Background

One important achievement of the Muscle group is the Muscle Network of Excellence, partially funded by the European Commission (FP6-507752, 1 March 2004 - 29 February 2008), managed by ERCIM and coordinated by Eric Pauwels (CWI, NL) and Nozha Boujemaa (INRIA, F)

The Signal & Images Lab at ISTI-CNR (SI Lab) is working in the fields of signal processing, image understanding and artificial vision. Sensorial information is increasing its importance in both our everyday lives and the most advanced technological and scientific contexts. In particular, visual and audio information is becoming the most significant part of the global information to be processed, understood and manipulated. Our general goal is to increase the knowledge in signal processing, image understanding and artificial vision. This will be achieved by studying and developing models, methods and machines for the formation, processing, analysis and recognition of images and signals, and by applying them to several areas of scientific and technological interest.

The AYIN project-team (Ayin) is located at INRIA Sophia-Antipolis Méditerranée and aims to provide image processing tools to aid in the solution of problems arising in a wide range of concrete applications in Earth observation and cartography, for example cartographic updating, land management, and agriculture, while at the same time advancing the state of the art in the image processing methods used to construct those tools. An important recent theme, for example, is the incorporation of geometric information into stochastic and variational techniques, in the probabilistic case via the use of stochastic geometry, and in the variational case via the use of higher-order active contours.

TAU-VISUAL specializes in the extraction and processing of visual information from video and still images. The group has substantial expertise in the use of variational methods to solve fundamentally difficult problems, such as restoration, registration and segmentation of images and video. Typical application domains include medical image analysis, image retrieval, video analytics, environmental monitoring and 3D image acquisition.

Bilkent EE Signal Processing group is interested in multimedia signal processing topics including Image, Video, Speech, 3D signal processing issues. Specific research topics of the group includes; Human-Computer Interaction using vision and speech, Audio-Visual Multimedia Databases, Speech Processing, Digital Coding of Waveforms ( Image, Video, Speech, and Biomedical Signals), Adaptive Filtering and Adaptive Subband Coding, Wavelet Transform and Applications, Time Series Analysis and Stochastic Processes, Signal Processing for Food Safety and Color Image Dithering. The groups is currently involved in 2 EU projects: FIRESENSE and MIRACLE.

The Computer Vision and Multimedia Laboratory (CVML ) of the University of Geneva is divided into three groups and carries out research in multimedia data processing, multimedia data management and security, as well as in multimodal human-machine interaction. Content-based Visual Indexing and Retrievalgroup: develops strategies for the efficient indexing retrieval and exploration of large multimedia databases. Stochastic Information Processing group: studies various aspects of information theory and statistical (stochastic) information analysis and processing. Multimodal Interaction group: studiesvarious forms of interaction between humans, computers, and environment. Some considered interaction modalities are haptic, auditory, and based on physiological signals. Current developments concern: affective state determination and emotion recognition and their use for affective computing, multimodal interaction, brain-computer interfaces, mobility aids for sight handicapped people,object identification and authentication based on unclonable object features in large nonstructured databases, indexing and retrieval in very large multimedia databases, privacy preserving search, indexing and multiclass classification.

The School of Computer Science and Statistics in Trinity College Dublin has two collaborating groups, GV2 and Statica, that carries out activities on multimedia data (e.g. images, video and sound), sensor network data (e.g. road trafic, communications networks, camera network, motion capture) and environmental data (e.g. weather). STATICA focuses on Bayesian inference to solve statistical problems that arise in computer science, information systems and telecommunications focusing on developing statistical techniques to analyse large and complex data. GV2, the Graphics Vision and Visualisation group, has expertises in computer graphics, computer vision and all aspects of visual computing. GV2 was formed in 2006 with the integration of two longstanding TCD research groups: the Image Synthesis Group [ISG], established in 1993, and the Computer Vision and Robotics Group [CVRG], which was established 1983.

The overall goal of the Signal and Images group at CWI is to understand and interpret multimedia data using mathematical tools, including stochastic geometric modelling, Monte Carlo methods, and statistical learning. Recent applications include object recognition and tracking, segmentation, prediction and detection of salient events, and content-based image retrieval.

The Institute of Computer Vision and Applied Computer Sciences (IBaI) was founded in 1995. The institute conducts basic and applied research in computer vision, data mining, machine learning, and for image databases. The institute has an excellent staff of highly-qualified researchers from various fields such as computer science, mathematics, electrical engineering, and physics. It has modern equipment and excellent facilities for conducting scientific research. The IBaI is involved in various national and international research projects and RTD projects. The institute is engaged in the developement of research themes such as Machine Learning and Data Mining in Pattern Recognition and Case-Based Reasoning in Computer Vision and Image Processing on the international level. Therefore the institute offers several scientific events such as MLDM, ICDM, MDA and technical committees. The institute provides courses(e.g. Tutorial Days Data Mining) on data mining and computer vision.

T.E.A. sas di E. Console & C. is a company based in Catanzaro (Italy), member of the Italian National Research Registry since 2003. The main sectors of activity of T.E.A. are Statistical Consulting (sample surveys, market research and marketing, studies and socio-economic research), Project Management and Technical Assistance, (project planning and implementation, especially for EU projects), Geo-Information (design and implementation of GIS and Web-GIS systems, environmental monitoring, planning and management of resources, geo-marketing, digital image processing, thematic maps), and Cultural Heritage, (hyper/multispectral imaging of documents and artifacts, reflexographic analysis for non-invasive diagnostics, virtual restoration for improving the readability and recovering hidden features in documents and paintings).

Texmex is a joint research group of IRISA and of INRIA, located in Rennes, France. It aims at developing techniques to facilitate the use or reuse of large collections of multimedia documents. The group focuses on the problem raised by very large-scale collection and on multimodal document analysis. The originality of our approach comes from the simultaneous consideration of the constraints dependent on the media and the documents and of the constraints related to the exploitation of these data, which are two aspects of the same problem. We develop multidisciplinary approaches based on media processing techniques (image, video, text, speech) and data analysis and management techniques (data analysis, machine learning, database management).

ARMINES is a non-profit French association which acts as the industrial interface serving engineering schools. CMM is a joint research laboratory of ARMINES and MINES ParisTech. Since the CMM was founded in 1967, it has contributed to the growth and dissemination of the theoretical and algorithmic corpus of mathematical morphology, through a very broad field of applications, thereby providing a rich experimental terrain for the development of new concepts and tools. For 40 years now, the CMM has been developing a powerful theoretical framework for image processing, called Mathematical Morphology. The CMM has acquired a leading position in the fields of mathematical foundations of the theory, efficient algorithms design, resolution of applications involving image processing, development of multimedia applications, and specific hardware development. The CMM has capitalized its expertise through common software libraries, creating a synergy between all applications in which the CMM is involved. These libraries provide advanced tools for filtering, segmentation, feature extraction, hyper-spectral image analysis and 3D point cloud analysis. contact : Beatriz.Marcotegui@mines-paristech.fr