Adaptive rule-based recognition of events in video sequences

Author

Tzouvaras, V. ; Tsechpenakis, G. ; Stamou, G. ; Kollias, Stefanos

Author_Institution

Multimedia Lab., Nat. Tech. Univ. of Athens, Greece

Volume

2

fYear

2003

fDate

14-17 Sept. 2003

Abstract

Knowledge-based fuzzy inference and neural learning are used in this paper in order to model the event recognition task in semantic video analysis. The advantage of their use is the symbolic nature of the representation of the knowledge concerning the events to be recognized. Moreover, this knowledge can be adapted with the aid of data taken from video sequences. The proposed system has been tested in soccer video sequences for detecting some complex predetermined (and represented in the form of rules) events.

Keywords

content-based retrieval; fuzzy logic; fuzzy neural nets; image recognition; image retrieval; image sequences; inference mechanisms; knowledge representation; learning (artificial intelligence); video signal processing; adaptive rule-based event recognition; complex predetermined event detection; fuzzy logic; knowledge representation; knowledge-based fuzzy inference; machine learning; neural learning; neurofuzzy architecture; semantic video analysis; soccer video sequence; Artificial neural networks; Character recognition; Data mining; Event detection; Fuzzy sets; Fuzzy systems; Hybrid intelligent systems; Object detection; Robustness; Video sequences;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 2003. ICIP 2003. Proceedings. 2003 International Conference on

ISSN

1522-4880

Print_ISBN

0-7803-7750-8

Type

conf

DOI

10.1109/ICIP.2003.1246753

Filename

1246753