multimedia data management m
play

Multimedia Data Management M Second cycle degree programme (LM) in - PowerPoint PPT Presentation

ALMA MATER STUDIORUM - UNIVERSIT DI BOLOGNA Multimedia Data Management M Second cycle degree programme (LM) in Computer Engineering University of Bologna Course presentation Academic Year 2019/2020 Home page:


  1. ALMA MATER STUDIORUM - UNIVERSITÀ DI BOLOGNA Multimedia Data Management M Second cycle degree programme (LM) in Computer Engineering University of Bologna Course presentation Academic Year 2019/2020 Home page: http://www-db.disi.unibo.it/courses/MDM/ Electronic version: 0.01.Presentation.pdf Electronic version: 0.01.Presentation-2p.pdf Bologna, February 19 th , 2020

  2. Teacher § Prof.ssa Ilaria Bartolini Department of Computer Science and Engineering (DISI) University of Bologna Viale Risorgimento, 2, Bologna Multimedia Database Group http://www-db.disi.unibo.it/MMDBGroup/ Datalab http://www-db.disi.unibo.it/research/datalab/ I. Bartolini Multimedia Data Management M 2

  3. Contacts § E-mail: § ilaria.bartolini@unibo.it § Telephone: § 051 20 93550 § Web site: § http://www-db.disi.unibo.it/ibartolini/ § Office hours: § on Monday, from 11:00 to 13:00, c/o Palazzina “gialla” DISI (close to the 2 nd School entrance of “via Vallescura”) § please, send me an email for appointment first I. Bartolini Multimedia Data Management M 3

  4. General information § Name: “Multimedia Data Management M” § Credits: 8 § Teaching hours: 64 hours § Period: Semester II § February 19 th 2020 – June 5 th 2020 Course calendar § Teaching hours: § Wednesday – 14:00-17:00 – Room 2.7.A (beginning of the lesson at 14:15) § Friday – 9:00-11:00 – Room 1.4 (beginning of the lesson at 9:15) I. Bartolini Multimedia Data Management M 4

  5. Course contents Learning outcomes § The course aims to provide the students with all necessary knowledge and skills to deal with the effective and efficient management of “non-conventional” data types, notably multimedia (MM) data (e.g., textual documents, still images, videos, sound, audio/visual streams, etc.); the final goal is to find, within very large collections, namely “ Big Data ”, those objects that are better suited to fulfill the information needs of non-expert users § We pay special attention to problems of MM data modeling/ representation, MM data retrieval models, and interaction paradigms between the user and the MM system (both for purposes of data presentation and exploration) § We first consider architectures of traditional (“standalone”) MM systems; then, we concentrate on more complex MM services, by primarily focusing on search engines, social networks and recommender systems I. Bartolini Multimedia Data Management M 5

  6. Course contents Topics at a glance § Multimedia data and data types classification § Textual documents: the easiest case of multimedia data § Multimedia data content representations § Automatic techniques for MM data semantic annotations § Efficient and effective techniques for multimedia data retrieval, browsing, and visualization § Multimedia data on the Web !Each lecture is enriched by practical examples , use cases , demos , and exercises … J I. Bartolini Multimedia Data Management M 6

  7. Main goal in one pic! § Facilitate and improve the “access” to very large multimedia data collections for general users, conjunctively exploiting: § low level features (e.g., color distribution of a video key frame) Models, § semi-automatically provided annotations Algorithms, Interfaces § “dedicated users” manually provided meta-data Archivio Storico Fiat Cineteca Archivio Artistico § Das Cabinet des Dr. Caligari § La Gioconda § Trimotore Fiat G212 § Data: 1920 § Sito: Museo Louvre, Parigi § Data: 1947 Collezione: Tema di cultura § Nazione: Germania Secolo: XVI § § § Regista: Robert Wiene § Autore: Leonardo da Vinci industriale Tipologia: Immagine § Genere: Horror Periodo: Rinascimento § § § Espressionismo, Ipnosi, § Data: 1503 § Aereo, Motore, Ali Sonnambulismo Dipinto, Ritratto, Sorriso § I. Bartolini Multimedia Data Management M 7

  8. Detailed program (1) § Multimedia data and data types classification § MM data and applications § Srtuctured data § Semi-strucutred data § Unstructured data § Textual documents: the easiest case of multimedia data § Documents representation § Automatic indexing techniques, stemming, stoplist § Searches of Boolean type § Searches of phrases and for proximity § The vector space model: weighing techniques and ranking of the results I. Bartolini Multimedia Data Management M 8

  9. Detailed program (2) § Multimedia data content representations § MM data coding § MM data content representation § How to find multimedia data of interest § Description models for complex MM objects § Similarity measures for MM data content § MM database management systems § Efficient algorithms for MM data retrieval § MM query formulation paradigms § Sequential retrieval of MM data § Index-based retrieval of MM data § Automatic techniques for MM data annotations: filling the semantic gap § Traditional techniques § Graph-based solutions I. Bartolini Multimedia Data Management M 9

  10. Detailed program (3) § Browsing MM data collections § Browsing paradigms § MM data presentation § User interface design principles § Visualization paradigms § Dimensionality reduction techniques § Result accuracy § Quality of the results: reference metrics § User-system interaction and relevance feedback: how to improve the quality of the results § Multimedia Data on the Web § Web search engines: principles § Graph-based data: semantic Web and social networks § Web recommender systems: basics I. Bartolini Multimedia Data Management M 10 10

  11. Course home page http://www-db.disi.unibo.it/courses/MDM/ https://iol.unibo.it/course/view.php?id=44586#section-1 Contents : § News § Copy of slides, extra material in PDF format § Bibliography& Useful links § Assessment methods § Exam sessions § Project work § Modalities/topics I. Bartolini Multimedia Data Management M 11

  12. Readings/Bibliography § Education material provided by the teacher (copies of the slides used in the classroom, scientific literature, etc.) For any further additional information, recommended books are: § Candan, Sapino. “ Data Management for Multimedia Retrieval ”, Cambridge, 2010. ISBN: 978-0-521-88739-7 § Zhang, Zhang. “ Multimedia Data Mining: A Systematic Introduction to Concepts and Theory ”, Chapman and Hall/CRC, 2008. ISBN: 9781584889663 § Chapman & Chapman. “ Digital Multimedia ”, Wiley & Sons Ltd, 2009. ISBN: 13 978-0-470-51216-6 § Colace, De Santo, Moscato, Picariello, Schreiber, Tanca. “ Data Management for Pervasive Systems ”, Springer, 2015. ISBN: 978-3-319- 20061-3 I. Bartolini Multimedia Data Management M 12 12

  13. Teaching methods § Most course lectures are in “traditional” classrooms and exploit the slides § Real use cases (+ relative demos) are also proposed and discussed based on open-source software libraries and frameworks I. Bartolini Multimedia Data Management M 13 13

  14. Assessment methods § The exam evaluation consists of an oral examination § To participate to the exam, interested students have to register themselves by exploiting the usual UniBO Web application, called AlmaEsami § The students can also arrange with the teacher a “Project work” of Multimedia Data Management M based on their own preferences or suggested topics… more details on this in few minutes… J § In this case, the oral examination can be taken conjunctly with the project presentation I. Bartolini Multimedia Data Management M 14 14

  15. Examination sessions § Six examination sessions per year divided as follows: § three sessions before the summer § starting from September, at the request of the students I. Bartolini Multimedia Data Management M 15 15

  16. Project work details (1) § The project activity aims to apply the notions and skills acquired during the course by developing a project § The project consists in the concrete resolution of a problem concerning the management of multimedia data § The topic of the project can be proposed either by the teacher and the student § Usually a scientific paper is considered as the base for the development of a new multimedia data management algorithm and/or infrastructure and/or service and/or interface § however, everything that “looks interesting” is allowed to be candidate! J § Once you start your project work, the development stages are verified by the teacher with periodical meetings I. Bartolini Multimedia Data Management M 16 16

  17. Project work details (2) § The final evaluation consists of a Power Point presentation integrated by a project demo § According to students’ preferences, the project presentation can be taken conjunctly with the final course oral examination § During the development phase of the project, students can profitably use/extend existing software libraries, such as § Open-source Multimedia libraries and architectures § Multimedia frameworks, e.g., § Windsurf, for the management of large image collections § Shiatsu, for the management of large video databases § RAM 3 S, for the real-time analysis of massive multimedia streams § … developed within the Multimedia Database Group @ DISI ( http://www-db.disi.unibo.it/MMDBGroup/ ) § Augmented reality environments for immersive 3D applications I. Bartolini Multimedia Data Management M 17 17

  18. ALMA MATER STUDIORUM - UNIVERSITÀ DI BOLOGNA Course presentation Academic Year 2019/2020 Questions? I. Bartolini Multimedia Data Management M 18

Download Presentation
Download Policy: The content available on the website is offered to you 'AS IS' for your personal information and use only. It cannot be commercialized, licensed, or distributed on other websites without prior consent from the author. To download a presentation, simply click this link. If you encounter any difficulties during the download process, it's possible that the publisher has removed the file from their server.

Recommend


More recommend