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Multimedia Retrieval Organization 2013/14, term 1

Multimedia Retrieval Organization 2013/14, term 1. Remco Veltkamp. 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@uu.nl. Schedule.

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Multimedia Retrieval Organization 2013/14, term 1

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  1. Multimedia RetrievalOrganization2013/14, 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@uu.nl

  3. Schedule • Ca. 11 lectures/topicsMondays 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@UU Shape-based image retrieval: • Logo retrieval: project Profi (Perceptually-relevant 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@SHAPE (Advanced Innovative Modeling of Shape)

  9. MM@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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