A vehicle tracking system using PCA and adaptive resonance theory
C. Sotthithaworn, Prayoth Kumsawat, K. Attakitmongkol, Arthit Srikaew · 2007
Abstract:- This work presents vehicle detecting and tracking system from a sequence of images. The system utilizes ART (Adaptive Resonance Theory) network for segmentation and recognition. By applying log-Gabor filters to the initially detected vehicle, the resulting filtered vehicles are fed into the network which can automatically recognize salient features of vehicles by analyzing theirs principal components. This unsupervised network allows the system to efficiently perform tracking in dynamic environments where shapes and sizes of vehicles are changing all the time. The proposed system can also track multiple vehicles simultaneously. Results and discussions are described.