Soccer line mark segmentation and classification with stochastic watershed transform

Augmented reality applications are beginning to change the way sports are broadcast, providing richer experiences and valuable insights to fans. The first step of augmented reality systems is camera calibration, possibly based on detecting the line markings of the playing field. Most existing proposals for line detection rely on edge detection and Hough transform, but radial distortion and extraneous edges cause inaccurate or spurious detections of line markings. We propose a novel strategy to automatically and accurately segment and classify line markings. First, line points are segmented thanks to a stochastic watershed transform that is robust to radial distortions, since it makes no assumptions about line straightness, and is unaffected by the presence of players or the ball. The line points are then linked to primitive structures (straight lines and ellipses) thanks to a very efficient procedure that makes no assumptions about the number of primitives that appear in each image. The strategy has been tested on a new and public database composed by 60 annotated images from matches in five stadiums. The results obtained have proven that the proposed strategy is more robust and accurate than existing approaches, achieving successful line mark detection even in challenging conditions.Comment: 18 pages, 11 figure

Audio-based event detection for sports video

In this paper, we present an audio-based event detection approach shown to be effective when applied to the Sports broadcast data. The main benefit of this approach is the ability to recognise patterns that indicate high levels of crowd response which can be correlated to key events. By applying Hidden Markov Model-based classifiers, where the predefined content classes are parameterised using Mel-Frequency Cepstral Coefficients, we were able to eliminate the need for defining a heuristic set of rules to determine event detection, thus avoiding a two-class approach shown not to be suitable for this problem. Experimentation indicated that this is an effective method for classifying crowd response in Soccer matches, thus providing a basis for automatic indexing and summarisation

TRAJECTORY STUDY OF BALLROOM DANCE USING MILLISECOND VIDEO ANALYSIS

A short video (3 s) of the natural turn movements of ballroom dance was analyzed using two-dimensional trajectory analysis to demonstrate precise verification of the movement. The movements were recorded with a high-speed camera (240 Hz), and the trajectory was plotted at 4 ms intervals. The precise trajectories of test subjects’ movements were successfully monitored by making them wear LED lights on their necks, elbows, waists, and knees. The differences between the trajectories of an experienced subject’s movement and that of a beginner were clearly indicated, even when those movements occurred over short durations. The differences were also evident from a velocity analysis of the same video data. Our low-cost method can be applied to ballroom dance education, even in a personal dance studio

Analysis of Player Motion in Sport Matches

The system for analysis of player motion during sport matches, developed at University of Ljubljana will be presented. The system allows for non-intrusive measurement of positions of all players in indoor sports through whole match using only inexpensive video equipment - cameras mounted on the ceiling of the sports hall. Tracking process (obtaining trajectories from videos) is automatic and only supervised by operator, to initialize player positions at the beginning and correct the mistakes during the tracking. The software provides means for user friendly calibration of video data - using court markings of each supported sport (e.g. european handball, basketball, squash, tennis...) as reference coordinates. Manual annotations can be added, to complement the quantitative data. Software keeps synchronization between annotations and trajectory data and provides means to use custom annotation dictionaries. Due to calibration, the results are provided in court coordinates (meters, centimeters) and can be exported (synchronized with annotations in same file) for further analysis with any application (e.g. excel, SPSS). Software itself supports several kinds of graphical data presentations. If time allows, the software itself will be demonstrated with examples from different sports