Work

FOOTBALL PLAYER TRACKING FROM MULTIPLE VIEWS - Using a Novel Background Segmentation Algorithm and Multiple Hypothesis Tracking

Year: 2007

Type: conference-paper

Abstract: In this work, our aim is to develop an automated system which provides data useful for football game analysis. Information from multiple cameras is used to perform player detection, classification and tracking. A background segmentation approach, which operates with the invariant Gaussian colour model and uses temporal information, is used to achieve more accurate results. Information derived and matched from all cameras is then used to perform tracking, using an advanced Multiple Hypothesis Tracking algorithm.

Source: International Conference on Computer Vision Theory and Applications

DOI: 10.5220/0002051205230526

Authors: A. Koutsia, N. Grammalidis, K. Dimitropoulos, M. Karaman, L. Goldmann

Language: English

Topic: Video Surveillance and Tracking Methods

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

OpenAlex ID: W263145574

FWCI:

Cites: 11

Cited by: 1

Related to: 10