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Base de Dados MultimédiaInteligentes
Andreas Wichert
MEIC Tagus(Página da cadeira: Fenix)
Objectivo Geral Esta cadeira irá apresentar técnicas e algoritmos
relevantes para o desenvolvimento e implementaçãode sistemas inteligentes de bases de dados demultimedia
Irá incluir tópicos técnicos tais como compressão,origem e papel desempenhado por metadata assimtambém como multimédia e SQL
Problemas relativos à manipulação de dadosmultimédia, em particular em relação a questionar(content based information retrieval) índices esumários serão abordados
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Organization
Program
Introduction
Querying Multimedia Databases
Application Examples
Corpo docente Andreas Wichert - Teóricas / Práticas
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Organização das aulas Teóricas:
Matéria (slides baseados no livro e artigos e ...)
Práticas/Laboratório (weekly!): Exercícios Software Experiments
Avaliação
Problemas praticas (Exercícios) (40%) + Exame orais (60%) !
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Bibliografia (Main)
Lynne Dunckley. Multimedia Databases, AnObject-Rational Approach. Addison Wesley,2003
Bibliografia
Fred Halsall. Multimedia Communications:Applications, Networks, Protocols and Standards.Addison Wesley, 2001
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Bibliografia
Christos Faloutsos. Modern information retrieval. InRicard Baeza-Yates and Berthier Ribeiro-Neto,editors, Modern Information Retrieval, chapter 12,pages 345–365. Addison-Wesley, 1999.
C. Böhm, S. Berchtold, and A. Keim Kei, D.Searching in highdimensional spaces—indexstructures for improving the performance ofmultimedia databases. ACM Computing Surveys,33(3):322–373, 2001.
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Programa 1. Introduction, examples
2. Multimedia Data
3. Tools: DFT/Wavelets
4. Compression, Image, MPEG audio
5. Video MPEG -1, -2, -4
6. Introduction to DB, Multimedia and SQL
Programa 7. Human visual system
8. Human acoustic system
9. Content Based Multimedia Retrieval
10. Multimedia metadata (MPEG 7)
11. Feature Selection and Extraction
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Programa 12. Primary key, B-trees
13. Multi—key Indexing, Inverted indices, k-d-trees, z-ordering
14. R-trees, Grid files, Metric trees
15. Gemini
16. Subspace method
Programa 17. Text indexing
18. Singular Value Decomposition
19. Querying and Information fusion
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Programa 21. Associative Memory
22. Semantic Modeling
23. Multimedia Database Architecture
24. Client server system and storage parameters
Programa 25. Multimedia and the Internet
Course ends around 13. Dec.
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Introduction In the past
Humans represented information through images
Modern times Dominance of text
This century Nature of documents and information is changing..
Human brain is more efficient atprocessing and interpreting visual andaudio information
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In dealing with multimedia information weare dealing with digital data representations how these data can be stored and
manipulated
Provide more functions than would beavailable in traditional forms of data
Early applications of multimedia databasemanagement systems MMDBMS tend to usemultimedia for presentational requirements only
A sales order processing system could include anonline catalog that includes a picture of the productsoffered
The image would be retrieved by an applicationprocess which referenced it through a traditionaldatabase record
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What is essential aboutdatabase systems? Users of a database system expect to be
able to manipulate the data to obtainuseful output Insert new data Retrieve and change existing data Delete data
What is different aboutMultimedia Data Size
A good quality colored image 6MB With 30 frames per sec., five min. video clip
would require 54 GB Time
Video, Music Semantic nature of multimedia
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Querying multimedia Database
How to pose a query?
How to search?
What information can be retrieved?
How the information can be retrieved?
Allow new access of data
Query by images:• Find the most similar image to the presented
image• Find images which may indicate an illness
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medGIFT
Anfragebild
Emphysem Emphysem
Macro nodules Micro nodules
Allow new access of data
Query by films• Find the most similar filmed operation to the
present one
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Thomas Blessington, a sixteen-year-old fromBradford who was arrested for shopbreaking 1901
The use of photography to record knowncriminals - the 'mug shot'- had been suggestedas early as the 1840s.
Intelligent multimedia-databases for medicine Images are kept with patients record
stored by unique identifiers browse and navigate their way through
collection of multimedia objects such asdigital images
“How does my patient's tumor lookcompared to other similar cases”
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