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We present a novel approach for vehicle detection in urban surveillance videos, capable of handling unstructured and crowded environments with large occlusions, different vehicle shapes, and environmental conditions such as lighting changes, rain, shadows, and reflections. This is achieved with virtually no manual labeling efforts. The system runs quite efficiently at an average of 66Hz on a conventional...
Focusing on the problem that the detection accuracy of traffic detection system is sensitive to the changes of complex environments, this paper presents an improved method of vehicle detection. It builds and updates the background adaptively. Additionally, to improve the computation efficiency of shadow elimination, a fast algorithm of neighbor mean based on HSV model is proposed. As the occlusion...
In this work, a traffic surveillance system, which contains background subtraction, occlusion handling and tracking steps, is designed in order to extract traffic parameters from low resolution video sequences. In every step, utilized algorithms are improved and more accurate results than existing approaches are obtained. Additionally, a new automatic Region of Interest detection approach is proposed...
Camera calibration, as a fundamental issue in computer vision, is indispensable in many visual surveillance applications. Firstly, calibrated camera can help to deal with perspective distortion of object appearance on image plane. Secondly, calibrated camera makes it possible to recover metrics from images which are robust to scene or view angle changes. In addition, with calibrated cameras, we can...
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