Course Name: 

Topics In Multimedia Information Retrieval (IT932)



Credits (L-T-P): 



Introduction to multimedia information retrieval, Characteristics of MM data; similarity-based retrieval model- retrieval framework; feature engineering for multimedia, feature selection and extraction techniques, Color-based Retrieval: color models; histogram model; indexing and retrieval; relevance feedback; histogram refinement; color cluster technique; Texture-based Retrieval: texture models; statistical models; combined color-texture representation; Shape-based Retrieval: shape matching; contour -based method (Fourier descriptors); region-based method (moment invariants); Audio Retrieval: characteristics of audio data; spectrum analysis; pitch tracking; techniques for audio feature extraction, similarity matching and retrieval; Video Retrieval: Video segmentation in raw and compressed domain; key-frame extraction; video summarization and retrieval techniques; Multimedia Retrieval Framework: multi-attribute query processing; knowledge-based methods, Evaluation metrics for multimedia information systems; benchmarking, Multimedia Retrieval Trends, Applications; Research Problems.


R. Jain, R. Kasturi, B.G. Schunck (1995), Machine Vision, McGraw-Hill.
B. Furht, S.W. Smoliar, H.J. Zhang (1995), Video and Image Processing in Multimedia Systems, Kluwer, Boston.
Roberto Raieli, “Multimedia Information Retrieval- Theory and Techniques”, Elsevier, 1st Edition, 2013
Mark T Maybury, “Intelligent Multimedia Information Retrieval”, AAAI Press, MIT Press
C. D. Manning et al., Introduction to Information Retrieval, Cambridge University Press. 2008.
Baeza-Yates & Ribeiro-Neto, Modern Information Retrieval, Pearson Education,2010


Information Technology

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Head of the Department,
Department of Information Technology,
National Institute of Technology Karnataka,
SurathkalP. O. Srinivasnagar, Mangalore - 575 025
Ph.:    +91-824-2474056
Email:  hodit [at] nitk [dot] edu [dot] in

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