Online visual learning method for color image segmentation and object tracking

In order to keep visual tracking systems with color segmentation technique running in real environment, it should be developed on-line learning method to update models for adapting them to dynamic changes of surroundings. To deal with this problem, we propose an on-line visual learning method for color image segmentation and object tracking in dynamic environment. Our method utilizes fuzzy ART model which is a kind of neural network for competitive learning. The mechanism of this neural network is suitable for on-line learning and different from that of backpropagation type neural network. In order to use fuzzy ART model for color segmentation on-line, we transform the color signal that the framegrabber used yields to a particular color space called Y rθ space. To show validity of our method, we present some results of experiments using sequences of real images.