There is a large variety of trackers, which have been proposed in the literature during the last two decades with some mixed success. Object tracking in realistic scenarios is a difficult problem, therefore, it remains a most active area of research in computer vision. A good tracker should perform well in a large number of videos involving illumination changes, occlusion, clutter, camera motion, low contrast, specularities, and at least six more aspects. However, the performance of proposed trackers have been evaluated typically on less than ten videos, or on the special purpose datasets. In this paper, we aim to evaluate trackers systematically and experimentally on 315 video fragments covering above aspects. We selected a set of nineteen trackers to include a wide variety of algorithms often cited in literature, supplemented with trackers appearing in 2010 and 2011 for which the code was publicly available. We demonstrate that trackers can be evaluated objectively by survival curves, Kaplan Meier statistics, and Grubs testing. We find that in the evaluation practice the F-score is as effective as the object tracking accuracy (OTA) score. The analysis under a large variety of circumstances provides objective insight into the strengths and weaknesses of trackers.

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Visual Tracking: An Experimental Survey

Recent technological developments have led to the production of inexpensive, non-invasive, miniature magneto-inertial sensors, ideal for obtaining sport performance measures during training or competition. This systematic review evaluates current evidence and the future potential of their use in sport performance evaluation. Articles published in English (April 2017) were searched in Web-of-Science, Scopus, Pubmed, and Sport-Discus databases. A keyword search of titles, abstracts and keywords which included studies using accelerometers, gyroscopes and/or magnetometers to analyse sport motor-tasks performed by athletes (excluding risk of injury, physical activity, and energy expenditure) resulted in 2040 papers. Papers and reference list screening led to the selection of 286 studies and 23 reviews. Information on sport, motor-tasks, participants, device characteristics, sensor position and fixing, experimental setting and performance indicators was extracted. The selected papers dealt with motor capacity assessment (51 papers), technique analysis (163), activity classification (19), and physical demands assessment (61). Focus was placed mainly on elite and sub-elite athletes (59%) performing their sport in-field during training (62%) and competition (7%). Measuring movement outdoors created opportunities in winter sports (8%), water sports (16%), team sports (25%), and other outdoor activities (27%). Indications on the reliability of sensor-based performance indicators are provided, together with critical considerations and future trends.

Trends Supporting the In-Field Use of Wearable Inertial Sensors for Sport Performance Evaluation: A Systematic Review

Until recently tactical analysis in elite soccer were based on observational data using variables which discard most contextual information. Analyses of team tactics require however detailed data from various sources including technical skill, individual physiological performance, and team formations among others to represent the complex processes underlying team tactical behavior. Accordingly, little is known about how these different factors influence team tactical behavior in elite soccer. In parts, this has also been due to the lack of available data. Increasingly however, detailed game logs obtained through next-generation tracking technologies in addition to physiological training data collected through novel miniature sensor technologies have become available for research. This leads however to the opposite problem where the shear amount of data becomes an obstacle in itself as methodological guidelines as well as theoretical modelling of tactical decision making in team sports is lacking. The present paper discusses how big data and modern machine learning technologies may help to address these issues and aid in developing a theoretical model for tactical decision making in team sports. As experience from medical applications show, significant organizational obstacles regarding data governance and access to technologies must be overcome first. The present work discusses these issues with respect to tactical analyses in elite soccer and propose a technological stack which aims to introduce big data technologies into elite soccer research. The proposed approach could also serve as a guideline for other sports science domains as increasing data size is becoming a wide-spread phenomenon.

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Big data and tactical analysis in elite soccer: future challenges and opportunities for sports science

Tactical match performance depends on the quality of actions of individual players or teams in space and time during match-play in order to be successful. Technological innovations have led to new possibilities to capture accurate spatio-temporal information of all players and unravel the dynamics and complexity of soccer matches. The main aim of this article is to give an overview of the current state of development of the analysis of position data in soccer. Based on the same single set of position data of a high-level 11 versus 11 match (Bayern Munich against FC Barcelona) three different promising approaches from the perspective of dynamic systems and neural networks will be presented: Tactical performance analysis revealed inter-player coordination, inter-team and inter-line coordination before critical events, as well as team-team interaction and compactness coefficients. This could lead to a multi-disciplinary discussion on match analyses in sport science and new avenues for theoretical and practical implications in soccer.

Current Approaches to Tactical Performance Analyses in Soccer Using Position Data

There is a need for a collective variable that captures the dynamics of team sports like soccer at match level. The centroid positions and surface areas of two soccer teams potentially describe the coordinated flow of attacking and defending in small-sided soccer games at team level. The aim of the present study was to identify an overall game pattern by establishing whether the proposed variables were linearly related between teams over the course of the game. In addition, we tried to identify patterns in the build-up of goals. A positive linear relation and a negative linear relation were hypothesized for the centroid positions and surface areas respectively. Finally, we hypothesized that deviations from these patterns are present in the build-up of goals. Ten young male elite soccer players (mean age 17.3, s=0.7) played three small-sided soccer games (4-a-side) of 8 minutes as part of their regular training routine. An innovative player tracking system, local position measurement (LPM), was us...

Oscillations of centroid position and surface area of soccer teams in small-sided games

This study explores whether positioning systems are a viable alternative to timing gates when it comes to measuring sprint times in ice hockey. We compared the results of a single-beam timing gate (Brower Timing) with the results of the Iceberg optical positioning system (Optical) and two radio-based positioning systems provided by InMotio (Radio 1) and Kinexon (Radio 2). The testing protocol consisted of two 40 m linear sprints, where we measured sprint times for a 11 m subsection (Linear Sprint 11), and a shuttle run (Shuttle Total), including five 14 m sprints. The exercises were performed by six top-level U19 field players in regular ice hockey equipment on ice. We quantified the difference between measured sprint times e.g., by Mean Absolute Error (MAE) (s) and Intra Class Correlation (ICC). The usefulness of positioning systems was evaluated by using a Coefficient of Usefulness (CU), which was defined as the quotient of the Smallest Worthwhile Change (SWC) divided by the Typical Error (both in s). Results showed that radio-based systems had a higher accuracy compared to the optical system. This concerned Linear Sprint 11 (MAEOptical = 0.16, MAERadio1 = 0.01, MAERadio2 = 0.01, ICCOptical = 0.38, ICCRadio1 = 0.98, ICCRadio2 = 0.99) as well as Shuttle Total (MAEOptical = 0.07, MAERadio1 = 0.02, MAERadio2 = 0.02, ICCOptical = 0.99; ICCRadio1 = 1.0, ICCRadio2 = 1.0). In Shuttle Total, all systems were able to measure a SWC of 0.10 s with a probability of >99% in a single trial (CUOptical = 4.6, CURadio1 = 6.5, CURadio2 = 5.1). In Linear Sprint 11 an SWC of 0.01 s might have been masked or erroneously detected where there were none due to measurement noise (CUOptical = 0.6, CURadio1 = 1.0, CURadio2 = 1.0). Similar results were found for the turning subsection of the shuttle run (CUOptical = 0.6, CURadio1 = 0.5, CURadio2 = 0.5). All systems were able to detect an SWC higher than 0.04 s with a probability of at least 75%. We conclude that the tested positioning systems may in fact offer a workable alternative to timing gates for measuring sprints times in ice hockey over long distances like shuttle runs. Limitations occur when testing changes/differences in performance over very short distances like an 11 m sprint, or when intermediate times are taken immediately after considerable changes of direction or speed.

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Can Positioning Systems Replace Timing Gates for Measuring Sprint Time in Ice Hockey

Computer science has become an important partner for sport science. Although many cases for the successful application of computers in sport exist, only a few meta-theoretical mediations on this research field can be found. To fill this gap, this paper looks at the genesis of sport informatics in Germany, discusses the interdisciplinary relation between computer science and sport science and forecasts its development up to the year 2020. Using existing models of interdisciplinarity the paper classifies research activities into four types of cooperation and emphasizes the importance of “genuine” interdisciplinary research. This discussion leads to a compact definition of sport informatics and to a graphical model, which illustrates its subject matter and the structural relations between sport science, computer science and their fields of application. The future section identifies increased computing power and network capacity, networks concepts such as pervasive or cloud computing, small one way electronics, flexible displays and positioning technologies being the most relevant technological improvements for sport. These technologies have a potential impact e.g. on the measurement and reporting of physiological and positional data, on computerized performance analysis, sport clothing and the quality of computer simulations in the fields of sports engineering, motor behavior and physiological adaptation.

/pdf/sport-informatics-historical-roots-interdisciplinarity-and-2bul048x8x.pdf

Sport Informatics - Historical Roots, Interdisciplinarity and Future Developments.

The aim of this study was the validation of player and ball position measurements of Kinexon's local positioning system (LPS) in handball and football. Eight athletes conducted a sport-specific course (SSC) and small sided football games (SSG), simultaneously tracked by the LPS and an infrared camera-based motion capture system as reference system. Furthermore, football shots and handball throws were performed to evaluate ball tracking. The position root mean square error (RMSE) for player tracking was 9 cm for SSCs, the instantaneous peak speed showed a percentage deviation from the reference system of 0.7-1.7% for different exercises. The RMSE for SSGs was 8 cm. Covered distance was overestimated by 0.6% in SSCs and 1.0% in SSGs. The 2D RMSE of ball tracking was 15 cm in SSGs, 3D position errors of shot and throw impact locations were 17 cm and 21 cm. The methodology for the validation of a system's accuracy in sports tracking requires extensive attention, especially in settings covering both, player and ball measurements. Most tracking errors for player tracking were smaller or in line with errors found for comparable systems in the literature. Ball tracking showed a larger error than player tracking. Here, the influence of the positioning of the sensor must be further reviewed. In total, the accuracy of Kinexon's LPS has proven to represent the current state of the art for player and ball position detection in team sports.

https://www.mdpi.com/1424-8220/21/4/1465/pdf

Validation of Player and Ball Tracking with a Local Positioning System

Team sports are complex dynamic systems based on the frequent interaction of various players. Recently, social network analysis has been introduced to the study of sports dynamics in order to quantify the involvement of individual players in the interplay and to characterize the organizational processes used by teams. Nonetheless, only a limited set of team sports has been assessed to date, and the focus of most studies has been on the application of small sets of network metrics to a single sport. Our study aims at comparing the network patterns of different team sports in order to contribute to the understanding of their underlying nature. It considers three invasion games, namely professional matches from basketball, football and handball. By applying relevant centrality measures and minimum spanning trees a first comparison between the nature of interplay in various team sports is offered as well as a deeper understanding of the role of different tactical positions in each sport. The point guard in basketball, defensive midfielder in football and center in handball are identified as the most central tactical positions. Direct interplay is most balanced in football followed by basketball and handball. A visualization of the basic structure of interplay for each sport is achieved through minimum spanning trees.

/pdf/characterizing-different-team-sports-using-network-analysis-3ru80eqwu2.pdf

Martin Lames

Papers

Can Positioning Systems Replace Timing Gates for Measuring Sprint Time in Ice Hockey

Sport Informatics - Historical Roots, Interdisciplinarity and Future Developments.

Validation of Player and Ball Tracking with a Local Positioning System

Characterizing different team sports using network analysis

Modellbildung in der Sportwissenschaft