国产欧美精品一区二区,中文字幕专区在线亚洲,国产精品美女网站在线观看,艾秋果冻传媒2021精品,在线免费一区二区,久久久久久青草大香综合精品,日韩美aaa特级毛片,欧美成人精品午夜免费影视

Do researches on the existing machine learning algorithms of vehicles detecting and analyze the disadvantages, which lie in using single feature or single ML algorithms, or not robust enough of illumination and other condition changes. For these problems, a vehicle detecting algorithm is presented based on fusion of LBP and HOG features and combining the Adaboost and SVM. Referencing cascade thought, the algorithm first extracts LBP features of training samples by AdaBoost and the classifier is used for initial classification. Classification results act as the inputs of next classifier. Then HOG features of training samples are extracted by SVM and the resulting classifier is applied to classify the above results. Experiments show that AdaBoost-SVM method accuracy rate and recall rate both are above 95% and the value FPPW of FPPI are about 5%. At the same time the proposed method is robust to lighting conditions because of the selected features. In the aspects of real-time, each frame processing time is 75ms which meets the real-time requirements.