Base de Dados Multimédia Inteligentes

Transcrição

1 Base de Dados Multimédia Inteligentes Andreas Wichert LEIC Tagus (Página da cadeira: Fenix) Objectivo Geral Esta cadeira irá apresentar técnicas e algoritmos relevantes para o desenvolvimento e implementação de sistemas inteligentes de bases de dados de multimedia Irá incluir tópicos técnicos tais como compressão, origem e papel desempenhado por metadata assim também como multimédia e SQL Problemas relativos à manipulação de dados multimédia, em particular em relação a questionar (content based information retrieval) índices e sumários serão abordados 1

2 Organization Program Introduction Querying Multimedia Databases Application Examples Corpo docente Andreas Wichert - Teóricas / Práticas andreas.wichert@tagus.ist.utl.pt andreas.wichert@inesc-id.pt 2

3 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%)! 3

4 Bibliografia (Main) Lynne Dunckley. Multimedia Databases, An Object-Rational Approach. Addison Wesley, 2003 Bibliografia Fred Halsall. Multimedia Communications: Applications, Networks, Protocols and Standards. Addison Wesley,

5 Bibliografia Christos Faloutsos. Modern information retrieval. In Ricard Baeza-Yates and Berthier Ribeiro-Neto, editors, Modern Information Retrieval, chapter 12, pages Addison-Wesley, C. Böhm, S. Berchtold, and A. Keim Kei, D. Searching in highdimensional spaces index structures for improving the performance of multimedia databases. ACM Computing Surveys, 33(3): ,

6 Programa 12. Sep. Introduction, examples 15. Sep. Multimedia Data 19. Sep. Tools: DFT/Wavelets 22. Sep. Compression, Image, MPEG audio 26. Sep. Video MPEG -1, -2, Sep. Introduction to DB, Multimedia and SQL Programa 03. Okt. Human visual system 06. Okt. Human acoustic system 10. Okt. Content Based Multimedia Retrieval 13. Okt. Multimedia metadata (MPEG 7) 17. Okt. Feature Selection and Extraction 6

7 Programa 20. Okt. Primary key, B-trees 24. Okt. Multi key Indexing, Inverted indices, k-d-trees, z-ordering 27. Okt. R-trees, Grid files, Metric trees 31. Okt. Gemini 03. Nov. Subspace method Programa 07. Nov. 10. Nov. 14. Nov. Text indexing Singular Value Decomposition Querying and Information fusion 7

8 Programa 17. Nov. Associative Memory 21. Nov. Semantic Modeling 24. Nov. Multimedia Database Architecture 28. Nov. Client server system and storage parameters Programa 05. Dez. 12. Dez. Multimedia and the Internet Examples of Image, Video and Music databases - Conclusion 8

9 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 at processing and interpreting visual and audio information 9

10 In dealing with multimedia information we are dealing with digital data representations how these data can be stored and manipulated Provide more functions than would be available in traditional forms of data Early applications of multimedia database management systems MMDBMS tend to use multimedia for presentational requirements only A sales order processing system could include an online catalog that includes a picture of the products offered The image would be retrieved by an application process which referenced it through a traditional database record 10

11 What is essential about database systems? Users of a database system expect to be able to manipulate the data to obtain useful output Insert new data Retrieve and change existing data Delete data What is different about Multimedia 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 11

12 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 12

13 medgift Emphysem Emphysem Anfragebild Macro nodules Micro nodules Allow new access of data Query by films Find the most similar filmed operation to the present one 13

14 Multimedia Applications Entertainment Systems Pubilc protection Medical information Systems 14

15 Thomas Blessington, a sixteen-year-old from Bradford who was arrested for shopbreaking 1901 The use of photography to record known criminals - the 'mug shot'- had been suggested as early as the 1840s. Intelligent multimediadatabases for medicine Images are kept with patients record stored by unique identifiers browse and navigate their way through collection of multimedia objects such as digital images How does my patient's tumor look compared to other similar cases 15

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17 Homework Go to... Famous Imperial Museum in St.Petersburg Russia! 17

18 Bioinformatics Chemistry Astronomy Organization Program Introduction Querying Multimedia Databases Application Examples 18