A system of detection, tracking and identification of an evolutionary adaptation of a vehicle lamp includes an image capture device and a processor. The image capture device captures an image of a vehicle. The processor processes the image of the vehicle to generate a detection result of the vehicle lamp, analyzes and integrates vehicle lamp dynamic motion information and vehicle lamp multiple scale variation information based on the detection result, and then tracks the position of the vehicle lamp by applying a multiple scale vehicle lamp measurement model.

Auto-completion of an input partial line pattern. Upon detecting that the user has input the partial line pattern, the scope of the input partial line pattern is matched against corresponding line patterns from a collection of line pattern representations to form a scoped match set of line pattern representations. For one or more of the line pattern representations in the scoped match set, a visualization of completion options is then provided. For example, the corresponding line pattern representation might be displayed in a distinct portion of the display as compared to the input partial line pattern, or perhaps in the same portion in which case, in which case the remaining portion of the line pattern representation might extend off of the input partial line pattern representation.

A pedestrian retrieval method and apparatus that belong to the video surveillance field include extracting first feature data, second feature data, and third feature data of a target pedestrian image, where the target pedestrian image is an image of a to-be-retrieved pedestrian, and the first feature data, the second feature data, and the third feature data respectively include a plurality of pieces of body multidimensional feature data, a plurality of pieces of upper-body multidimensional feature data, and a plurality of pieces of lower-body multidimensional feature data of the target pedestrian image, screening stored multidimensional feature data based on the first feature data, the second feature data, and the third feature data to obtain a target feature data set, and outputting a pedestrian retrieval result using the target feature data set.

[PROBLEMS TO BE SOLVED] It is an object to provide a marker and a marker generating and detecting technology that can automatically design a diagrammatic marker that is not similar to any patterns to appear during the reproduction of background video images. [MEANS FOR SOLVING THE PROBLEMS] A marker generating system is characterized in having a special feature extracting means that extracts a portion, as a special feature, including a distinctive pattern in a video image not including a marker; a unique special feature selecting means that, based on the extracted special feature, selects a special feature of an image, as a unique special feature, that does not appear on the video image; and a marker generating means that generates a marker based on the unique special feature.

This disclosure provides an apparatus and method for performing object detection based on images captured by a fisheye camera and an electronic device. The apparatus includes a memory and a processor coupled to the memory. The processor according to an embodiment is configured to: project an original image captured by the fisheye camera onto a cylindrical or spherical projection model, and perform reverse mapping to obtain at least two reversely mapped images, angles of view of the at least two reversely mapped images being towards different directions, detect objects in the reversely mapped images, respectively, and detect an object that is the same among the objects detected in the reversely mapped images. According to this disclosure, information in the wide field of view images obtained by capturing by the fisheye camera may be fully utilized.

Systems and methods for roof area and slope estimation using a point set are provided. The system selects roof structure points having a high probability of being positioned on a top surface of a structure present in the region of interest point set. Then, the system determines a footprint of the structure associated with the selected roof structure points. The system determines a distribution of the slopes of the roof structure points and generates a slope distribution report indicative of prominent slopes of the roof structure and each slope's contribution toward (percentage composition of) the total roof structure. The system then determines an area of the roof structure based on the footprint of the structure and the slope distribution report.

Provided are a device and method for providing a notification message related to content. The method includes: recognizing an action related to at least one object in the image content by applying the image content to a first artificial intelligence model for identifying the action of the at least one object; determining target images for identifying the at least one object in the image content; obtaining identification information of the at least one object in the target images by applying the target images to at least one second artificial intelligence model for identifying the at least one object; and generating the notification message describing the image content by applying, to a third artificial intelligence model, an identification value indicating the action and the identification information of the at least one object.

Provided are a device and method for providing a notification message related to content. The method includes: recognizing an action related to at least one object in the image content by applying the image content to a first artificial intelligence model for identifying the action of the at least one object; determining target images for identifying the at least one object in the image content; obtaining identification information of the at least one object in the target images by applying the target images to at least one second artificial intelligence model for identifying the at least one object; and generating the notification message describing the image content by applying, to a third artificial intelligence model, an identification value indicating the action and the identification information of the at least one object.

An image processor includes an edge detection portion that scans an image and detects, as an edge, an arrangement of pixels in which brightness value difference or color parameter difference between the pixels is equal to or greater than a threshold; a grouping portion that groups the detected edge based on the edge length, a distance between endpoints of the edges, and an angle between the edges; a determination portion that determines the grouped edges as a dashed line edge group when a pattern in which the brightness value difference or color parameter difference between the pixels is detected matches a predetermined pattern; a correction portion that performs a linear approximation process on the dashed line edge group to correct a coordinate value of an endpoint of the dashed line edge; and a parking frame setting portion that sets a parking frame using the corrected dashed line edge.

An image recognition method includes a feature amount extracting step of generating, from an input image, a base feature map group including a plurality of base feature maps; an inferring step of deriving a plurality of inference results using each of a plurality of machine-learned inference devices for a plurality of inference inputs based on the base feature map group; and an integrating step of integrating the plurality of inference results by a specific manner to derive a final inference result, where each of the plurality of inference inputs has some or all base feature maps of the plurality of base feature maps, and each of the plurality of inference inputs has the some or all base feature maps that are different in part or whole from the some or all base feature maps of another inference input in the plurality of inference inputs.