Motion Data Processing

Current motion capturing technologies (e.g., Microsoft Kinect, Vicon Vantage, Asus Xtion…) record human motions at high frame-per-second rates. Motions are recorded as a series of 3D coordinates of body joints in space and time. The recorded motion data can be processed and utilized in a variety of applications, for example, in sports for comparing the performance of athletes, in security for identifying special-interest persons, in medicine for determining the success of rehabilitative treatments. All these applications require an effective and efficient (sub)motion-to-motion similarity matching.

Our Research

• Demos: to get acquinted with our research, you may visit try one of our demo applications
• Data: in the course of our research, we have created several new resources for motion data processing, which we offer to the scientific community

Related Publications

• J. Sedmidubsky, P. Elias, P. Budikova, P. Zezula: Content-Based Management of Human Motion Data: Survey and Challenges. IEEE Access. IEEE, 2021. doi:10.1109/ACCESS.2021.3075766.
• P. Budikova, J. Sedmidubsky, J. Horvath, P. Zezula: Towards Scalable Retrieval of Human Motion Episodes. In IEEE International Symposium on Multimedia (ISM). IEEE, 2020. doi:10.1109/ISM50513.2020.
• J. Sedmidubsky, P. Budikova, V. Dohnal, P. Zezula: Motion Words: A Text-like Representation of 3D Skeleton Sequences. In 42nd European Conference on Information Retrieval (ECIR). Cham: Springer, 2020. doi:10.1007/978-3-030-45439-5_35.
• J. Sedmidubsky, P. Elias, P. Zezula: Searching for Variable-Speed Motions in Long Sequences of Motion Capture Data. Information Systems, Elsevier, 2019. doi:10.1016/j.is.2018.04.002.
• F. Carrara, P. Elias, J. Sedmidubsky, P. Zezula: LSTM-Based Real-Time Action Detection and Prediction in Human Motion Streams. Multimedia Tools and Applications, Springer US, 2019. doi:10.1007/s11042-019-07827-3.
• J. Sedmidubsky, P. Elias, P. Zezula: Benchmarking Search and Annotation in Continuous Human Skeleton Sequences. In International Conference on Multimedia Retrieval (ICMR 2019). New York, NY, USA: ACM, 2019. doi:10.1145/3323873.3325013.
• J. Sedmidubsky, P. Elias, P. Zezula: Effective and Efficient Similarity Searching in Motion Capture Data. Multimedia Tools and Applications, Springer US, 2018. doi:10.1007/s11042-017-4859-7.
• J. Valcik, J. Sedmidubsky, P. Zezula: Assessing similarity models for human-motion retrieval applications. Computer Animation and Virtual Worlds, John Wiley & Sons Ltd. ISSN 1546-427X, 2015. doi: 10.1002/cav.1674.
• J. Sedmidubsky, J. Valcik, P. Zezula: A Key-Pose Similarity Algorithm for Motion Data Retrieval. In 12th International Conference on Advanced Concepts for Intelligent Vision Systems (ACIVS 2013). Springer-Verlag, 2013. doi: 10.1007/978-3-319-02895-8_60.