Paper
17 January 2006 Multimedia content analysis, management and retrieval: trends and challenges
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Proceedings Volume 6073, Multimedia Content Analysis, Management, and Retrieval 2006; 607301 (2006) https://doi.org/10.1117/12.673788
Event: Electronic Imaging 2006, 2006, San Jose, California, United States
Abstract
Recent advances in computing, communications and storage technology have made multimedia data become prevalent. Multimedia has gained enormous potential in improving the processes in a wide range of fields, such as advertising and marketing, education and training, entertainment, medicine, surveillance, wearable computing, biometrics, and remote sensing. Rich content of multimedia data, built through the synergies of the information contained in different modalities, calls for new and innovative methods for modeling, processing, mining, organizing, and indexing of this data for effective and efficient searching, retrieval, delivery, management and sharing of multimedia content, as required by the applications in the abovementioned fields. The objective of this paper is to present our views on the trends that should be followed when developing such methods, to elaborate on the related research challenges, and to introduce the new conference, Multimedia Content Analysis, Management and Retrieval, as a premium venue for presenting and discussing these methods with the scientific community. Starting from 2006, the conference will be held annually as a part of the IS&T/SPIE Electronic Imaging event.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Alan Hanjalic, Nicu Sebe, and Edward Chang "Multimedia content analysis, management and retrieval: trends and challenges", Proc. SPIE 6073, Multimedia Content Analysis, Management, and Retrieval 2006, 607301 (17 January 2006); https://doi.org/10.1117/12.673788
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Cited by 6 scholarly publications.
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KEYWORDS
Multimedia

Analytical research

Document management

Chemical elements

Video

Data modeling

Facial recognition systems

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