Beijing Baidu Netcom Science and Technology Co., Ltd.

Beijing Baidu Netcom Science Technology Co., Ltd

Apollo Intelligent Driving Technology (Beijing) Co., Ltd.

Pengbin Yang

Yang Yang

Jianxu Zhang

Fengze Han

Wenlong Chen

Caimao Yuan

Fei Ni

Xuguang Lv

Xiaohui Zhu

Songpeng Zhang

An image processing method, apparatus, and electronic device relate to the technical field of image processing. In the method, an initial image is acquired; and then a connected region in the initial image is acquired, where the connected region is a region composed of pixels having pixel values within a target threshold range in the initial image. In addition, a region of interest in the initial image is acquired according to the connected region, and the region of interest is preprocessed to obtain a target image. By extracting the region of interest in the initial image, and only preprocessing the region of interest, the resource expenditure during image preprocessing can be reduced, and the preprocessing efficiency can be improved.

Image processing method, apparatus, and electronic device

The present application discloses a method and an apparatus for calibrating external parameters of an image acquisition device, a device and a storage medium, and relates to the technical field of vehicle positioning. The specific implementation solution is as follows: acquiring an image captured by the image acquisition device; determining a plurality of marking points on a calibration plate in the image; determining a first conversion matrix based on coordinates of each of the marking points in the image pixel coordinate system and the calibration plate coordinate system; determining a second conversion matrix based on coordinates of at least one wheel grounding point of the vehicle in the calibration plate coordinate system and the vehicle body coordinate system; and determining external parameters of the image acquisition device by using the first conversion matrix and the second conversion matrix.

Method and apparatus for calibrating external parameters of image acquisition device, device and storage medium

The present disclosure provides a method of matching lane line data, which relates to a field of automatic driving, and in particular to a field of locating an autonomous vehicle. The method of matching lane line data includes: obtaining a first data indicating sensed lane lines and a second data indicating map lane lines respectively; constructing a correlation weight matrix for the first data and the second data, based on differences between the sensed lane lines and the map lane lines; and matching the first data with the second data according to the correlation weight matrix, so as to obtain a third data having an optimal match with the first data from the second data. The present disclosure further discloses an apparatus of matching lane line data, a device, a storage medium and a computer program product.

Method and apparatus of matching lane line data, device and storage medium

The present application discloses a method and an apparatus for processing map data, which relate to autonomous driving technologies in the field of data processing. The specific implementation is that: a controlling unit inputs initial positioning data collected by a data collecting unit to a data fusing unit to obtain fused positioning data, where the initial positioning data and the fused positioning data are data in a first coordinate system; the controlling unit obtains target positioning data according to the fused positioning data, where the target positioning data is data in a second coordinate system, and the second coordinate system is a coordinate system obtained by offsetting the first coordinate system; and the controlling unit performs a positioning operation on the target positioning data through at least one positioning unit, to determine a position of a vehicle corresponding to an autonomous driving system.

Method and apparatus for processing map data

The present disclosure provides a vehicle positioning method implemented by an electronic device, including: obtaining sensor data about N frames of a vehicle through a sliding window, N being a positive integer; creating a target function for a factor graph model in accordance with the sensor data about the N frames, and performing optimization solution on the target function; and determining a pose and a position of the vehicle in accordance with a target value obtained through the optimization solution on the target function.

Vehicle positioning method for determining position of vehicle through creating target function for factor graph model

The present application discloses a dead reckoning method for a vehicle, an apparatus, an apparatus and a storage medium, and relates to the fields of vehicle control, intelligent driving and automatic driving. The specific implementation solution is as follows: obtaining a position and attitude increment of the vehicle on the basis of wheel speed information of the vehicle; and carrying out dead reckoning on the position and attitude of the vehicle at a current moment, on the basis of the position and attitude increment of the vehicle and the position and attitude at a previous moment.

Dead reckoning method and apparatus for vehicle, device and storage medium

A lane line determination method and apparatus, a lane line positioning accuracy evaluation method and apparatus, a device and a storage medium are provided, which are related to a field of image processing, and particularly to fields of autonomous driving, intelligent transportation, computer vision and the like. The specific implementation is: determining a line in a received road image; screening pixels forming the line and determining pixels forming a lane line; and fitting the pixels forming the lane line to obtain the lane line. According to the technology of the present disclosure, the disadvantages of manual labeling can be overcome, and the lane line in the image collected by image acquisition device can be automatically recognized using an image recognition method, thereby improving the automation degree of lane labeling.

Growing community of inventors

Beijing, China

Pengbin Yang