed. In such a set, the more closely a point is related to the analyzed node in the underlying semantic graph, the higher degree of membership it receives. The keywords included in the query are disambiguated through the interactive process and mapped onto the concepts stored in the knowledgebase.

In the next step, fuzzy sets corresponding to the concepts from the user query are joined accordingly to the operands in the query—intersection for AND, union for OR, and complement for NOT. A joining operation is performed in 3-dimensional space, representing points in space and time. As a result, another fuzzy set is obtained that represents the region in space and time that the user is interested in.

Finally, for each node being a possible answer to the query, the TST similarity between the considered node and the user query is computed.

Interactive 3D Multimedia Content

On the basis of the TST measure the results are ranked. The resource for which the TST similarity measure is the highest is the best match. This problem arises when —in response to a query—thousands of documents fulfill relevancy criteria. Currently, almost all widely accepted indexing search engines use textual interfaces based on the same presentational metaphor: I wholeheartedly recommend reading this book! Overige kenmerken Extra groot lettertype Nee. Reviews Schrijf een review.

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