Mean Shift: A Robust Approach Toward Feature Space Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Detection in Color Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Numerical Recipes in C: The Art of Scientific Computing
Numerical Recipes in C: The Art of Scientific Computing
Computer vision for computer games
FG '96 Proceedings of the 2nd International Conference on Automatic Face and Gesture Recognition (FG '96)
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
IEEE Transactions on Pattern Analysis and Machine Intelligence
Skin Segmentation Using Color Pixel Classification: Analysis and Comparison
IEEE Transactions on Pattern Analysis and Machine Intelligence
Circular road signs recognition with soft classifiers
Integrated Computer-Aided Engineering - Artificial Neural Networks
Committee machine for road-signs classification
ICAISC'06 Proceedings of the 8th international conference on Artificial Intelligence and Soft Computing
Building Road-Sign Classifiers Using a Trainable Similarity Measure
IEEE Transactions on Intelligent Transportation Systems
Road-Sign Detection and Recognition Based on Support Vector Machines
IEEE Transactions on Intelligent Transportation Systems
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Tracking of multiple objects belongs to one of the fundamental tasks of computer vision. In this paper an improvement to the continuously adaptive mean shift tracking method is proposed. It consists in substitution of the probabilistic density function for the especially formed membership function. This makes possible design of tracking systems in terms of fuzzy logic. Additionally, a special data structure was developed to allow tracking of multiple objects at a time. It stores information on image regions which are active for tracking. By this it provides initial conditions for tracking in subsequent frames which also speeds up computations. The method was used and verified in an application of the road signs tracking in real time of 30 frames/s.