An edge device for monitoring safety of a highway work zone is disclosed. The edge device includes at least one camera, one or more processors, and memory. The at least one camera is configured to capture images in sequence. The memory stores computer-executable instructions that, when executed, cause the one or more processors to: perform vehicle detection over an input of a data stream of the images, from the at least one camera, utilizing just-in-time processing; determine a level of safety by tracking vehicles detected and performing a time sequence analysis of the vehicles; and send a signal to one or more assisted reality devices indicating the level of safety thereto.

An edge device for monitoring safety of a highway work zone is disclosed. The edge device includes at least one camera, one or more processors, and memory. The at least one camera is configured to capture images in sequence. The memory stores computer-executable instructions that, when executed, cause the one or more processors to: perform vehicle detection over an input of a data stream of the images, from the at least one camera, utilizing just-in-time processing; determine a level of safety by tracking vehicles detected and performing a time sequence analysis of the vehicles; and send a signal to one or more assisted reality devices indicating the level of safety thereto.

A reward system and method collects feedback based on driving records and road conditions. A camera disposed on a vehicle can generate traffic-condition data, and the neural network based artificial intelligence is used to identify a traffic flow and a road-sign area in the traffic-condition data. When the road-sign area is identified, the optical character recognition is performed on the road-sign area to generate a geographic location information. The user information, the traffic flow and the geographic location information are embedded into the corresponding traffic-condition data. The traffic-condition data is transmitted to a map-data host for classification and storage. When the geographic location information of the traffic-condition data matches with road congestion location information and a clarity of the traffic-condition data is greater than a preset threshold, a contribution reward is calculated to improve timeliness of updating the traffic-condition data and the user's incentive for providing the traffic-condition data.

A computer vision-based system provides for load distribution estimation and load rating and vibration serviceability assessment of structures. The system integrates evaluates the structural load carrying capacity, the diagnosis and prognosis of performance and safety, and vibration serviceability. Cameras record images of a structure, and regions of interest are monitored in those images for their displacement and velocity as loading varies. Where the displacement determined exceeds a predetermined threshold, or where the acceleration determined exceeds predetermined limits, or where the distribution of displacements of parts of the structure deviates substantially from an estimated displacement distribution, an output indicating potential problems with the structure is output.

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.

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.

A vehicle imaging station for capturing images of scratches on a vehicle, the vehicle imaging station including a tunnel having an entrance and an exit, with one or more walls defining an enclosure between the entrance and exit to define a tunnel volume containing a vehicle pathway having a central axis. The station further includes a reflection source surface and a camera arranged with a field of view including an imaging volume of the tunnel volume in which an image defined by the reflection source surface will be reflected to be visible to the camera as a reflected image by a vehicle moving along the vehicle pathway. The station also includes a color modifier arranged to cause the reflection source surface to adopt a first color of a plurality of possible colors in response to a color control signal such that the reflected image has the first color.

A vehicle imaging station for capturing images of scratches on a vehicle, the vehicle imaging station including a tunnel having an entrance and an exit, with one or more walls defining an enclosure between the entrance and exit to define a tunnel volume containing a vehicle pathway having a central axis. The station further includes a reflection source surface and a camera arranged with a field of view including an imaging volume of the tunnel volume in which an image defined by the reflection source surface will be reflected to be visible to the camera as a reflected image by a vehicle moving along the vehicle pathway. The station also includes a color modifier arranged to cause the reflection source surface to adopt a first color of a plurality of possible colors in response to a color control signal such that the reflected image has the first color.

A method of performing an object segmentation on a video using a semantic segmentation model, a device, and a storage medium, which relate to a field of artificial intelligence, in particular to computer vision and deep learning technologies. The method includes: sequentially inputting a current video frame and a previous video frame into a first feature extraction network to obtain a feature map sequence; sequentially inputting object segmentation information of the previous video frame into a second feature extraction network to obtain a segmentation feature sequence; sequentially inputting the current video frame and the previous video frame into a temporal encoding network to obtain a temporal feature sequence; generating a fused feature sequence based on the feature map sequence, the segmentation feature sequence and the temporal feature sequence; and inputting the fused feature sequence into a segmentation network to obtain an object segmentation information of the current video frame.

A method of recognizing an image is provided, which relates to a field of artificial intelligence technology, in particular to a field of image recognition. The method includes: recognizing a plurality of target object groups of different categories from an image to be recognized; intercepting an area of each target object group from the image to be recognized, so as to obtain a target image of the each target object group; recognizing a number of at least one target object in the each target object group from the target image of the each target object group; and generating a scheduling information for the each target object group according to the category of the each target object group and the number of the at least one target object in the each target object group. An electronic device and a storage medium are further provided.