Abstract. Semi-automatic parking system is a driver convenience system automating steering control required during parking operation. This paper proposes novel monocular-vision based target parking-slot recognition by recognizing parking-slot markings when driver designates a seed-point inside the target parking-slot with touch screen. Proposed method compensates the distortion of fisheye lens and constructs a bird's eye view image using homography. Because adjacent vehicles are projected along the outward direction from camera in the bird's eye view image, if marking line-segment distinguishing parking-slots from roadway and front-ends of marking linesegments dividing parking-slots are observed, proposed method successfully recognizes the target parking-slot marking. Directional intensity gradient, utilizing the width of marking line-segment and the direction of seed-point with respect to camera position as a prior knowledge, can detect marking linesegments irrespective of noise and illumination variation. Making efficient use of the structure of parking-slot markings in the bird's eye view image, proposed method simply recognizes the target parking-slot marking. It is validated by experiments that proposed method can successfully recognize target parkingslot under various situations and illumination conditions.
Abstract-This paper proposes a novel light stripe projection based free parking space recognition method in order to overcome the common drawbacks of existing vision based target parking position designation methods in dark indoor parking site. 3D information of parking site is recognized by light stripe projection method. By analyzing the 3D information, system can recognize discontinuous points, pivot, and opposite-site reference point. Experiments show that the proposed method can successfully designate target position in spite of dark illumination condition and the black reflective surface of vehicle. Furthermore, because the proposed method can be implemented just by adding a low-cost light plane projector, it is economically practical solution.
Abstract. This paper proposes a sensor fusion based obstacle detection/classification system for active pedestrian protection system. At the frontend of vehicle, one laser scanner and one camera is installed. Clustering and tracking of range data from laser scanner generate obstacle candidates. Vision system classifies the candidates into three categories: pedestrian, vehicle, and other. Gabor filter bank extracts the feature vector of candidate image. The obstacle classification is implemented by combining two classifiers with the same architecture: support vector machine for pedestrian and vehicle. Obstacle detection system recognizing the class can actively protect pedestrian while reducing false positive rate.
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