M-Svm Classifiers For Events Detection In Video Using Auto-Associative Neural Network Models

Our main goal in this study was to develop and validate an intelligent system for video event detection based on spatiotemporel features combining an auto-associative neural network models for feature reduction. Proposed system aims at high accuracy of event classification mainly with the use of an M-SVM model. The core of the system is the auto-associative neural network models which can reduce the size of feature vectors. The proposed model performance, evaluated an important data basis including seven events, was compared to other models found in the literature; it outperforms the other methods in terms of precision.