1 / 3

Introduction Color Texture Shape Sketch Blobs+Spatial Interaction High-Level Representation

Computer Vision Seminar - Image Retrieval. Date. Topic. Student Names. Student e-mail. Student Phones. Introduction Color Texture Shape Sketch Blobs+Spatial Interaction High-Level Representation Compressed Image Retrieval Learning Text+Image Features - Retrieval from WWW

afi
Download Presentation

Introduction Color Texture Shape Sketch Blobs+Spatial Interaction High-Level Representation

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Computer Vision Seminar - Image Retrieval Date Topic Student Names Student e-mail Student Phones Introduction Color Texture Shape Sketch Blobs+Spatial Interaction High-Level Representation Compressed Image Retrieval Learning Text+Image Features - Retrieval from WWW Navigation in Image Space Video Retrieval 21/11/99 28/11/99 4/11/99 11/11/99 18/11/99 25/11/99 2/12/99 9/12/99 30/12/99 6/1/00 13/1/00 20/1/00

  2. Computer Vision Seminar - Image Retrieval Lecture 1 - Introduction • F. Idris and S. Panchanathan,  “Review of Image and Video Indexing Techniques”, Journal of • Visual Communication and Image Representation, Vol 8, No. 2, June, pp.146-166, 1997. • R. W. Picard , "Lightyears from Lena: Image and Video Libraries of the Future", IEEE Int. Conf. on Image • Processing, ICIP 95, Special Session on Digital Image/Video Libraries and Video-on-demand, Oct. 1995, • Washington DC. Lecture 2 - Color • M. Swain and D. Ballard, "Color Indexing," International Journal of Computer Vision, Vol 7, No.1, 11-32, 1991. • J. Huang et al, "Image Indexing Using Color Correlograms," Proceedings Computer Vision and Pattern • Recognition-CVPR97, 1997. • G. Lu and J. Phillips,"Using Perceptual Weighted Histograms for Colour-based Image Retrieval", • J. Huang and R. Zabih, "Combining Color and Spatial Information for Content-based Image Retrieval". • Y. Rubner, C. Tomasi and L.J. Guibas, "The Earth Mover's Distance as a Metric for Image Retrieval". Lecture 3 - Texture • B. S.Manjunath and W. Y. Ma, “Texture Features for Browsing and Retrieval of Image Data”, IEEE • Transactions on Pattern Analysis and Machine Intelligence, Vol. 18, No. 8, August 1996. • R. Picard and T. Minka, “Visual Texture for Annotation,” MIT Media Lab report No. 302. • Y. Rubner and C. Tomasi, "Texture Metrics". Lecture 4 - Shape • H. Nishida, "Shape Retrieval from Image Databases Through Structural Feature Indexing", • Vision Interface 99, Trois-Rivieres, Canada, 19-21 May 1999. • Y. Gdalyahu and D. Weinshall, "Flexible Syntactic Matching of Curves and its Application to Automatic • Hierarchical Classification of Silhouettes". • B. Scassellati, S. Alexopoulos and M. Flickner, "Retrieving Images by 2D Shape: a Comparison of • Computation methods with Human Perceptual Judgments". • NETRA: A Toolbox for Navigating Large Image Database", IEEE Int. Conf. on Image Processing, ICIP99. Lecture 5 - Sketch • T. Kato, T. Koritu, N. Otso and K. Hirata, "Asketch Retrieval Method for Full Color Image Database", • International Conference on Pattern Recognition-ICPR92, pp. 530-533, 1992. • C.E. Jacobs, A. Finkelstein and D.H. Salesin, Fast Multiresolution Image Querying", Proceedings of • SIGGRAPH95, Los Angeles CA, August 6-11, 1995. • W. Niblack, R. Barber, W. Equitz, M. Flickner, E. Glasman, D. Petkovic, and P. Yanker, "The QBIC project: • querying images by content using colour, texture and shape,'' IS&T/SPIE 1993 Int. Symp. Electronic Imaging: • Science and Technology, Conference,Storage and Retrieval for Image and Video Databases, Vol. 1908, 1993. Lecture 6 - Blobs and Spatial Interaction • C. Carson, S. Belongie, H. Greenspan, and J. Malik, "Region-based Image Querying'', Proceedings of the • IEEE Workshop on Content-based Access of Image and Video Libraries - CVPR97, pp. 42--49, 1997. • S.J. Cho and S.I. Yoo, "MCEBC - A Blob Coloring Algorithm for Content-Based Image Retrieval System", • 8th Int. Conf. on Comp. Analysis of Images and Patterns - CAIP99, Ljubljana, Slovenia, pp. 9-16, Sept. 1999. • Lecture Notes in CS Vol 1689, F. Soliha and A. Leonardis Eds. • J.R. Smith and S.F. Chang, "Querying by Color Regions using the VisualSEEk Content-Based Visual • Query System".

  3. Lecture 7 - High Level Image Representation • V. Castelli, C.S. Li and L.D. Bergman, "Searching image Databases at Multiple Levels of Abstraction", • IBM Research Report RC 20702 (91227) 1/28/97. • D. Dori and H.Z. Hel-Or, "Semantic Content Based Image Retrieval Using Object-Process Diagrams'', • Proceedings of the 7th International Workshop on Structural and Syntactic Pattern Recognition - SSPR98, • Vol. 1451, pp. 230-241, Sydney Australia, 1998. Lecture 8 - Compressed Image Retrieval • C.E. Jacobs, A. Finkelstein and D.H. Salesin, Fast Multiresolution Image Querying", Proceedings of • SIGGRAPH95, Los Angeles CA, August 6-11, 1995. • G. Lu and S. Teng, "A Novel Image Retrieval Technique Based on Vector Quantization". • M. Shenier and M. Abdel-Mottaleb, "Exploiting the JPEG Compression Scheme for Image Retrieval", • IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 18, No. 8, August 1996, pp.849-853. • C. Chen and R. Wilkinson, "Image Retrieval Using Multiresolution Wavelet Decomposition", Proceedings of • Int. Conf. on Computational Intelligence and Mulimedia Applications, 9-11 Feb, Australia, pp. 824-829. • F. Idris and S. Panchanathan, "Algorithms for Indexing of Compressed Images", Proceedings of Int. Conf. on • Visual Information Systems, Melbourne, Feb 1996, pp.303-308. Lecture 9 - Learning • T. Minka, "An Image Database Browser that Learns from User Interaction", MIT Media Laboratory • Technical Report 365. • T.P. Minka and R.W. Picard, "Interactive Learning using a Society of Models", MIT Media Laboratory • Technical Report 349. • T. Kurita and T. Kato, "Learning of Personal Visual Impression for Image Database Systems". Lecture 10 - Text + Image Features - Retrieval from the Internet • G. Lu and B. Williams, "An Integrated WWW Image Retrieval System", 5th Australian World Wide Web • Conf - AUSWEB99, Lismore, Australia. http://ausweb.scu.edu.au/aw99/papers/lu/paper.html • M.J. Swain, C. Frankel and V. Athitsos, "WebSeer: An Image Search Engine for the World Wide Web", • Proc. Computer Vision and Pattern Recognition - CVPR97. • J.R. Smith and S.F. Chang, "Querying by Color Regions using the VisualSEEk Content-Based Visual • Query System". • Yahoo Image Search etc. Lecture 11 - Navigation in Image Space • Y. Rubner, L. Guibas and C. Tomasi, "The Earth Mover's Distance, Multi-Dimensional Scaling, and • Color-Based Image Retrieval". • Y. Rubner, C. Tomasi and L.J. Guibas, "Adaptive Color-Image Embeddings for Database Navigation", • Proc. of the IEEE Asian Conf. on Computer Vision, Hong Kong, 1998. • Y. Rubner, L. Guibas and C. Tomasi, "Navigating Through a Space of Color Images", Proc. Computer • Vision and Pattern Recognition - CVPR97. • D.F. Jerding and J.T. Stasko, "The Information Mural: A Technique for Displaying and Navigating Large • Information Spaces", Proceedings of SIGGRAPH. Lecture 12 - Video Retrieval • M. Irani and P. Anandan, "Video Indexing Based on Mosaic Representations". • J.S. Wachman and R.W. Picard, "Tools for Browsing a TV Situation Comedy Based on Content • Specific Attributes". • C.W. Chang and S.Y. Lee, "Video Content Representation, Indexing and Matching in Video Information • Systems.

More Related