Abstract
After text retrieval, the next waves in web searching and multimedia retrieval are the search for and delivery of images, music, video, and 3D scenes. Not only the perceptual and cognitive aspects, but also many of the algorithmic and performance aspects are still badly understood. One relevant issue is the design of dissimilarity measures (distance functions) that have desired properties. Another aspect is the development of algorithms that can compute or approximate these distances efficiently. Indexing data structures and search algorithms are necessary to make the search more efficient than sequential browsing through large collections. Apart from provable properties of individual algorithms, the experimental verification of the performance of a complete retrieval system is important to analyse merits and drawbacks of certain approaches, and to compare various techniques.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Smeulders, A.W., Worring, M., Santini, S., Gupta, A., Jain, R.: Content-Based Image Retrieval at the End of the Early Years. IEEE Transactions on Pattern Analysis and Machine Intelligence 22(12), 1349–1380 (2000)
Veltkamp, R.C., Tanase, M.: A Survey of Content-Based Image Retrieval Systems. In: Marques, O., Furht, B. (eds.) Content-Based Image and Video Retrieval, pp. 47–101. Kluwer, Norwell (2002)
Moret, B.: Towards a Discipline of Experimental Algorithmics. In: Goldwasser, M., Johnson, D., McGeoch, C. (eds.) Data Structures, Near Neighbor Searches, and Methodology: Fifth and Sixth DIMACS Implementation Challenges. DIMACS Monographs, vol. 59, pp. 197–213. American Mathematical Society, Providence (2002)
Biederman, I.: Recognition-by-Components: A Theory of Human Image Understanding. Psychological Review 94(2), 115–147 (1987)
Tănase, M., Veltkamp, R.C., Haverkort, H.J.: Multiple Polyline to Polygon Matching. In: Deng, X., Du, D.-Z. (eds.) ISAAC 2005. LNCS, vol. 3827, pp. 60–70. Springer, Heidelberg (2005)
Bober, M., Kim, J.D., Kim, H.K., Kim, Y.S., Kim, W.Y., and Muller, K.: Summary of the Results in Shape Descriptor Core Experiment, iso/iec jtc1/sc29/wg11/mpeg99/m4869 (1999)
Latecki, L.J., Lakaemper, R., Eckhardt, U.: Shape Descriptors for Non-Rigid Shapes with a Single Closed Contour. In: Proc. Conference on Computer Vision and Pattern Recognition (CVPR), pp. 424–429 (2000)
Mokhtarian, F., Abbasi, S., Kittler, J.: Efficient and Robust Retrieval by Shape Content through Curvature Scale Space. In: Proceedings of IDB-MMS’96, pp. 35–42 (1996)
Tanase, M.: Shape Deomposition and Retrieval. PhD Thesis, Utrecht University, Department of Computer Science (2005)
Veltkamp, R.C., Latecki, L.J.: Properties and Performances of Shape Similarity Measures. In: Batagelj, et al. (ed.) Data Science and Classification, Proceedings of the IFCS 2006 Conference, pp. 47–56. Springer, Heidelberg (2006)
Typke, R., Veltkamp, R.C., Wiering, F.: A Measure for Evaluating Retrieval Techniques Based on Partially Ordered Ground Truth Lists. In: Proceedings International Conference on Multimedia & Expo, ICME (2006)
Järvelin, K., Kekäläinen, J.: Cumulated Gain-Based Evaluation of IR Techniques. ACM Transactions on Information Systems 20(4), 422–446 (2002)
Vleugels, J., Veltkamp, R.C.: Efficient Image Retrieval through Vantage Objects. Pattern Recognition, pp. 69–80 (2002)
Henning, C., Latecki, L.J.: The Choice of Vantage Objects for Image Retrieval. Pattern Recognition, pp. 2187–2196 (2003)
van Leuken, R.H., Veltkamp, R.C., Typke, R.: Selecting Vantage Objects for Similarity Indexing. In: Proceedings of the 18th International Conference on Pattern Recognition, ICPR (2006)
Giannopoulos, P., Veltkamp, R.C.: A Pseudo-Metric for Weighted Point Sets. In: Heyden, A., Sparr, G., Nielsen, M., Johansen, P. (eds.) ECCV 2002. LNCS, vol. 2352, pp. 715–730. Springer, Heidelberg (2002)
Rubner, Y.: Perceptual Metrics for Image Database Navigation. PhD Thesis, Stanford University, Department of Computer Science (1999)
Bosma, M., Veltkamp, R.C., Wiering, F.: Muugle: A Music Retrieval Experimentation Framework. In: Proceedings of the 9th International Conference on Music Perception and Cognition, pp. 1297–1303 (2006)
Répertoire International des Sources Musicales (RISM): Serie A/II, manuscrits musicaux après 1600. K.G. Saur Verlag, München (2002)
Typke, R., Giannopoulos, P., Veltkamp, R.C., Wiering, F., van Oostrum, R.: Using Transportation Distances for Measuring Melodic Similarity. In: Proceedings of the Fourth International Conference on Music Information Retrieval (ISMIR 2003), pp. 107–114 (2003)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer Berlin Heidelberg
About this paper
Cite this paper
Veltkamp, R.C. (2007). Multimedia Retrieval Algorithmics. In: van Leeuwen, J., Italiano, G.F., van der Hoek, W., Meinel, C., Sack, H., Plášil, F. (eds) SOFSEM 2007: Theory and Practice of Computer Science. SOFSEM 2007. Lecture Notes in Computer Science, vol 4362. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69507-3_11
Download citation
DOI: https://doi.org/10.1007/978-3-540-69507-3_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-69506-6
Online ISBN: 978-3-540-69507-3
eBook Packages: Computer ScienceComputer Science (R0)