Research on Video Image Vehicle Tracking Algorithm Based on Random Forest Method
Li Yanxue, Fang Lv, Ming Xiaojing · Journal of Physics Conference Series · 2018
On the basis of apparent tracking theory of discriminant model, we put forward a vehicle video tracking improvement algorithm based on the random forest classifier to seek a better classifier confidence figure, so that we can improve the tracking accuracy. After getting the degree of confidence of the rectangular image block predicted by the classifier, the pixels and the distance information between rectangular image blocks have different impacts on the degree of confidence. According to this feature, using the pixel confidence estimation method based on weighted distance information to improve the confidence estimation accuracy of pixel, and then improve the tracking accuracy.