Hierarchical affinity hybrid tree: A multidimensional index structure to organize videos and support content-based retrievals

Chatterjee, Kasturi; Chen, Shu‐Ching

doi:10.1109/iri.2008.4583070

Cited by 5 publications

(5 citation statements)

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“…[4] discusses a multidimensional index structure designed to handle images. [5] extends the idea to a hierarchical index structure, supporting video data objects. It can handle the hierarchical relationship among the different video units and facilitate intra and inter-unit retrieval strategies.…”

Section: Replicated Multidimensional Index Structurementioning

confidence: 99%

“…We chose AH-Tree as we wanted to use images as the test bed for developing and testing the initial framework of the distributed multimedia database. It should be pointed out here that both [5] as well as [6] can be used in the proposed framework without any loss of generality.…”

Section: Replicated Multidimensional Index Structurementioning

confidence: 99%

“…Though there are numerous multidimensional index structures such as those in [8] [3] that can handle the multidimensional aspect of the multimedia data but they lack the capability to handle the high-level semantic relationships efficiently. In our earlier works, we proposed multidimensional index structures including AH-Tree [4], HAH-Tree [5] and GeM-Tree [6] designed for efficient management of multimedia data comprising of images and videos. In this chapter, we extend the usability of multimedia index structures in a distributed Grid environment.…”

Section: Introductionmentioning

confidence: 99%

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A Distributed Multimedia Data Management over the Grid

Chatterjee

Sadjadi

Chen

2010

Multimedia Services in Intelligent Environments

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In this chapter, we propose a distributed multimedia data management architecture, which can efficiently store and retrieve multimedia data across several nodes of a Grid environment. The main components of the proposed system comprises of a distributed multidimensional index structure, a distributed query manager handling content-based information retrievals and a load balancing technology. The proposed distributed query manager embeds the high-level semantic relationships among the multimedia data objects into the k-NN based similarity search, thus bridging the semantic gap and increasing the relevance of query results manifold. This research has two major usabilities. First, it models a web environment where each node of the Grid can be considered as the nodes or sources of data in the world-wide-web. This should help to investigate and understand the challenges and requirements of future search paradigms based on content of multimedia data rather than on text annotations, as used currently. Second, it provides the foundation to develop content-based information retrievals as a possible Grid service. Extensive experiments were conducted with varied data sizes and different number of distribution nodes. Encouraging results are obtained that makes this endeavor a potential architecture to manage complex multimedia data over a distributed environment.

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Section: Replicated Multidimensional Index Structurementioning

confidence: 99%

Section: Replicated Multidimensional Index Structurementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Distributed Multimedia Data Management over the Grid

Chatterjee

Sadjadi

Chen

2010

Multimedia Services in Intelligent Environments

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“…Three different types of queries are executed, namely queries involving only images, queries involving only videos, and queries involving both images and videos. The results obtained from GeM-Tree are compared with a distance-based index structure for only images [45] (labeled as I in Tables 4.3 to 4.5), a distance-based index structure for only videos [48] (labeled as II in Tables 4.3 Essentially, I and II have the same framework as GeM-Tree. The only difference is that in this experimental setup, while GeM-Tree indexes a data corpus having both images and videos, I and II indexes a data corpus having only images and videos respectively.…”

Section: Empirical Studymentioning

confidence: 99%

A generalized multidimensional index structure for multimedia data to support content-based similarity searches in a collaborative search environment

Chen

Chetterjee

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Chatterjee, Kasturi, "A generalized multidimensional index structure for multimedia data to support content-based similarity searches in a collaborative search environment" (2010 Since multimedia data, such as images and videos, are way more expressive and informative than ordinary text-based data, people find it more attractive to communicate and express with them. Additionally, with the rising popularity of social networking tools such as Facebook and Twitter, multimedia information retrieval can no longer be considered a solitary task. Rather, people constantly collaborate with one another while searching and retrieving information. But the very cause of the popularity of multimedia data, the huge and different types of information a single data object can carry, makes their management a challenging task. Multimedia data is commonly represented as multidimensional feature vectors and carry high-level semantic information. These two characteristics make them very different from traditional alpha-numeric data. Thus, to try to manage them with frameworks and rationales designed for primitive alpha-numeric dat, will be ineflicient.An index structure is the backbone of any database management system.. It has been seen that index structures present in existing relational database management frameworks cannot handle multimedia data effectively. Thus, ill this dissertation, a generalized multidimensional index structure is proposed which accommodates the atypical multidimensional representation and the semantic information carried by different multimedia data seamlessly from within one single framework. Additionally, the dissertation vi investigates the evolving relationships among multimedia data in a collaborative environment and how such information can help to customize the design of the proposed index structure, when it is used to manage multimedia data in a shared environment.Extensive experiments were conducted to present the usability and better performance of the proposed framework over current state-of-art approaches.

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“…Para garantir uma resposta rápida, é imperativo o desenvolvimento de algoritmos de busca por similaridade que acelerem esse processo. Elaboradas estruturas de dados, conhecidas como métodos de acesso (MAs), têm sido propostas a fim de acelerar buscas por similaridade [44,45,47,65,94]. No entanto, a maioria desses métodos sofre de um problema conhecido como maldição da dimensionalidade (do inglês, curse of dimensionality): na medida em que aumenta a dimensionalidade dos dados, as estruturas de indexação desses métodos tornam-se lentas e grandes demais [174].…”

Section: Introductionunclassified

Recuperação de vídeos comprimidos por conteúdo

Almeida¹,

Torres²

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Todos os direitos reservados. vii À memória da minha bisavó Luzia e do seu irmão Mauro. ix AgradecimentosAgradeço, a Deus, por todas as oportunidades que Ele me oferece. ao meu orientador e co-orientador, Prof. Dr. Ricardo da Silva Torres e Prof. Dr. Neucimar Jerônimo Leite, pela oportunidade e orientação, cujos conselhos e sugestões foram muito valiosos tanto para este trabalho quanto para minha vida. a toda minha família, em especial a minha bisavó Luzia (in memorian) e ao seu irmão Mauro (in memorian), e avós, Anésio (in memorian), Virgínia (in memorian), João (in memorian) e Ordália, por me ensinarem a valorizar tudo que a vida nos oferece. aos meus pais Jurandy e Sônia, pela formação como ser humano, pelo incentivo constante, pelo apoio irrestrito e por seus valiosos conselhos. à minha namorada, Noemi, pela dedicação, companheirismo, paciência e carinho. ao meu irmão Tiago, pelos inúmeros conselhos, correções e sugestões. ao meu irmão Marcos, pelo apoio. aos meus companheiros do LIV e RECOD, pelas frutíferas discussões. aos demais colegas de pós-graduação, pela ótima convivência. aos professores e funcionários do IC, pelos serviços prestados. à UNICAMP, pela infra-estrutura. à CAPES, FAPESP e FAEPEX, pelo apoio financeiro. a todos que de alguma forma contribuíram com o meu progresso. xi ResumoAvanços recentes na tecnologia têm permitido o aumento da disponibilidade de dados de vídeo, criando grandes coleções de vídeo digital. Isso tem despertado grande interesse em sistemas capazes de gerenciar esses dados de forma eficiente.Fazer uso eficiente de informações de vídeo requer o desenvolvimento de ferramentas poderosas capazes de extrair representações semânticas de alto nível a partir de características de baixo nível do conteúdo de vídeo. Devido à complexidade desse material, existem cinco desafios principais na concepção de tais sistemas: (1) dividir o fluxo de vídeo em trechos manuseáveis de acordo com a sua estrutura de organização, (2) implementar algoritmos para codificar as propriedades de baixo nível de um trecho de vídeo em vetores de características, (3) desenvolver medidas de similaridade para comparar esses trechos a partir de seus vetores, (4) responder rapidamente a consultas por similaridade sobre uma enorme quantidade de sequências de vídeo e (5) apresentar os resultados de forma amigável a um usuário.Inúmeras técnicas têm sido propostas para atender a tais requisitos. A maioria dos trabalhos existentes envolve algoritmos e métodos computacionalmente custosos, em termos tanto de tempo quanto de espaço, limitando a sua aplicação apenas ao ambiente acadêmico e/ou a grandes empresas.Contrário a essa tendência, o mercado tem mostrado uma crescente demanda por dispositivos móveis e embutidos. Nesse cenário, é imperativo o desenvolvimento de técnicas tanto eficazes quanto eficientes a fim de permitir que um público maior tenha acesso a tecnologias modernas.Nesse contexto, este trabalho apresenta cinco abordagens originais voltadas a análise, indexação e recuperação de vídeos digitais. Todas essas co...

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Hierarchical affinity hybrid tree: A multidimensional index structure to organize videos and support content-based retrievals

Abstract: Abstract

Cited by 5 publications

References 16 publications

A Distributed Multimedia Data Management over the Grid

A Distributed Multimedia Data Management over the Grid

A generalized multidimensional index structure for multimedia data to support content-based similarity searches in a collaborative search environment

Recuperação de vídeos comprimidos por conteúdo

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