Uma proposta para execução de consultas complexas em uma grande base de dados de imagens horizontalmente fragmentada

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Ciência da Computação, Florianópolis, 2014.Sistemas de recuperação de informação têm se tornado cada vez mais populares e eficientes. Porém, a recuperação de objetos complexos (e.g., imagens, vídeos, séries temporais) ainda apresenta enormes desafios, principalmente quando envolve similaridade de conteúdo. O problema se torna ainda mais intrincado se as condições de busca incluem predicados convencionais conectados logicamente à predicados baseados em similaridade. A otimização de tais consultas é um problema em aberto hoje em dia. Este trabalho valida uma proposta para melhorar o desempenho de consultas que podem ser expressas por conjunções de predicados convencionais e baseados em similaridade. Tal proposta utiliza fragmentação de dados, segundo predicados diversos e compatíveis com predicados utilizados em consultas. A validação da proposta é feita sobre uma grande base de dados chamada CoPhIR a respeito de imagens, com dados convencionais a elas relacionados. Esta base é manipulada em um sistema de banco de dados relacional com extensões para o tratamento de predicados baseados em similaridade, caracterizada segundo a distribuição do seu conteúdo, fragmentada e indexada, com métodos de acesso convencionais e métricos. Verificou-se um melhor desempenho na execução de algumas consultas com cláusulas conjuntivas para filtragem de dados utilizando os fragmentos propostos do que sobre a base completa.Abstract : Information retrieval systems are growing in popularity and efficiency. However, the retrieval of complex data (e.g., images, video, temporal series) presents huge challenges yet, particularly when it involves content similarity. The problem becomes even more intricate if the search condition includes conventional predicates logically connected to similarity-based predicates. The optimization of such queries is an open problem nowadays. This work validates a proposal for improving the performance of queries that can be expressed by conjunctions of conventional predicates and similarity-based predicates. This proposal employs data fragmentation, according to diverse predicates, that are compatible with the predicates used in queries. The validation of this proposal is done on a large image database, named CoPhIR with conventional data associated with the images. This database is handled in a relational database system with extensions for coping with similarity-based predicates, characterized according to contents distribution, fragmented and indexed, for efficient access with conventional methods and metric methods. The result of the experiments shows that for some queries with conjunctive filtering clauses were executed more efficiently on fragments than by accessing the complete database

Web service for annotating vector geographic data and its application in information systems for biodiversity

Orientador: Ricardo da Silva TorresDissertação (mestrado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: Estudos na área de biodiversidade baseiam-se no uso de dados relacionados a coletas em campo. Normalmente estes dados estão associados a uma localização geográfica. Grande parte dos sistemas de biodiversidade oferece recursos básicos para armazenamento e consulta de dados geográficos. Esta dissertação apresenta um modelo de dados e um serviço Web para correlacionar dados de biodiversidade e dados geográficos, baseados no conceito de Informação Sobreposta (Superimposed Information). Informação sobreposta é uma nova informação (ou nova interpretação) sobre uma informação existente. Pode estar na forma de um novo conteúdo ou novas estruturas. Esta dissertação descreve a utilização do conceito de Superimposed Information para a construção de um serviço Web para anotação de dados geográficos vetoriais. A especificação do serviço Web inclui a definição de uma API genérica para manipulação de anotações e a definição de um modelo de dados para gerenciamento de informações sobrepostas. A solução foi validada a partir da implementação de um protótipo para a área de biodiversidade considerando um potencial cenário de usoAbstract: Biodiversity studies are often based on the use of data associated with field observations. These data are usually associated with a geographic location. Most of existing biodiversity information systems provide basic support for storing and quering geographic data. This work presents a data model and a Web service to correlate biodiversity data and geographic information, based on the concept of Superimposed Information. Superimposed Information is a new information (or new interpretation) over existing information usually in the form of new content or new structures. This work uses the concept of Superimposed Information for constructing a Web service for annotating vector geographic data. The Web service specification includes the definition of a generic API for handling annotations and the definition of a data model for managing Superimposed information.The solution was validated through the implementation of a prototype for the biodiversity area considering a potential usage scenarioMestradoBanco de DadosMestre em Ciência da Computaçã

Superimposed image description and retrieval for fish species identification

Abstract. Fish species identification is critical to the study of fish ecology and management of fisheries. Traditionally, dichotomous keys are used for fish identification. The keys consist of questions about the observed specimen. Answers to these questions lead to more questions till the reader identifies the specimen. However, such keys are incapable of adapting or changing to meet different fish identification approaches, and often do not focus upon distinguishing characteristics favored by many field ecologists and more user-friendly field guides. This makes learning to identify fish difficult for Ichthyology students. Students usually supplement the use of the key with other methods such as making personal notes, drawings, annotated fish images, and more recently, fish information websites, such as Fishbase. Although these approaches provide useful additional content, it is dispersed across heterogeneous sources and can be tedious to access. Also, most of the existing electronic tools have limited support to manage user created content, especially that related t

Reusing A Compound-based Infrastructure For Searching Video Stories

The fast evolution of technology has led to a growing demand for multimedia data, increasing the amount of research into efficient systems to manage those materials. A lot of research has being done by the Content-Based Image Retrieval (CBIR) community in the field of images. Nowadays, they play a key role in digital applications. Thus, contextual integration of images with different sources is vital. It involves reusing and aggregating a large amount of information with other media types. In particular, if we consider video data, images can be used to summarize videos into storyboards, providing an easy way to navigate and to browse large video collections. This has been the goal of a quickly evolving research area known as video summarization. In this paper, we present a novel approach to reuse the CBIR infrastructure for searching video stories, taking advantage of the compound object (CO) concept to integrate resources. 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