Authors:
Filipe Trocado Ferreira
1
;
Jaime S. Cardoso
2
and
Hélder P. Oliveira
3
Affiliations:
1
Faculdade de Engenharia da Universidade do Porto, Portugal
;
2
Faculdade de Engenharia da Universidade do Porto and INESC TEC, Portugal
;
3
INESC TEC, Portugal
Keyword(s):
Sport Analysis, Quadcopter, Video Processing, Player Detection, Homography Estimation.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Classification
;
Computer Vision, Visualization and Computer Graphics
;
Image and Video Analysis
;
Image Understanding
;
Object Recognition
;
Pattern Recognition
;
Software Engineering
;
Theory and Methods
;
Video Analysis
Abstract:
Automatic vision systems are widely used in sports competition to analyze individual and collective performance
during the matches. However, the complex implementation based on multiple fixed cameras and the
human intervention on the process makes this kind of systems expensive and not suitable for the big majority
of the teams. In this paper we propose a low-cost, portable and flexible solution based on the use of Unmanned
Air Vehicles to capture images from indoor soccer games. Since these vehicles suffer from vibrations and disturbances,
the acquired video is very unstable, presenting a set of unusual problems in this type of applications.
We propose a complete video-processing framework, including video stabilization, camera calibration, player
detection, and team performance analysis. The results showed that camera calibration was able to correct
automatically image-to-world homography; the player detection precision and recall was around 75%; and the
high-level data interpretat
ion showed a strong similarity with ground-truth derived results.
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