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Introduction
and overview
Application of computer vision technology to sports
domain presents a useful and challenging area of research for several
reasons. Most sports involve complex human motion and therefore
automated capturing, analyzing and quantifying the ability of the
athlete can offer significant help to the sports expert. We
concentrate our activities on tracking people in sports based on
computer vision. For many years the analysis of a sport event has been
based on "observation sheets'' filled-in during the match. In the
1980's, modern techniques of motion analysis were developed with the
help of video recordings. Motion acquisition and analysis were performed
manually, which was a time consuming and tedious task. In the past,
progress in introducing the computer vision technology to the team
sports domain was slow, mainly due to inadequate video and computational
facilities, as just a single match may require processing of tens of
thousands of complex images. Large amounts of data and high
computational load are by no means the only burden. The players strive
to move rapidly, change direction unpredictably and collide with one
another. They violate the smooth motion assumption, on which many
tracking algorithms are based. Players appear in the images as highly
non-rigid forms, especially due to the movements of their extremities.
In addition, cameras used to record the sport events have to cover large
area, either by following the players of interest, or by using
wide-angle lenses, which results in substantial image distortion and low
resolution. Many of the proposed approaches solved the motion
acquisition and analysis problem only partially and were therefore
unable to provide an adequate solution to the sports experts, i.e.
tracking every player and/or the ball in the whole
field, and in every instance of time.
This research project is a result of cooperation with
Faculty of Sports
at University of Ljubljana and is currently divided into the two parts, as
different approaches are needed in dealing with different types of sport.
Part 1: Team sports (handball, basketball) Part 2: Individual sports (squash) Handball video demonstration (input data, processing and results - 21 MB, 60 sec, MPEG)
Recent Work: Continuing the work on human motion analysis, we have developed between years 2003 and 2008 a new version of our computer-vision-based system for sports analysis. The system is composed of four major parts:(i) Camera calibration module, which is highly intuitive and easy to use tool for establishing a mapping between video data and ground plane of the court; (ii) Tracking module which allows semi-automatic tracking of a particular player or a group of players during a sports match; (iii) Presentation module is used for visualization of the obtained data; (iv) Video export module can be used to generate annotated virtual-camera videos of selected players; (v) Activity recognition module, which is used for data-mining and tactical analysis of sports matches. More on activity recognition can be found here. The tracking and video exporting engines are written in C++ with native interfaces to Java user-friendly interfaces, which makes the application fairly platform-independent (tested under Linux as well as under Windows). This application has been extensively used by sports experts from the Faculty of Sport University of Ljubljana, and by sport experts from Ruhr-Universität Bochum, for motion analysis of players during basketball, european handball, squash and tennis. The sports-oriented research so-far has been primarily focused on answering some fundamental questions about a particular sports discipline, such as the expected distances travelled per match, in which part of the court does a player spend most of time, how do player's velocity and acceleration vary during a match, what are the major differences in the dynamics of losers and winners, etc. A video describing the capabilities of the tracking system was accepted to 10th European Conference of Computer Vision (ECCV08) and can be found below; Online presentations: Tracking of players in the case of handball (methods) Error analysis, accuracy evaluation and testing.
Selected publications: |