Abstract
In this paper, a novel framework for search and retrieval of multimodal content is introduced as part of the EU-funded project I-SEARCH. The main objective of I-SEARCH is to create a unified framework for multimodal content search, i.e. to retrieve content of any media type (text, 2D images, video, audio and 3D) by using as query any of the above media, along with real-world information, expressive and social cues. The outcome will be a highly user-centric search engine, able to deliver to the end-users only the content of interest, satisfying their information needs and preferences, which is expected to significantly improve end-user’s experience. The paper will present the concept of I-SEARCH, as well as its major scientific advances.
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References
Flickr Photo Sharing, http://www.flickr.com/
Internet Archive, http://www.archive.org/
VICTORY project official website, http://www.victory-eu.org:8080/victory
Google SketchUp, http://sketchup.google.com/
I-SEARCH project official website, http://www.isearch-project.eu/
The Pharos Project, http://www.pharosproject.net/
The VITALAS Project, http://vitalas.ercim.org/
Worring, M., Gevers, T.: Interactive retrieval of color images. Int. J. Image Graph 1(3), 387–414 (2001)
Kokare, M., Biswas, P.K., Chatterji, B.N.: Texture image retrieval using new rotated complex wavelet filters. IEEE Transactions on Systems, Man, and Cybernetics, Part B 35(6), 1168–1178 (2005)
Attalla, E., Siy, P.: Robust shape similarity retrieval based on contour segmentation polygonal multiresolution and elastic matching. Pattern Recognition 38(12), 2229–2241 (2005)
Lowe, D.G.: Distinctive Image Features from Scale-Invariant Keypoints. Int. Journal of Computer Vision 60(2) (2004)
Joly, A., Frélicot, C., Buisson, O.: Feature statistical retrieval applied to content-based copy identification. In: Proc. of Int. Conf. on Image Processing (2004)
Law-To, J., Chen, L., Joly, A., Laptev, I., Buisson, O., Gouet-Brunet, V., Boujemaa, N., Stentiford, F.: Video Copy Detection: a Comparative Study. In: Proc. of the ACM International Conference on Image and Video Retrieval (2007)
Laptev, I., Lindeberg, T.: Local Descriptors for Spatio-Temporal Recognition. In: Proc. of ECCV (2004)
Zarpalas, D., Daras, P., Axenopoulos, A., Tzovaras, D., Strintzis, M.G.: 3D Model Search and Retrieval Using the Spherical Trace Transform., EURASIP Journal on Advances in Signal Processing, Article ID 239110 (2007)
Papadakis, P., Pratikakis, I., Perantonis, S., Theoharis, T.: Efficient 3D shape matching and retrieval using a concrete radialized spherical projection representation. Pattern Recognition 40(9), 2437–2452 (2007)
Daras, P., Axenopoulos, A.: A 3D Shape Retrieval Framework Supporting Multimodal Queries. International Journal of Computer Vision (July 2009), doi:10.1007/s11263-009-0277-2
Ohbuchi, R., Osada, K., Furuya, T., Banno, T.: Salient local visual features for shape-based 3D model retrieval. In: Proc. of the IEEE International Conference on Shape Modeling and Applications (SMI 2008), pp. 93–102 (2008)
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© 2012 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering
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Axenopoulos, A., Daras, P., Tzovaras, D. (2012). Towards the Creation of a Unified Framework for Multimodal Search and Retrieval. In: Alvarez, F., Costa, C. (eds) User Centric Media. UCMEDIA 2010. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 60. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35145-7_4
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DOI: https://doi.org/10.1007/978-3-642-35145-7_4
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