Neural Networks
A practical approach to feature selection
ML92 Proceedings of the ninth international workshop on Machine learning
Seizure Detection by Recurrent Backpropagation Neural Network Analysis
ISUMA '03 Proceedings of the 4th International Symposium on Uncertainty Modelling and Analysis
An introduction to variable and feature selection
The Journal of Machine Learning Research
Computer Manual in MATLAB to Accompany Pattern Classification, Second Edition
Computer Manual in MATLAB to Accompany Pattern Classification, Second Edition
A neural-based crowd estimation by hybrid global learning algorithm
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Estimation of number of people in crowded scenes using perspective transformation
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
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The paper is devoted to the problem of estimating the number of people visible in a camera. It uses as features the ratio of foreground pixels in each cell of a rectangular grid. Using the above features and data mining techniques allowed reaching accuracy up to 85% for exact match and up to 95% for plus-minus one estimates for an indoor surveillance environment. Applying median filters to the sequence of estimation results increased the accuracy up to 91% for exact match. The architecture of a real-time people counting estimator is suggested. The results of analysis of experimental data are provided and discussed.