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This paper proposes a new vehicle color classification scheme to identify vehicles with their colors. To detect vehicles from roads, the paper proposes a novel symmetrical descriptor to determine the ROI of each vehicle without using any motion features. This scheme provides two advantages; there is no need of background subtraction and it is extremely efficient for real-time applications. After detection,...
This paper presents a monocular algorithm for front and rear vehicle detection, developed as part of the FP7 V-Charge project's perception system. The system is made of an AdaBoost classifier with Haar Features Decision Stump. It processes several virtual perspective images, obtained by un-warping 4 monocular fish-eye cameras mounted all-around an autonomous electric car. The target scenario is the...
This paper presents a video-based intelligent multidrive vehicle retrograde detection algorithm. Through the vehicle detection and tracking to determine the traffic flow direction on the road, compare the movement direction of vehicles and the traffic flow direction on the road to realize intelligent retrograde detection of multi-drive vehicles. Experiments show that the method is simple and effective...
We propose a method of real-time moving vehicle detection using infrared thermal images. It can detect moving vehicles robustly even for bad weather compared with conventional vehicle detection methods using visible light cameras. It can also measure the size of each vehicle around the clock. The algorithm we propose for this detection is designed for a high-speed processing without complicated calculations...
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