Beijing Smarter Eye Technology Co. Ltd.

Shenzhen Pengcheng Electric Group Co., Ltd

Shenzhen Talent Database Data Technology Co., Ltd

Other

Ran Meng

Hua Chai

Feng Cui

An Jiang

Haitao Zhu

Zhe Wang

Qiwei Xie

Zunying Pang

Yong Jia

Bin Chen

Hui Cai

Zhipeng Xiao

Chuanbin Feng

Yanqiu Xia

Xi Chen

Jian Li

Li Li Ma

Chao Yang

Zhao Sun

Shanshan Pei

Haifeng Lai

Jixia Du

Wentao Lin

Shuhong Wu

Yuzhi Lin

Zhiwei He

Ruibin Lin

Jun Liao

Huosheng Xu

A real-time ground fusion system is based on binocular stereo vision and an intelligent terminal. The method for accomplish real-time ground fusion includes: S1 of obtaining a disparity map about a same road scenario, and converting a disparity map in a target region into a 3D point cloud; S2 of performing pose conversion on a current frame and a next frame adjacent to the current frame, and performing inverse conversion on a 3D point cloud of the current frame; and S3 of repeating S2 with each frame in the target region as the current frame, so as to achieve ground fusion. Through the conversion and fusion of adjacent frames, holes caused by the projection of the disparity map can be filled to assist driving and output accurate height data, thereby improving comfortableness.

Real-time ground fusion method and system based on binocular stereo vision, and intelligent terminal

Provided is an Aobject-based short range measurement method, a short range measurement device, a short range measurement system, and a storage medium. The short range measurement method includes: identifying a target object, and acquiring border information about an ROI of the target object; acquiring two groups of geometric constraint points of the target object with respect to a left-eye camera and a right-eye camera respectively; acquiring pixel coordinates of each geometric constraint point and a border pixel size corresponding to the border information, and calculating a monocular distance estimation value of the target object; acquiring an overall disparity of the two groups of geometric constraint points, and calculating a binocular distance estimation value of the target object in accordance with the overall disparity; and acquiring a final measurement value in accordance with the monocular distance estimation value and the binocular distance estimation value.

Object-based short range measurement method, device and system, and storage medium

The topographic environment detection method and a topographic environment detection system based on a binocular stereo camera, and an intelligent terminal are provided. The topographic environment detection method includes: obtaining a left-eye image and a right-eye image about a same road scenario, and processing the left-eye image and the right-eye image to obtain a dense disparity map of the road scenario; converting image information in a detection region into 3D point cloud information in a world coordinate system in accordance with the dense disparity map; fitting a road surface model in accordance with the 3D point cloud information; inputting an image in the detection region into a trained semantic segmentation model, and obtaining a segmentation result from the semantic segmentation model; and obtaining topographic information about the detection region in accordance with the segmentation result, and transmitting the topographic information to a vehicle assistant driving system.

Topographic environment detection method and system based on binocular stereo camera, and intelligent terminal

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.

Vehicle positioning device for vehicle vision calibration, and positioning adjustment method and system

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.

RGB-D fusion information-based obstacle target classification method and system, and intelligent terminal

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.

Method and system for calculating a focusing parameter of a binocular stereo camera, and intelligent terminal

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.

Vehicle braking and warning method, system and device based on binocular stereo camera

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.

Method, device and system for automatically braking commercial vehicle

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.

Method and device for detecting height-limiting rod, and automatic driving system

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.

Image edge extraction method and device, and automated driving system

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.

Method and device for building camera imaging model, and automated driving system for vehicle

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.

Method and device for detecting digital camera

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.

Method and device of lane departure warning and automobile driving assistance system

The present disclosure provides a disparity map-based obstacle detection method, a disparity map-based obstacle detection device, and a vehicle assistant driving system. The method includes steps of: acquiring a disparity map and a V disparity map in accordance with an image including a road surface; simulating the road surface in accordance with the V disparity map; identifying a first obstacle in accordance with a simulation result; extracting an object whose disparity value is greater than a first threshold in accordance with the disparity map, and subjecting the object to morphological operation so as to identify a second obstacle; extracting an object whose disparity value is smaller than a second threshold in accordance with the disparity map, and subjecting the object to morphological operation so as to identify a third obstacle; and screening the first obstacle, the second obstacle and the third obstacle in accordance with a training model, so as to detect the obstacle, the training model being acquired through machine learning in accordance with correct obstacle information and erroneous obstacle information. According to the present disclosure, it is able to improve the robustness.

Detecting method and device of obstacles based on disparity map and automobile driving assistance system

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.

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Beijing, China

Ran Meng