The ease of creation, storage and exchange of digital media (inc. image, video, 3D) over the WWW has imposed the definition of automated management strategies for this data. Furthermore, the immersion of the data into the social context provided by the Web 2.0 model has reinforced the need for high-level semantic management of the content but also fast and reliable transmission of the media over distributed heterogeneous networks.

Multimedia Information Systems, backed with automated content analysis tools, arising from Pattern Recognition and Computer Vision aims at providing ever better means to mine, access and finally use digital media. Image/video analysis and processing, information retrieval, pattern recognition and computer vision, multimedia data modeling, multidimensional indexing, data mining, machine learning, psychological modeling of user behavior, man-machine interaction, and information visualization, are only some of the most important research fields that contribute to this wide-spanning research area.

Pattern Recognition applies at all levels of these process, discovering structured information in places such as:

• Visual, Textual, Audio, 3D,… document content;
• Media collection content;
• Media usage trend.

APR’s Technical Committee 12 on Multimedia and Visual Information Systems promotes interaction among researchers working in modeling, design, and development of systems for the analysis, processing, description, and retrieval of multimedia and visual information as well as the applications of these systems in challenging domains. In particular, topics of primary interest are:

• Content analysis of images, videos, 3D models, and associated audio or text.
• Summarization of multimedia content.
• Multimedia mining.
• Cross-media mapping.
• Multimedia information retrieval, browsing, and visualization.
• Semantics based analysis of multimedia data.
• Innovative multimedia applications.

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