Call For Papers


Multimedia understanding is an important part of many intelligent applications in our social life, be it in our households, or in commercial, industrial, service, and scientific environments. Analyzing raw data to provide them with semantics is essential to exploit their full potential and help us managing our everyday tasks. Nowadays, raw data normally come from a host of different sensors and other sources, and are different in nature, format, reliability and information content. Multimodal and cross-modal analyses are the only ways to use them at their best. Besides data analysis, this problem is also relevant to data description intended to help storage and mining. Interoperability and exchangeability of heterogeneous and distributed data is a need for any practical application. Semantics is information at the highest level, and inferring it from raw data (that is, from information at the lowest level) entails exploiting both data and prior information to extract structure and meaning. Computation, machine learning, statistical and Bayesian methods are tools to achieve this goal at various levels.

Scope and Topics

Our purpose is to provide an international forum to present and discuss current trends and future directions in computational intelligence for multimedia understanding. The workshop, organized by the ERCIM MUSCLE Working Group, also aims at fostering the creation of a permanent network of scientists and practitioners for an easy and immediate access to people, data and ideas. The scientific program, organized in a single-session format, consists of invited lectures, contributed talks, and poster presentations. We are looking for original and high-quality submissions addressing multimedia processing and understanding methodologies, ranging from statistical, neural, evolutionary methods to mixed reality and multisensor interaction, as well as a variety of applications, in the areas of public services, transport/mobility, aids to impaired people, process control and diagnosis, remote sensing, and beyond. Active participation of graduate students is strongly encouraged.

Suggested topics include, but are not limited to:

  • Multisensor systems
  • Multimodal analysis
  • Crossmodal data analysis and clustering
  • Mixed-reality applications
  • Activity and object detection and recognition
  • Text and speech recognition
  • Multimedia labeling, semantic annotation, and metadata
  • Multimodal indexing and searching in very large data-bases
  • Case studies
  • Microscopic Image Segmentation and Model-based Representation
  • Microscopic Image Feature Extraction and Classification

Review and Publication

All submitted papers will be peer-reviewed. Accepted papers will be published in IEEE Xplore. Selected papers will be published in Signal, Image and Video Processing after further review.

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