A neural network approach for counting pedestrians from video sequence images
Norifumi Ikeda, Ayumu Saitoh, Teijiro Isokawa, Naotake Kamiura, Nobuyuki Metsui · 2008
A system for counting pedestrians in sequence images obtained from single video camera is proposed in this paper. This system has the capabilities of simultaneously detecting and tracking several groups of pedestrians. Groups can be extracted by using the background subtraction method, and a layered neural network with BP learning algorithm is applied to estimate the number of pedestrians in each of the groups. The practical applicability of the proposed system is demonstrated, applying it to the sequence images of a real scenery.