Baidu Online Network Technology (beijing) Co., Ltd.

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

Yuqiang Zhai

Tian Xia

Shufu Xie

Yu Ma

Xun Sun

Han Gao

Hao Wang

Li Wang

Rui Wang

Yucheng Wang

Shijia Chen

Mingjian Liu

Ming Li

Embodiments of the present application provide a lane line processing method and a lane line processing device. The method can include: performing a binarization processing on a first image to obtain a binary image, the first image including lane line points and non-lane line points; performing a connected domain analysis on the binary image to obtain at least one connected domain in the binary image, the connected domain including a plurality of adjacent lane line points; determining lane line points in a group corresponding to a lane line, based on the connected domain; and obtaining representation information of the lane line corresponding to the group, by using the lane line points in the group.

Lane line processing method and device

Embodiments of the present disclosure disclose a method for position detection, a device, and a storage medium. The method includes: detecting a first lane line in a current image captured by a camera; performing an optimization on an initial transformation matrix reflecting a mapping relationship between a world coordinate system and a camera coordinate system based on a detection result of the first lane line; and obtaining a first 3D coordinate of a target object in the current image according to a transformation matrix optimized, and determining an ultimate 3D coordinate of the target object according to the first 3D coordinate.

Method for position detection, device, and storage medium

A lane line processing method and device are provided. The method can includes obtaining distances between lane line points in a first image, determining direction densities of the individual lane line points by using the distances between the lane line points, dividing lane line points into groups corresponding to lane lines by using the direction densities of the individual lane line points, and obtaining representation information of the lane lines corresponding to the groups by using the lane line points in the groups. By using the direction densities of the individual lane line points, lane line points in an image are divided into groups, the obtained groups are then more accurate, and thus the lane lines obtained by fitting are accurate, are less susceptible to image quality issues, and have high robustness.

A lane line tracking method and device are provided. The method can include: projecting a lane line detection result of previous K frames preceding a current frame in a camera coordinate system to a world coordinate system, to obtain a first projection result, wherein K is a positive integer greater than or equal to 1, and the previous K frames are consecutive K frames preceding the current frame; projecting the first projection result of the previous K frames in the world coordinate system to a camera coordinate system of the current frame, to obtain a second projection result; and determining, in the camera coordinate system of the current frame, lane line groups of the current frame, according to lane line groups in the second projection result of the previous K frames.

Lane line tracking method and device

The method comprises: obtaining a first image collected by a long-focus camera, a second image collected by a short-focus camera, and positioning information and travelling direction of the autonomous vehicle collected by a positioning sensor at a target moment; according to the positioning information and traveling direction of the autonomous vehicle at the target moment, obtaining, from a high-precision map server, location information of traffic lights within a range of preset distance threshold ahead in the traveling direction of the autonomous vehicle at the target moment; recognizing the state of traffic lights at the target moment, according to the location information of the traffic lights at the target moment, and one image of the first image and second image.

Traffic light state recognizing method and apparatus, computer device and readable medium

The disclosure discloses a method and apparatus for identifying a traffic light. An embodiment of the method comprises: zooming a to-be-processed image acquired by an image acquisition device by at least one preset ratio to obtain at least one zoomed image; inputting the at least one zoomed image into a pre-trained convolutional neural network to obtain location information and category information of a traffic light corresponding to each zoomed image of the at least one zoomed image, wherein the convolutional neural network is used for retrieving location information and category information of a traffic light displayed in an image; and analyzing the obtained location information and category information to generate at least one candidate traffic light identification result, and fusing the generated candidate traffic light identification result to generate a traffic light identification result corresponding to the to-be-processed image. The embodiment improves the accuracy in identifying a traffic light.

Method and apparatus for identifying traffic light

The present disclosure provides a three-dimensional posture estimating method and apparatus, a device and a computer storage medium, wherein the method comprises: obtaining two-dimensional posture information of an object in an image and three-dimensional size information of the object; determining coordinates of key points of the object in an object coordinate system according to the three-dimensional size information of the object; determining a transformation relationship between a camera coordinate system and the object coordinate system according to a geometrical relationship between coordinates of key points of the object in the object coordinate system and the two-dimensional posture information of the object. Application of this manner to the field of autonomous driving may implement mapping a detection result of a two-dimensional obstacle to a three-dimensional space to obtain its posture.

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Beijing, China

Yuqiang Zhai