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Tracking and Localization

Filtering of position data in sports
  • In recent years, there has been an increasing demand for reliable and objective evaluation of sport specific data. The measurement and analysis of the trajectories of athletes is one possible approach to gain such insights. It allows the assessment of the physical performance and tactical behavior of athletes. Thus, it can yield helpful feedback for athletes, coaches and referees. Furthermore, spectators can be supplied with additional information about the accomplishments of their idols.

    Local Positioning Systems (LPS) provide a means for the measurement of athletes’ positions and motion trajectories. Although such systems can offer accurate position data under ideal measurement conditions, they often suffer from deficient behavior when used at a real sports venue. Since the LPS, which is used in this project, is based on radar, it is susceptible to multipath errors due to reflections of the signal on boards or stands. Besides, weather conditions influence the accuracy of the system. These issues cause deterioration in the reliability of the acquired raw data, so it cannot be used directly for performance or tactical analysis.

    Due to the lack of accuracy in the measurements, further signal processing is necessary to obtain useful information. In this project we try to overcome this problem by combining the measurements with physical constraints, sport specific motion models, plausibility considerations and probabilistic filtering.



Real-Time Localization in Sports Events
  • Sensor technology plays a major role in today´s sport events. It is used for the time measurement of races but also to analyze movements and to optimize tactics in team sports. Therefore, a reliable localization and tracking of the athletes (or their vehicles) is necessary. A further aspect of tracking single sportsmen is the entertainment of the audience who likes to get analyses of matches (e.g. the distance run by a soccer player) and real-time information about the current split times in races (e.g. in sailing).

    This project improves the localization of athletes in real-time by implementing a sensor data fusion of GPS information and additional inertial sensors. By only using a GPS to localize the current position of an athlete the result can be quite inaccurate. It is even worse if races take place in forests or areas with high-rise buildings. Additional inertial sensors (acceleration, gyroscope, ..) improve the accuracy of the system. A position filter which fulfills an appropriate sensor data fusion (GPS and inertial sensors) provides a reliable localization and allows tracking the target even in surroundings with limited GPS reception.



    Articles in Conference Proceedings
    Groh, Benjamin; Reinfelder, Samuel; Streicher, Markus; Taraben, Adib; Eskofier, Björn
    IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP 2014), Singapore, 22.04.2014, pp. 1-6, 2014 (BiBTeX, Who cited this?)