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Multimedia Retrieval Organization 2013/14, term 1

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Multimedia Retrieval Organization 2013/14, term 1 Remco Veltkamp Lecturer Prof. dr. Remco Veltkamp Chair: Multimedia Media Technologie: Image Retrieval 3D Object ... – PowerPoint PPT presentation

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Title: Multimedia Retrieval Organization 2013/14, term 1


1
Multimedia Retrieval Organization 2013/14, term 1
  • Remco Veltkamp

2
Lecturer
  • Prof. dr. Remco Veltkamp
  • Chair Multimedia
  • Media Technologie
  • Image Retrieval
  • 3D Object Retrieval
  • 3D Scene analysis
  • Music retrieval
  • Video analysis
  • Room BBL-479, R.C.Veltkamp_at_uu.nl

3
Schedule
  • Ca. 11 lectures/topics Mondays 17.00 - 18.45,
    BBG-023 Thursdays 9.00 - 10.45, BBL-079
  • Practical Assignment

4
Grading
  • Written exam 50
  • Assignment 50
  • Pass if average at least 6, and parts at least 4
  • Retake exam only if original final grade is at
    least a 4
  • Form of retake written exam and/or additional
    assignment

5
Exam
  • Motivation MM retrieval requires critical amount
    of knowledge
  • About the topics discussed in all lectures
  • Slides are available Make your own notes
    (academic skill)

6
Literature
  • M. Lew (ed.). Principles of Visual Information
    Retrieval. Springer 2001.
  • Backgroud
  • D. Feng, W.C. Siu, H.J. Zhang. Multimedia
    Information Retrieval and Management,
    Technological Fundamentals and Applications
    Springer 2003.
  • A. del Bimbo. Visual Information Retrieval.
    Morgan Kaufmann 1999.
  • C. Faloutsos. Searching Multimedia Databases by
    Content. Kluwer 1996.
  • T. Gevers. Image Search Engines. Conference
    course at CVPR (Computer Vision and Pattern
    Recognition) 2001. (Some of the slides are taken
    from this course.)
  • O. Marques, B. Furht. Content-Based Image and
    Video Retrieval. Kluwer 2002.
  • R. Veltkamp, M. Tanase. Content-Based Image
    Retrieval Systems Survey. http//give-lab.cs.uu.nl
    /
  • R. Veltkamp, H. Burkhardt, H.-P. Kriegel.
    State-of-the-Art in Content-Based Image and Video
    Retrieval. Kluwer 2001.

7
Assignments
  • Motivation MM retrieval requires practical
    experience
  • Feature extraction, feature matching, performance
    comparison
  • This year 3D model retrieval

8
MM_at_UU
  • Shape-based image retrieval
  • Logo retrieval project Profi (Perceptually-releva
    nt Retrieval of Figurative Images)
  • Part-based retrieval project Mindshade (Matching
    and Indexing through Shape Decomposition)
  • Shape-based retrieval project Shame (Shame
    Matching Environment)
  • 3D Model retrieval
  • SHREC (3D Shape Retrieval Contests)
  • Project FOCUS-K3D (Foster the Comprehension and
    Use of Knowledge-intensive 3D-media )
  • Project AIM_at_SHAPE (Advanced Innovative Modeling
    of Shape)

9
MM_at_UU
  • Music retrieval
  • Project COGITCH (COgnition Guided
    Interoperability beTween Collections of musical
    Heritage)
  • Project Musiva (Musical similarity through
    variational principle)
  • Project Witchcraft (What Is Topical in Cultural
    Heritage Content-based Retrieval Among Folksong
    Tunes)
  • Project C-Minor (Cognition-based Music
    Information Notation Oriented Retrieval)
  • Project Orpheus (On-line Retrieval from
    Polyhymnia the Human-oriented Experimental
    Utrecht Searcher
  • Indexing
  • Project AMIS (Advanced Multimedia Indexing and
    Searching)

10
Media Technology Lab
  • Graphic workstations
  • Gaming devices
  • Digital video and photo camera
  • Video editing software
  • 3D shutter glasses
  • Web and file server
  • 3D scanners (2)
  • Fingerprint scanners
  • Motion capture, synched video cameras
  • (eye tracker)
  • (video wall)
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