Title :
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
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;
Conference_Titel :
Image Processing, 2003. ICIP 2003. Proceedings. 2003 International Conference on
Print_ISBN :
0-7803-7750-8
DOI :
10.1109/ICIP.2003.1246753
