SGN-5508 MULTIMEDIA ANALYSIS AND RETRIEVAL, 5 CR

LECTURE NOTES AND EXERCISES


COURSE TOPIC

Upon completion of this course, the students shall learn:

* The current approaches for searching, browsing, and mining various types of multimedia data such as images, audio and video (audiovisual data).

* Methods from machine learning and computer vision to these problems.

* A broad range of techniques that will be studied including multimedia features, video analysis and management, retrieval techniques, spatial indexing methods, long-term learning and Relevance Feedback, audio analysis and retrieval, semantic based retrieval techniques.

Lecturers:   Prof. Serkan Kiranyaz (Office TC 432), Dr. Esin Guldogan (TF 314)

TA: Guanqun Cao (TC 413)

E-mail: firstname.lastname@tut.fi

 

There will be 14 lectures (Thursday, 10:15-12 o’clock in TB 215) and 12 Lab. exercises (Thursday, 14:15-16 o’clock in TC 303)

Students should submit their Lab. reports and projects via the online submission system:

                      http://www.cs.tut.fi/courses/SGN-5508/Reports/

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Important Note: Lab. reports will only be considered for those students who attended that Lab.

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rss-icon What’s new:

·        We also updated FeX_5508 in the Exercise09.zip to help you fit into the bigger shape_dbs. (15/03/2013)

·        We updated shape_dbs so that it matches the exercise instruction.

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LECTURE NOTES:

 

 

Topic

Lecture Notes

Date (10:00 – 12:00)

Lecture 1

Introduction

Lecture01.zip

10.01.2013

Lecture 2

Multimedia and Standards

 

Lecture02.zip

 

17.01.2013

Lecture 3

MPEG-7: An Overview

 

Lecture03.zip

 

24.01.2013

Lecture 4

CBIR: Visual Retrieval 1

 

01.31.2013

Lecture 5

CBIR: Visual Retrieval 2

 

Lecture04_05.zip

 

07.02.2013

Lecture 6

Image analysis 1

 

Lecture06.zip

 

14.02.2013

Lecture 8

Image analysis: Salient feature

 

Lecture08.zip

 

28.02.2013

Lecture 9

Image Classification

 

Lecture09.zip

 

14.03.2013

 

 

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EXERCISES:

The exercise sheets and additional materials will be published below in PDF format on Thursday each week.

Throughout exercises you will be asked to use following databases: realIm_dbs, texture_dbs, color dbs, shape dbs, video_dbs, categorization_dbs .

And the following template modules: Fex_5508, SEG_5508, SBD_5508.

We have a new image browser: MBrowser

 

Exercise Sheets

Additional Material

Date (14:00 – 16:00)

Exercise 1

Introduction to MUVIS

Exercise01.zip

10.01.2013

Exercise 2

Introduction to MUVIS (cont’d)

 

MUVIS_MBrowser.zip

 

17.01.2013

Exercise 3

A Color Descriptor Implementation in MUVIS – Lab/Luv Histogram

 

 

Exercise03.zip

 

24.01.2013

Exercise 4

A Color Descriptor Implementation in MUVIS – Dominant Color

 

 

Exercise04.zip

 

31.01.2013

Exercise 5

A Texture Descriptor Implementation in MUVIS – Local Binary Patterns

 

 

Exercise05.zip

 

07.02.2013

Exercise 6

Compression Effects on Retrieval Performance

 

 

Exercise06.zip

 

14.02.2013

Exercise 7

Edge Histogram Descriptor

 

Exercise07.zip

 

21.02.2013

Exercise 8

A Shape  Descriptor Implementation in MUVIS – Chain Code Histogram

 

 

Exercise08.zip

 

28.02.2013

Exercise 9

A Shape  Descriptor Implementation in MUVIS – Pyramid Histogram of Oriented Gradients

 

 

Exercise09.zip

 

14.03.2013

Exercise 10

A Spatial Color Descriptor Implementation in MUVIS – Color Coherence Vector

 

 

Exercise10.zip

 

21.03.2013

Exercise 11

Color-based Segmentation

 

 

Exercise11.zip

 

04.04.2013

 

 

 

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EXERCISE GRADING:

                                            Grades