Authors:
P. Spagnolo
;
P. L. Mazzeo
;
M. Leo
and
T. D’Orazio
Affiliation:
Institute of Intelligent Systems for Automation – National Research Council, Italy
Keyword(s):
Sport scene analysis, Motion Detection, Background Subtraction, Data Clustering.
Related
Ontology
Subjects/Areas/Topics:
Biometrics and Pattern Recognition
;
Image and Video Processing, Compression and Segmentation
;
Multimedia
;
Multimedia Signal Processing
;
Telecommunications
Abstract:
In this work we consider the problem of soccer player detection and classification. The approach we propose starts from the monocular images acquired by a still camera. Firstly, players are detected by means of background subtraction. An algorithm based on pixels energy content has been implemented in order to detect moving objects. The use of energy information, combined with a temporal sliding window procedure, allows to be substantially independent from motion hypothesis. Then players are assigned to the correspondent team by means of an unsupervised clustering algorithm that works on colour histograms in RGB space. It is composed by two distinct modules: firstly, a modified version of the BSAS clustering algorithm builds the clusters for each class of objects. Then, at runtime, each player is classified by evaluating its distance, in the features space, from the classes previously detected. Algorithms have been tested on different real soccer match of the Italian Serie A.