Toward a Visual Tracking System with On-Line Visual Learning Capability.
Takayuki Nakamura, Tsukasa Ogasawara · Journal of the Robotics Society of Japan · 2000
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 architecture 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 architecture for color segmentation on-line, we transform the color signal that the framegrabber used yields to a particular color space called Yrθ space. To show validity of our method, we present some results of experiments using sequences of real images.