Zhejiang Dahua Technology Co., Ltd.

Qiankun Li

Wei Lu

Shizhu Pan

Jun Yin

Xingming Zhang

Xiaohui Sun

Haijiang Pan

Jinting Wang

Jichao Geng

Miao Cheng

Zhangwei Zhou

Xiangming Zhou

Qing Guo

A method and system for image processing are provided in the present disclosure. The method may include obtaining a first image and determining whether there is an object of interest in the first image by performing an object detection on the first image. The method may also include upon a determination that there is an object of interest in the first image, retrieving at least one background image from a first storage device, and obtaining a foreground image. The method may further include upon a determination that there is no object of interest in the first image, determining whether a first predetermined condition is satisfied; and upon a determination that the first predetermined condition is satisfied, updating the at least one background image in the first storage device based on at least one candidate image determined as including no object of interest.

Method and system for obtaining and processing foreground image and background image

Systems and methods for lane detection are provided. The methods may include obtaining an image and determining, for each of a plurality of pixels in an image, a semantic category using a trained semantic segmentation network. The methods may further include determining one or more pixel sets based on the plurality of pixels according to a predetermined rule. Each of the one or more pixel sets includes one or more pixels of a same semantic category. The methods may further include, in response to a determination that there are one or more erroneous pixels in a pixel set, removing the one or more erroneous pixels from the pixel set to obtain a fitting line corresponding to a lane line. The methods may further include determining a position of the lane line based on the fitting line.

Systems and methods for lane detection

A system and method for jointly displaying an image and a map is disclosed. The method may including obtaining an image captured by a camera. The image may include a target in a surrounding environment of the camera. The method may further include obtaining a map of the surrounding environment. The map may at least include a location corresponding to the target and a location corresponding to the camera. The method may jointly display the image and the map, wherein a representation of the image is aligned with the location corresponding to the target and the location corresponding to the camera in the map.

Systems and methods for image display

A method and system for locating a target object in a target scene. The method may include obtaining a depth image of the target scene. The depth image may include a plurality of pixels. The method may also include, for each of the plurality of pixels of the depth image, determining a first target coordinate under a target coordinate system. The method may further include generating a marking image according to the depth image and the first target coordinates of the plurality of pixels in the depth image. The marking image may represent potential target objects in the depth image. The method may also include determining a locating coordinate of the target object under the target coordinate system according to the marking image.

Locating method and system

A system and method for determining a dimension of a target. The method includes: determining a camera parameter, the camera parameter including at least one of a focal length, a yaw angle, a roll angle, a pitch angle, or a height of one or more cameras; acquiring a first image and a second image of an target captured by the one or more cameras; generating a first corrected image and a second corrected image by correcting the first image and the second image; determining a parallax between a pixel in the first corrected image and a corresponding pixel in the second corrected image; determining an outline of the target; and determining a dimension of the target based at least in part on the camera parameter, the parallax, and the outline of the target.

Methods and systems for traffic monitoring

A method relating to an image fusion includes acquiring a thermal infrared image and a visible image. The method also includes receiving a fusion parameter corresponding to a color space and generating, based on the fusion parameter, a fused image of the thermal infrared image and the visible image. The method further includes receiving a regulation parameter, the regulation parameter including a color scheme or a partial contrast, and adjusting the fused image according to the regulation parameter.

Methods and systems for fusion display of thermal infrared and visible image

The present disclosure provides a method for identifying a plurality of lane lines on a road segment. The method may include obtaining a plurality of images of the road segment having one or more lanes and vehicles, and identifying a plurality of reference straight lines from the images. The method may include determining a vanishing point based on the reference straight lines, and determining a plurality of candidate lane lines among the reference straight lines based on the vanishing point. The method may also include determining at least one travel trajectory of at least one of the vehicles based on the images. The method may further include determining a target travel trajectory among the travel trajectory based on the vanishing point or a count of the lanes, and determining the lane lines among the candidate lane lines based on the target travel trajectory.

Methods and systems for lane line identification

A system and method for binocular stereo vision is disclosed. The method includes acquiring a pair of images including a first image and a second image, the pair of images being captured by one or more cameras; obtaining a training model; determining a plurality of feature images according to the first image; determining one or more features of an object in the first image according to the training model and the plurality of feature images; determining a first area in the first image, the first area including at least one of the determined one or more features; obtaining depth information of the determined first area based on the first and second images; and determining a second area in the first image based on the determined first area and depth information, the second area including at least one of the determined first area.

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Hangzhou, China

Qiankun Li