Soccer ball detection by comparing different feature extraction methodologies

  • Authors:

  • Pier Luigi Mazzeo;Marco Leo;Paolo Spagnolo;Massimiliano Nitti

  • Affiliations:

  • Istituto di Studi sui Sistemi Intelligenti per l'Automazione, CNR, Bari, Italy;Istituto di Studi sui Sistemi Intelligenti per l'Automazione, CNR, Bari, Italy;Istituto di Studi sui Sistemi Intelligenti per l'Automazione, CNR, Bari, Italy;Istituto di Studi sui Sistemi Intelligenti per l'Automazione, CNR, Bari, Italy

  • Venue:
  • Advances in Artificial Intelligence
  • Year:
  • 2012

Quantified Score

Hi-index 0.00

Visualization

Abstract

This paper presents a comparison of different feature extraction methods for automatically recognizing soccer ball patterns through a probabilistic analysis. It contributes to investigate different well-known feature extraction approaches applied in a soccer environment, in order tomeasure robustness accuracy and detection performances. This work, evaluating differentmethodologies, permits to select the one which achieves best performances in terms of detection rate and CPU processing time. The effectiveness of the differentmethodologies is demonstrated by a huge number of experiments on real ball examples under challenging conditions.