Recent years, many vision-based vehicle detection methods have been proposed. But just a few of them paid attention to vehicle type classification in a real-time video, which is an important part in intelligent traffic system. The Haar features and Histograms of Oriented Gradients (HOG) features have been proposed as useful features for vehicle detection respectively. In this paper, we propose a method based on combined the Haar features and HOG features to detect vehicles in videos and classify them into two types. The experiment results show that this method can classify and detect the vehicles in multi-orientations with good classification results, and it verified the effectiveness of the propose method with real vehicle samples.
Algorithm for vision-based vehicle detection and classification
2013-12-01
948533 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Vision-based vehicle classification
IEEE | 2000
|Vision-Based Vehicle Classification
British Library Conference Proceedings | 2000
|A monocular-vision rear vehicle detection algorithm
IEEE | 2007
|Unstructured Road Region Detection and Road Classification Algorithm Based on Machine Vision
British Library Conference Proceedings | 2023
|