Currently, we work on the following projects:

  • Searching, Mining, and Annotating Human Motion Streams
    Czech Science Foundation, 2019–2021
    Motion capturing devices have become widely available, which resulted in large volumes of 3D human motion data produced in a variety of application domains, ranging from entertainment to medicine. However, automatized processing of such data is a challenging problem because their inherent spatio-temporal nature implies that the same action can be performed in a number of alternatives that vary in speed, timing, or location in space. Moreover, the captured data are imprecise and voluminous, as hundreds of megabytes per hour are obtained during tracking only 3D positions of body joints. Therefore, the employment of basic data-processing paradigms is much more intriguing, when compared to the traditional domains such as text or images. In the proposed project, we aim at developing new theories and technologies for three interconnected open problems of content-based searching, annotating, and mining in motion data streams. Taking into account the fast growth of motion data volumes, a lot of attention will be given to the scalability of proposed solutions.
  • Big Data Analytics for Unstructured Data
    Czech Science Foundation, 2016–2018
    Development of new foundations for Big Data Analytics requires an effective and efficient content-based access to data that is prevalently unstructured. For this data, to achieve the needed integration of large-scale knowledge discovery techniques with statistical modelling, it is necessary to first uncover descriptive knowledge of complex and heterogeneous objects to make them findable. Then, scalable search structures are needed to efficiently execute similarity access operations, considering also simultaneous execution of multiple queries. More information
  • Center for Large-Scale Multi-Modal Data Interpretation
    Czech Science Foundation, 2012–2018
    This project aims at exploiting large collections of unlabeled multi-modal data, mainly video footage, to further state-of-the-art in video, audio and natural language understanding, interpretation, annotation and retrieval by combining unsupervised and semi-supervised learning. It will address problems that are very difficult (some probably impossible) to solve in a single modality by adopting an interdisciplinary approach. More information

Selected Past Projects

  • Effective Search in Large-Scale Biometric Data
    Ministry of Interior of the CR, 2012 – 2015
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  • Research of Technologies Suitable for Face Recognition That Can Be Used For Multimedia Retrieval on Internet
    Ministry of Education, Youth and Sports of the CR, 2012 – 2014
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  • Multimedia Analysis
    Ministry of Interior of the CR, 2010 – 2014
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  • Content-based Image Retrieval on the Web Scale
    Czech Science Foundation, 2010 – 2012
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  • Similarity Searching in Very Large Multimedia Databases
    Czech Science Foundation, 2009 – 2011
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  • Search on Audio-visual content using Peer-to-peer Information Retrieval (SAPIR)
    European Union / 6th Specific RTD Programme, 2006 – 2009
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  • Network of Excellence on Digital Libraries (DELOS)
    European Union / 6th Specific RTD Programme, 2003 – 2007
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