Abstract: A vision system (10) for a motor vehicle includes a stereo imaging apparatus (11) adapted to capture images from a surrounding of the motor vehicle, a disparity calculation block (17) adapted to calculate a stereo disparity of left/right images captured by the stereo imaging apparatus (11), and a processing device (14) adapted to perform image processing of images captured by the imaging apparatus (11). The vision system is adapted to perform time sharing of the disparity calculation block (17) between the stereo disparity calculation and calculation of a one-dimensional optical flow of captured images in a horizontal direction only.

Abstract: A vision system (10) for a motor vehicle with a stereo imaging apparatus (11) with imaging devices (12) adapted to capture images from a surrounding of the motor vehicle, and a processing device (14) adapted to process images captured by the imaging devices (12) and to detect objects, and track detected objects over several time frames, in the captured images. The processing device (14) is adapted to obtain an estimated value for the intrinsic yaw error of the imaging devices (12) by solving a set of equations, belonging to one particular detected object (30), using a non-linear equation solver method, where each equation corresponds to one time frame and relates a frame time, a disparity value of the particular detected object, an intrinsic yaw error and a kinematic variable of the vehicle.

Abstract: A vision system for detecting free space in front of a motor vehicle includes a mono imaging apparatus (11) adapted to capture images (30) from the surrounding of a motor vehicle, and an electronic processing device (14) adapted to perform image processing of images (30) captured by the mono imaging apparatus (11) in order to detect objects in the surrounding of a motor vehicle. The electronic processing device (14) is adapted to calculate a horizontal component of the optical flow (31), and to determine transitions (33, 35) between regions of essentially constant horizontal optical flow and regions of essentially non-constant horizontal optical flow.

Abstract: A vision system (10) for a motor vehicle with a stereo imaging apparatus (11) with imaging devices (12) adapted to capture images from a surrounding of the motor vehicle, and a processing device (14) adapted to process images captured by the imaging devices (12) and to detect objects, and track detected objects over several time frames, in the captured images. The processing device (14) is adapted to obtain an estimated value for the intrinsic yaw error of the imaging devices (12) by solving a set of equations, belonging to one particular detected object (30), using a non-linear equation solver method, where each equation corresponds to one time frame and relates a frame time, a disparity value of the particular detected object, an intrinsic yaw error and a kinematic variable of the vehicle.

Abstract: A vision system (10) for a motor vehicle includes a stereo imaging apparatus (11) adapted to capture images from a surrounding of the motor vehicle, a disparity calculation block (17) adapted to calculate a stereo disparity of left/right images captured by the stereo imaging apparatus (11), and a processing device (14) adapted to perform image processing of images captured by the imaging apparatus (11). The vision system is adapted to perform time sharing of the disparity calculation block (17) between the stereo disparity calculation and calculation of a one-dimensional optical flow of captured images in a horizontal direction only.

Abstract: A vision system for detecting free space in front of a motor vehicle includes a mono imaging apparatus (11) adapted to capture images (30) from the surrounding of a motor vehicle, and an electronic processing device (14) adapted to perform image processing of images (30) captured by the mono imaging apparatus (11) in order to detect objects in the surrounding of a motor vehicle. The electronic processing device (14) is adapted to calculate a horizontal component of the optical flow (31), and to determine transitions (33, 35) between regions of essentially constant horizontal optical flow and regions of essentially non-constant horizontal optical flow.