Abstract
In this paper we address the problem of automatically computing a set of views over a simulated three dimensional enviromnent. The viewing system aims at, for each moment, supplying the user with the most pertinent information in order to allow a good understanding of the evolving environment. Our approach relies on an innovative optimization architecture that enables intelligent optimization techniques based on simulated annealing and genetic algorithms. Reported experiments were performed in urban rescue scenarios from the RoboCup Rescue Domain. We outline the possible extension of the proposed architecture to other visualization problems and argue on how several problems within the fields of Visualization and Rendering can benefit from it.

Abstract

Abstract
The INESC Porto group has participated in the search task (automatic and interactive). Our approach combines high-level features (the 39 con- cepts of the LSCOM-Lite set) with low-level features. We use a large set of low-level features with the intention of analysing as many facets as possible of each shot. The aggregation of large feature sets can be time consuming as it needs to be done at query time. We have developed the BitMatrix indexing method to speed up the search process. For each shot, binary signatures in the form of bit sequences are obtained in an on-line process. At query time, the query bit signature is compared to each of the shots signatures. The automatic run performs above the median, in spite of not using any classifier or any other knowledge sources except the translation of the query into LSCOM-Lite concepts.

Abstract
The paper presents a multimedia database model accounting for the representation of documents, collections and the associated metadata. Appropriate structures are provided for descriptive metadata and for metadata resulting from automatic content analysis. The model is based on the identification and unification of the main concepts in the archival standards and the audiovisual area. The main features of the model, designed to support multimedia database applications, axe the integration of descriptive and content analysis metadata, the association of metadata to collections as well as to items, the extensibility with respect to the inclusion of new descriptors and the support to several retrieval modes. The MetaMedia application development platform, based on the model, has been used to support the construction of a historic documentation collection where a common web interface provides collection administrators, metadata creators and visitors a multi-faceted view of the repository.

Abstract
The web is currently the information searching and browsing environment of choice for scholars and lay users alike. The goal of most cultural heritage applications is to interest a large audience, and therefore web interfaces are being developed even when part of their functionality is not offered to the general public. We present a web-based interface for managing, browsing and searching a repository of historic documents. The documents pertain to a region which has been an important regional power in medieval times and their originals are under the custody of the Portuguese national archives. The challenges of the project came from its requisites in three aspects: rigorous archival description, the incorporation of document analysis and a flexible search interface. The system is an instance of a multimedia database framework providing both browse and retrieval functionalities to end users and configuration and content management services to the collection administrators.

Abstract
Time has been successfully used as a feature in web information retrieval tasks. In this context, estimating a document's inception date or last update date is a necessary task. Classic approaches have used HTTP header fields to estimate a document's last update time. The main problem with this approach is that it is applicable to a small part of web documents. In this work, we evaluate an alternative strategy based on a document's neighborhood. Using a random sample containing 10,000 URLs from the Yahoo! Directory, we study each document's links and media assets to determine its age. If we only consider isolated documents, we are able to date 52% of them. Including the document's neighborhood, we are able to estimate the date of more than 86% of the same sample. Also, we find that estimates differ significantly according to the type of neighbors used. The most reliable estimates are based on the document's media assets, while the worst estimates are based on incoming links. These results are experimentally evaluated with a real world application using different datasets. Copyright 2007 ACM.