IWCIM: International Workshop on Computational Intelligence for Multimedia Understanding

Moroni D., Trocan M., Toreyin B. U.

ERCIM  MUSCLE Working Group  Computer vision  Signal processing  Multimedia understanding 

The International Workshop on Computational Intelligence for Multimedia Understanding (IWCIM) is the annual workshop organized by the working group Multimedia Understanding through Semantics, Computation and Learning (MUSCLE) of the European Research Consortium for Informatics and Mathematics (ERCIM). In this edition, IWCIM took place as a satellite workshop to SITIS 2019 held in Sorrento, Italy on November 26-29, 2019. Multimedia understanding is an essential 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 manage our everyday tasks. Nowadays, raw data usually come from a host of different sensors and other sources, and are different in nature, format, reliability and information content. Multimodal and cross-modal analysis 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 The scope of IWCIM 2019 includes, but is not limited to the following topics: oMultisensor systems oMultimodal analysis oCrossmodal data analysis and clustering oMixed-reality applications oActivity and object detection and recognition oText and speech recognition oMultimedia labeling, semantic annotation, and metadata oMultimodal indexing and searching in very large data-bases oBig and Linked Data oSearch and mining Big Data oLarge-scale recommendation systems oMultimedia and Multi-structured data oSemantic web and Linked Data oCase studies In this edition, 6 papers were submitted of which 4 have been accepted for oral presentation (acceptance ratio 66%).

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