Jamil Draréni

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In this paper we present two methods to geometrically calibrate a video projector using a markerless planar surface. The first method assumes a partial knowledge on the camera parameters, whereas the second method consists in an auto-calibration method with no assumption on the parameters of the camera. Instead, the auto-calibration is performed by(More)
Linear or 1D cameras are used in several areas such as industrial inspection and satellite imagery. Since 1D cameras consist of a linear sensor, a motion (usually perpendicular to the sensor orientation) is performed in order to acquire a full image. In this paper, we present a novel linear method to estimate the intrinsic and extrinsic parameters of a 1D(More)
In this paper we address the problem of geometric calibration of video projectors. Like in most previous methods we also use a camera that observes the projection on a planar surface. Contrary to those previous methods, we neither require the camera to be calibrated nor the presence of a calibration grid or other metric information about the scene. We thus(More)
The topic of this thesis revolves around three fundamental problems in computer vision; namely, video tracking, camera calibration and shape recovery. The proposed methods are solely based on photometric and geometric constraints found in the images. Video tracking, usually performed on a video sequence, consists in tracking a region of interest, selected(More)
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