Background: Pedestrians are the major road users in transportation system. They are more
vulnerable than other road users when traffic accidents occurr, which has attracted much concerns from
researchers around the world by developing corresponding countermeasures.
Pedestrians are not easy to be tracked accurately because of the changes in illumination conditions and
the occlusion of human body using traditional tracking algorithms.
Method: To improve the effectiveness of pedestrian tracking, particle filter (PF) is utilized to track the
pedestrian, which is detected using the histograms of oriented gradient (HOG) features. Then scale
invariant feature transform (SIFT) features are employed to represent the region of interest for sequence
Result: The representative vector utilized to describe the pedestrian is renewed after comparing the
object model and the characteristic variables during the tracking process. This method takes advantage
of color histogram and adopts PF to predict the position of the pedestrian.
Conclusion: Experiments were conducted to compare the proposed method with traditional PF tracking
method. Results verify the accuracy and efficiency of the proposed method.