John R. Smith
Liangliang Cao
ABSTRACT
Visual data is exploding! 500 billion consumer photos are taken each year world-wide, 633 million photos taken per year in NYC alone. 120 new video-hours are uploaded on YouTube per minute. The explosion of digital multimedia data is creating a valuable open source for insights. However, the unconstrained nature of 'image/video in the wild' makes it very challenging for automated computer-based analysis. Furthermore, the most interesting content in the multimedia files is often complex in nature reflecting a diversity of human behaviors, scenes, activities and events. To address these challenges, this tutorial will provide a unified overview of the two emerging techniques: Semantic modeling and Massive scale visual recognition, with a goal of both introducing people from different backgrounds to this exciting field and reviewing state of the art research in the new computational era.
- L. Cao, L. Gong, J. R. Kender, N. C. Codella, and J. R. Smith. Learning by focusing: A new framework for concept recognition and feature selection. Proc. of IEEE Conference on Multimedia and Expo, 2013.Google Scholar
- A. Hanjalic, R. Lienhart, W.-Y. Ma, and J. R. Smith. The holy grail of multimedia information retrieval: So close or yet so far away? Proc. IEEE, 94(4):541--547, 2008.Google ScholarCross Ref
- M. Naphade, J. R. Smith, J. Tesic, S.-F. Chang, W. Hsu, L. Kenendy, A. Hauptmann, and J. Curtis. Large-scale concept ontology for multimedia. IEEE MultiMedia, 13(3), July-September 2006. Google ScholarDigital Library
- J. R. Smith. History made everyday. IEEE MultiMedia, 18(2), July-September 2011. Google ScholarDigital Library
- J. R. Smith. Minding the gap. IEEE MultiMedia, 19(2):53--62, January-March 2012.Google Scholar
- J. R. Smith. Just the facets. IEEE MultiMedia, 20(1), January-March 2013. Google ScholarDigital Library
- L. Xie, A. Natsev, J. R. Kender, M. Hill, and J. R. Smith. Visual memes in social media: Tracking real-world news in youtube videos. Proc. of the 19th ACM Intl. Conf. on Multimedia, pages 53--62, November 2011. Google ScholarDigital Library
- R. Yan, M. O. Fleury, M. Merler, A. Natsev, and J. R. Smith. Large-scale multimedia semantic concept modeling using robust subspace bagging and map-reduce. Proc. of the First ACM Workshop on Large-Scale Multimedia Retrieval, 2009. Google ScholarDigital Library
- F. Yu, L. Cao, R. S. Feris, J. R. Smith, and S.-F. Chang. Designing category-level attributes for discriminative visual recognition. Proc. of IEEE Conference on Computer Vision and Pattern Recognition, 2013. Google ScholarDigital Library
Index Terms
- Massive-scale multimedia semantic modeling
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