Reconfigurable Vision Processing for Player Tracking in Indoor Sports

Ibraheem OW. Reconfigurable Vision Processing for Player Tracking in Indoor Sports. Bielefeld: Universität Bielefeld; 2018.Over the past decade, there has been an increasing growth of using vision-based systems for tracking players in sports. The tracking results are used to evaluate and enhance the performance of the players as well as to provide detailed information (e.g., on the players and team performance) to viewers. Player tracking using vision systems is a very challenging task due to the nature of sports games, which includes severe and frequent interactions (e.g., occlusions) between the players. Additionally, these vision systems have high computational demands since they require processing of a huge amount of video data based on the utilization of multiple cameras with high resolution and high frame rate. As a result, most of the existing systems based on general-purpose computers are not able to perform online real-time player tracking, but track the players offline using pre-recorded video files, limiting, e.g., direct feedback on the player performance during the game. In this thesis, a reconfigurable vision-based system for automatically tracking the players in indoor sports is presented. The proposed system targets player tracking for basketball and handball games. It processes the incoming video streams from GigE Vision cameras, achieving online real-time player tracking. The teams are identified and the players are detected based on the colors of their jerseys, using background subtraction, color thresholding, and graph clustering techniques. Moreover, the trackingby-detection approach is used to realize player tracking. FPGA technology is used to handle the compute-intensive vision processing tasks by implementing the video acquisition, video preprocessing, player segmentation, and team identification & player detection in hardware, while the less compute-intensive player tracking is performed on the CPU of a host-PC. Player detection and tracking are evaluated using basketball and handball datasets. The results of this work show that the maximum achieved frame rate for the FPGA implementation is 96.7 fps using a Xilinx Virtex-4 FPGA and 136.4 fps using a Virtex-7 device. The player tracking requires an average processing time of 2.53 ms per frame in a host-PC equipped with a 2.93 GHz Intel i7-870 CPU. As a result, the proposed reconfigurable system supports a maximum frame rate of 77.6 fps using two GigE Vision cameras with a resolution of 1392x1040 pixels each. Using the FPGA implementation, a speedup by a factor of 15.5 is achieved compared to an OpenCV-based software implementation in a host-PC. Additionally, the results show a high accuracy for player tracking. In particular, the achieved average precision and recall for player detection are up to 84.02% and 96.6%, respectively. For player tracking, the achieved average precision and recall are up to 94.85% and 94.72%, respectively. Furthermore, the proposed reconfigurable system achieves a 2.4 times higher performance per Watt than a software-based implementation (without FPGA support) for player tracking in a host-PC.Acknowledgments: I (Omar W. Ibraheem) would like to thank the German Academic Exchange Service (DAAD), the Congnitronics and Sensor Systems research group, and the Cluster of Excellence Cognitive Interaction Technology ‘CITEC’ (EXC 277) (Bielefeld University) not only for funding the work in this thesis, but also for all the help and support they gave to successfully finish my thesis

バレーボールのアタックトレーニングを拡張するシステムデザインに関する研究

筑波大学 (University of Tsukuba)201

A Novel Multi-View Table Tennis Umpiring Framework

This research investigates the development of a low-cost multi-view umpiring framework, as an alternative to the current expensive systems that are almost exclusively restricted to elite professional sports. Table tennis has been selected as the testbed because, while automating the process is challenging, it has many different complex match elements including the service, return and rallies, which are governed by a strict set of regulations. The focus is mainly on the rally element rather than the whole match. Ball detection and tracking in video frames are undertaken to determine reliably the ball position relative to key reference objects like the table surface and net, and the ball’s flight path is used to determine the rally’s status. While a low-cost option has benefits, it is technically challenging due to the limited number of cameras and generally low video resolution used. This thesis presents a portable multi-view umpiring framework that identifies each state change in a rally. It makes three significant contributions to knowledge: i) a reliable ball detection strategy that accurately detects the location of the ball in low-resolution sequences; ii) a novel framework for ball tracking using a multi-view system, and iii) a new state-machine based evaluation system for analysing table tennis rallies. In a series of ten different test scenarios, the system achieved an average of 94% system detection rate and 100% accurate decisions. A test sequence of duration 1 s can be processed in 8 s, leading to a delay of only 7 s, which is considered acceptable for practical purposes. This solution has the potential to reform the way matches are umpired, providing objectivity in resolving disputed decisions. It affords an economic technology for amateur players, while the multi-view facility is extendible to other relevant ball-based sports. Finally, the ball flight path analysis mechanism can be a valuable training tool for skills development

A Systematic Review and Meta-Analysis of the Incidence of Injury in Professional Female Soccer

The epidemiology of injury in male professional football is well documented and has been used as a basis to monitor injury trends and implement injury prevention strategies. There are no systematic reviews that have investigated injury incidence in women’s professional football. Therefore, the extent of injury burden in women’s professional football remains unknown. PURPOSE: The primary aim of this study was to calculate an overall incidence rate of injury in senior female professional soccer. The secondary aims were to provide an incidence rate for training and match play. METHODS: PubMed, Discover, EBSCO, Embase and ScienceDirect electronic databases were searched from inception to September 2018. Two reviewers independently assessed study quality using the Strengthening the Reporting of Observational Studies in Epidemiology statement using a 22-item STROBE checklist. Seven prospective studies (n=1137 professional players) were combined in a pooled analysis of injury incidence using a mixed effects model. Heterogeneity was evaluated using the Cochrane Q statistic and I2. RESULTS: The epidemiological incidence proportion over one season was 0.62 (95% CI 0.59 - 0.64). Mean total incidence of injury was 3.15 (95% CI 1.54 - 4.75) injuries per 1000 hours. The mean incidence of injury during match play was 10.72 (95% CI 9.11 - 12.33) and during training was 2.21 (95% CI 0.96 - 3.45). Data analysis found a significant level of heterogeneity (total Incidence, X2 = 16.57 P < 0.05; I2 = 63.8%) and during subsequent sub group analyses in those studies reviewed (match incidence, X2 = 76.4 (d.f. = 7), P <0.05; I2 = 90.8%, training incidence, X2 = 16.97 (d.f. = 7), P < 0.05; I2 = 58.8%). Appraisal of the study methodologies revealed inconsistency in the use of injury terminology, data collection procedures and calculation of exposure by researchers. Such inconsistencies likely contribute to the large variance in the incidence and prevalence of injury reported. CONCLUSIONS: The estimated risk of sustaining at least one injury over one football season is 62%. Continued reporting of heterogeneous results in population samples limits meaningful comparison of studies. Standardising the criteria used to attribute injury and activity coupled with more accurate methods of calculating exposure will overcome such limitations