Abstract
During recent years, a new framework, which aims to bring a unified and global approach in indexing, browsing and querying various digital multimedia data such as audio, video and image has been developed. This new system partitions each media stream into smaller units based on actual physical events. These physical events within each media stream can then be effectively indexed for retrieval. In this paper, we present a new approach that exploits audio, image and video features to segment and analyze the audio-visual data. Integration of audio and visual analysis can overcome the weakness of previous approach that was based on the image or video analysis only. We implement a web-based multimedia data retrieval system called XCRAB and report on its experiment result.
This research was supported by University IT Research Center Project.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Jiang, H., Lin, T., Zhang, H.: Video segmentation with the Support of Audio Segmentation and classification. In: ICME 2000-IEEE International Conference on Multimedia and Expo, New York City, NY, USA, July 30-August 2 (2000)
Yoshitaka, A., Miyake, M.: Scene Detection by Audio-Visual Features. In: IEEE International Conference on Multimedia and Expo (ICME 2001), pp. 49–52 (2001)
Li, D., Sethi, I.K., Dimitrova, N., McGee, T.: Classification of general audio data for content-based retrieval. Pattern Recognition Letters 22(5), 533–544 (2001)
Chen, S.-C., Shyu, M.-L., Liao, W., Zhang, C.: Scene Change Detection By Audio and Video Clues. In: IEEE International Conference on Multimedia and Expo (ICME 2002), pp. 365–368 (2002)
Rho, S., Hwang, E.: FMF(Fast Melody Finder): A Web-based Music Retrieval System. In: Wiil, U.K. (ed.) CMMR 2003. LNCS, vol. 2771, pp. 179–192. Springer, Heidelberg (2004)
Rho, S., Hwang, E.: Video Scene Determination using Audiovisual Data Analysis. In: Proc. of the 24th International Conference on Distributed Computing Systems (ICDCS 2004) Workshops - Multimedia Network Systems and Applications (MNSA 2004), Tokyo, Japan (March 2004) (to appear)
Lee, S., Hwang, E.: Spatial Similarity and Annotation-Based Image Retrieval System. In: IEEE Fourth International Symposium on Multimedia Software Engineering, Newport Beach, CA (December 2002)
Niblack, W., et al.: The QBIC project: Query images by content using color, texture and shape. In: SPIE, vol. 1908 (1993)
Ogle, V.E., Stonebraker, M.: Chabot: Retrieval from a Relational Database of Images. IEEE Computer 28(9) (September 1995)
Egenhofer, M.J., Franzasa, R.D.: Point set topological spatial relations. Journal of Geographical Information Systems 5(2), 161–174 (1991)
Chang, S., Shi, Q., Yan, S.: Iconic indexing using 2-D strings. IEEE Trans. on Pattern Analysis & Machine Intelligence 9(3), 413–428 (1987)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Rho, S., Lee, S., Hwang, E., Lee, Y. (2004). XCRAB: A Content and Annotation-Based Multimedia Indexing and Retrieval System. In: Laganá, A., Gavrilova, M.L., Kumar, V., Mun, Y., Tan, C.J.K., Gervasi, O. (eds) Computational Science and Its Applications – ICCSA 2004. ICCSA 2004. Lecture Notes in Computer Science, vol 3046. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24768-5_92
Download citation
DOI: https://doi.org/10.1007/978-3-540-24768-5_92
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22060-2
Online ISBN: 978-3-540-24768-5
eBook Packages: Springer Book Archive