1000 resultados para Visual crowding
Resumo:
There are still major challenges in the area of automatic indexing and retrieval of multimedia content data for very large multimedia content corpora. Current indexing and retrieval applications still use keywords to index multimedia content and those keywords usually do not provide any knowledge about the semantic content of the data. With the increasing amount of multimedia content, it is inefficient to continue with this approach. In this paper, we describe the project DREAM, which addresses such challenges by proposing a new framework for semi-automatic annotation and retrieval of multimedia based on the semantic content. The framework uses the Topic Map Technology, as a tool to model the knowledge automatically extracted from the multimedia content using an Automatic Labelling Engine. We describe how we acquire knowledge from the content and represent this knowledge using the support of NLP to automatically generate Topic Maps. The framework is described in the context of film post-production.
Resumo:
There are still major challenges in the area of automatic indexing and retrieval of digital data. The main problem arises from the ever increasing mass of digital media and the lack of efficient methods for indexing and retrieval of such data based on the semantic content rather than keywords. To enable intelligent web interactions or even web filtering, we need to be capable of interpreting the information base in an intelligent manner. Research has been ongoing for a few years in the field of ontological engineering with the aim of using ontologies to add knowledge to information. In this paper we describe the architecture of a system designed to automatically and intelligently index huge repositories of special effects video clips, based on their semantic content, using a network of scalable ontologies to enable intelligent retrieval.
Resumo:
A large volume of visual content is inaccessible until effective and efficient indexing and retrieval of such data is achieved. In this paper, we introduce the DREAM system, which is a knowledge-assisted semantic-driven context-aware visual information retrieval system applied in the film post production domain. We mainly focus on the automatic labelling and topic map related aspects of the framework. The use of the context- related collateral knowledge, represented by a novel probabilistic based visual keyword co-occurrence matrix, had been proven effective via the experiments conducted during system evaluation. The automatically generated semantic labels were fed into the Topic Map Engine which can automatically construct ontological networks using Topic Maps technology, which dramatically enhances the indexing and retrieval performance of the system towards an even higher semantic level.
Resumo:
Visually impaired people have a very different view of the world such that seemingly simple environments as viewed by a ‘normally’ sighted people can be difficult for people with visual impairments to access and move around. This is a problem that can be hard to fully comprehend by people with ‘normal vision’ even when guidelines for inclusive design are available. This paper investigates ways in which image processing techniques can be used to simulate the characteristics of a number of common visual impairments in order to provide, planners, designers and architects, with a visual representation of how people with visual impairments view their environment, thereby promoting greater understanding of the issues, the creation of more accessible buildings and public spaces and increased accessibility for visually impaired people in everyday situations.
Resumo:
This paper describes the development of an interface to a hospital portal system for information, communication and entertainment such that it can be used easily and effectively by all patients regardless of their age, disability, computer experience or native language. Specifically, this paper reports on the work conducted to ensure that the interface design took into account the needs of visually impaired users.