Abstract: The present disclosure provides a vehicle positioning device for vehicle vision calibration, a positioning adjustment method, and a positioning adjustment system. The vehicle positioning device includes a base, a chassis, a translation mechanism and a rotation mechanism. A to-be-calibrated vehicle is placed onto the chassis, and the chassis is provided with a stopper. The translation mechanism is arranged between the chassis and the base, and configured to drive the chassis to move in an X-axis direction in a three-dimensional coordinate system relative to the base in accordance with a translation control instruction. The rotation mechanism is arranged between the chassis and the base, and configured to drive the chassis to rotate about a Z-axis in the three-dimensional coordinate system relative to the base in accordance with a rotation control instruction.

Abstract: An RGB-D fusion information-based obstacle target classification method includes: collecting an original image through a binocular camera within a target range, and acquiring a disparity map of the original image; collecting a color-calibrated RGB image through a reference camera of the binocular camera within the target range; acquiring an obstacle target through disparity clustering in accordance with the disparity map and the color-calibrated RGB image, and acquiring a target disparity map and a target RGB image of the obstacle target; calculating depth information about the obstacle target in accordance with the target disparity map; and acquiring a classification result of the obstacle target through RGB-D channel information fusion in accordance with the depth information and the target RGB image.

Abstract: A method and a system for calculating a focusing parameter of a binocular stereo camera, and an intelligent terminal are provided. The method includes: calculating a lower limit value and an upper limit value of a distance measurement range; acquiring a depth-of-field range in accordance with the lower limit value and the upper limit value; calculating a maximum value and a minimum value of an image distance gain corresponding to a real object distance within the depth-of-field range, and calculating an optimal image distance gain in accordance with the maximum value and the minimum value; acquiring an optimal object distance of a focused target in accordance with the optimal image distance gain; and calculating an optimal size of the focused target in accordance with the optimal object distance.

Abstract: A vehicle braking and warning method includes: acquiring first target information within a detection range of the binocular stereo camera, second target information within a detection range of a millimeter-wave radar, and current vehicle driving information; acquiring sensing result data about a target obstacle in accordance with the first target information and the second target information in conjunction with a predetermined weight; and outputting a braking instruction and/or a warning instruction in accordance with the sensing result data and the current vehicle driving information so as to enable a vehicle to adjust its driving state in accordance with the instructions.

Abstract: A method for automatically braking a commercial vehicle includes: providing a plurality of ultrasonic radars on a front vehicle body of a target commercial vehicle, the ultrasonic radars being configured to detect a region before the target commercial vehicle in a gapless manner, an active speed range being set for each ultrasonic radar; acquiring a current speed of the target commercial vehicle in real time and calculating a safe distance for each ultrasonic radar in accordance with the current speed; and detecting whether there is an obstacle within the safe distance in real time, and when there is the obstacle within the safe distance, transmitting a decelerating or braking instruction to an execution system of the target commercial vehicle.

Abstract: The present disclosure provides a method for distance measurement based on a binocular camera, a system for distance measurement based on a binocular camera, a device and a computer-readable storage medium. The method includes: taking N images of a distance measurement marker placed at each of Z positions in a depth direction of the binocular camera; calculating an average disparity of the distance measurement marker at the middle position, the left side position and the right side position at each of the Z positions; calculating a distance measurement value at each of the Z positions in the depth direction; calculating a distance measurement error value at the middle position, the left side position and the right side position at each of the Z positions, and acquiring a total error cost function; and calculating extrinsic parameters, so as to acquire a distance measurement result in the depth direction.

Abstract: The present disclosure provides a method for calibrating a binocular camera, including: S2 of extracting feature points from an image set 1 and an image set 2 taken at two points separated from each other by a predetermined distance; S3 of fitting Gaussian distribution parameters of each feature point, and extracting a desired value as a theoretical disparity; S4 of selecting a common feature point, and calculating the predetermined quantity of frames at a first theoretical distance and the predetermined quantity of frames at a second theoretical distance; S5 of performing Gaussian fitting on a difference between the theoretical distances of the common feature point, and extracting a variance as an evaluation index; S6 of determining whether the evaluation index is smaller than a threshold, if yes, terminating the calibration, and otherwise, proceeding to S7; and S7 of adjusting posture parameters of the binocular camera, and returning to S3.

Abstract: Provided is a binocular camera depth calibration method, a binocular camera depth calibration device, a binocular camera depth calibration system and a storage medium. The method includes: acquiring a plurality of groups of images of a 2D code calibration board at different positions so as to acquire disparity maps of the 2D code calibration board; acquiring a 2D code template image of a target region; matching the 2D code template image, so as to determine and store matching region information; determining a position of the 2D code template image in each disparity map in accordance with the matching region information, and calculating an average disparity value of the 2D code template image at the position; acquiring a plurality of groups of average disparity values, and calculating a final disparity value; and calibrating a depth of a binocular camera.

Abstract: Provided is a road surface information-based imaging environment evaluation method, an imaging environment evaluation device, an imaging environment evaluation system, and a storage medium. The imaging environment evaluation method includes: acquiring a disparity information matrix and pixel coordinates of a vanishing point in the disparity information matrix; subjecting the disparity information matrix to matrix partition and projection in accordance with the pixel coordinates of the vanishing point so as to acquire a disparity projection image; acquiring a road surface model-based statistic model in accordance with the disparity projection image; and acquiring an evaluation result of a current imaging environment in accordance with a relationship between the statistic model and a predetermined threshold.

Abstract: The present disclosure provides a method and a device for detecting a height-limiting rod, and an automatic driving system, for use in a binocular stereo camera. The method includes: filtering out invalid points in a disparity map corresponding to a target image in accordance with a predetermined detection range, so as to acquire a valid point disparity map; projecting the valid point disparity map along an X-axis direction in a three-dimensional coordinate system onto a plane where a Y axis and a Z axis are located, and counting the quantity of valid points for each row of pixels with respect to each disparity value, so as to acquire a projection image; filtering out invalid projection points and invalid blobs in the projection image, so as to acquire a valid blob image; and back-projecting the valid blob image to the three-dimensional coordinate system, and determining a rectangular region where the height-limiting rod is located in accordance with X-axis, Y-axis and Z-axis coordinate values.

Abstract: An image edge extraction device for an automated driving system is capable of extracting an image edge in a rapid manner. The device employs an image edge extraction method that includes: acquiring a grayscale image of a target image; calculating an edge magnitude and an edge angle of the grayscale image, so as to generate an edge magnitude image and an edge angle image; detecting an edge peak of the edge magnitude image in accordance with the edge angle image, so as to acquire each edge point of the edge magnitude image and acquire an edge peak detection result; and performing double-thresholding segmentation on the edge peak detection result through a flooding method, so as to acquire an image edge of the target image.

Abstract: A method for building a camera imaging model includes: converting world coordinate values of a random point P into camera coordinate values of a target camera in accordance with a predetermined mode; converting the camera coordinate values into image coordinate values of the target camera; and converting the image coordinate values into digital image coordinate values and building the camera imaging model. The converting the image coordinate values into the digital image coordinate values includes performing a spatial sampling operation on the random point P, and adjusting coordinate values of an origin to image coordinate values through calculation. The method can be used in an automated driving system for a vehicle.

Abstract: The present disclosure provides a detection method and a detection device for a digital camera. The detection method includes: Step 1 of moving the to-be-detected auto-focusing lens assembly to a position spaced apart from a subject by a first distance; Step 2 of performing automatic exposure control until an average luminance value of a central region of an image is in a stable state; Step 3 of locking an automatic exposure control parameter; Step 4 of taking a first image; Step 5 of determining sizes of four corner regions in the first image; Step 6 of counting average luminance values of the four corner regions; and Step 7 of, in the case that the average luminance values of the four corner regions are identical to each other, determining that the to-be-detected auto-focusing lens assembly is installed at an accurate position. According to the present disclosure, it is able to detect where or not the auto-focusing lens assembly is installed at the accurate position in an automatic and efficient manner.

Abstract: A lane departure warning method includes steps of: collecting a road image by an imaging device; detecting a lane marking in accordance with the road image, so as to extract a position of the lane marking and an angle of the lane marking relative to a running direction of the vehicle; acquiring steering information and a movement speed of the vehicle by an OBD system; judging whether or not the vehicle is unconsciously running on the lane marking in accordance with the position of the lane marking, the angle of the lane marking relative to the running direction of the vehicle and the steering information of the vehicle; in the case that the vehicle is unconsciously running on the lane marking, recording a duration within which the vehicle is unconsciously running on the lane marking; and judging whether or not to send a lane departure warning to the vehicle.

Abstract: An obstacle warning method includes the steps of: acquiring scenario images at a current sampling time and a previous sampling time, and a map about first relative distances between respective viewing points in a viewing field and a vehicle; acquiring a profile and marking information of an obstacle and a map about a second relative distance between the obstacle and the vehicle in accordance with the map about the first relative distances; calculating a map about a third relative distance between the obstacle and the vehicle at a previous sampling time in accordance with the map about the first relative distances at the previous sampling time, the profile and the marking information of the obstacle at the current sampling time and a motion vector of the obstacle from the current sampling time to the previous sampling time.