Informace o projektu
Searching, Mining, and Annotating Human Motion Streams
        
    
        - Kód projektu
- GA19-02033S
- Období řešení
- 1/2019 - 12/2021
- Investor / Programový rámec / typ projektu
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                        Grantová agentura ČR        - Standardní projekty
 
- Fakulta / Pracoviště MU
- Fakulta informatiky
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.
Publikace
Počet publikací: 21
2022
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    Enhancing the Learning Process of Folk Dances using Augmented Reality and Non-Invasive Brain StimulationEntertainment Computing, rok: 2022, ročník: 40, vydání: January 2022, DOI 
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    Tracking subjects and detecting relationships in crowded city videosMultimedia Tools and Applications, rok: 2022, ročník: Neuveden, vydání: January, DOI 
2021
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    Content-Based Management of Human Motion Data: Survey and ChallengesIEEE Access, rok: 2021, ročník: 9, vydání: 26 April 2021, DOI 
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    Data-driven Learned Metric Index: an Unsupervised Approach14th International Conference on Similarity Search and Applications (SISAP 2021), rok: 2021 
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    Efficient Combination of Classifiers for 3D Action RecognitionMultimedia Systems, rok: 2021, ročník: 27, vydání: 5, DOI 
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    Efficient Indexing of 3D Human MotionsACM International Conference on Multimedia Retrieval (ICMR), rok: 2021 
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    Efficient Retrieval of Human Motion Episodes Based on Indexed Motion-Word RepresentationsInternational Journal of Semantic Computing, rok: 2021, ročník: 15, vydání: 2, DOI 
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    FIMSIM: Discovering Communities By Frequent Item-Set Mining and Similarity Search14th International Conference on Similarity Search and Applications (SISAP), rok: 2021 
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    Learned metric index - proposition of learned indexing for unstructured dataInformation Systems, rok: 2021, ročník: 100, vydání: 101774, DOI 
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    SPEED21: Speed Climbing Motion DatasetMMSports'21: Proceedings of the 4th International Workshop on Multimedia Content Analysis in Sports, rok: 2021