Computer-implemented method, systems, computer program products include a processor(s) that obtains input data comprising an image and image data: coordinates (points) defining a region of interest in the image. The processor(s) determines a non-duplicative sequential order for navigating the coordinates. The processor(s) defines a set of points bordering the region of interest: points in the image and points comprising intersection points between two coordinates with an edge of a pixel in the image. The processor(s) determines a combined area of sub pixel subregions in each pixel that includes points in the set of points by: identifying the points of the set, generating one or more sub pixel subregions, and utilizing the sub pixel subregions to determine the combined area of sub pixel subregions.

A map generation device (10) generates linearization information expressing at least one or the other of a marking line of a roadway and a road shoulder edge based on measurement information of a periphery of the roadway. The measurement information is obtained by a measurement device. The map generation device (10) calculates an evaluation value expressing a reliability degree of partial information, for each partial information constituting the linearization information. A map editing device (20) displays the partial information in different modes according to the evaluation value, thereby displaying the linearization information. The map editing device (20) accepts input of editing information for the displayed linearization information.

An image analyzer unit performs lesion site detection for each tomographic image. In response to a lesion site detection state, the image analyzer unit outputs a position data array and a size data array that represent temporal change in position and size of the lesion site. A rate of change calculator unit calculates a rate of change that represents a degree of temporal change in tomographic image content. A smoother unit smooths the position data array and the size data array in accordance with the rate of change. A mark is generated based on the smoothed position data array and the smoothed size data array.

An image analyzer unit performs lesion site detection for each tomographic image. In response to a lesion site detection state, the image analyzer unit outputs a position data array and a size data array that represent temporal change in position and size of the lesion site. A rate of change calculator unit calculates a rate of change that represents a degree of temporal change in tomographic image content. A smoother unit smooths the position data array and the size data array in accordance with the rate of change. A mark is generated based on the smoothed position data array and the smoothed size data array.

Systems and methods for utilizing Augmented Reality (AR) processes to track cables among a tangled bundle of cables are provided. An AR method, according to one implementation, includes a step of obtaining an initial captured image showing a bundle of cables. The AR method also includes the step of processing the initial captured image to distinguish a selected cable from other cables of the bundle of cables. Also, the AR method includes displaying the initial captured image on a display screen while visually augmenting an image of the selected cable to highlight the selected cable with respect to the other cables.

An image matting method and apparatus, an electronic device, and a computer-readable storage medium. The method comprises: performing feature point detection on an image so as to obtain a feature point; acquiring a first image region manually marked on the image; adjusting the first image region according to the feature point, so as to obtain a second image region; and performing matting on the image according to the second image region. The manually marked first image region is adjusted according to the feature point, so as to acquire the second image region which is more accurately positioned, and then matting can be performed according to the second image region so as to accurately extract a required region.

An image matting method and apparatus, an electronic device, and a computer-readable storage medium. The method comprises: performing feature point detection on an image so as to obtain a feature point; acquiring a first image region manually marked on the image; adjusting the first image region according to the feature point, so as to obtain a second image region; and performing matting on the image according to the second image region. The manually marked first image region is adjusted according to the feature point, so as to acquire the second image region which is more accurately positioned, and then matting can be performed according to the second image region so as to accurately extract a required region.

A device comprises processing circuitry to receive an input polygon comprised of a plurality of segments connected by a plurality of points, some of the plurality of segments extending in a first direction and remaining ones of the plurality of segments extending in a second direction perpendicular to the first direction. The processing circuitry performs a first set of operations on the input polygon to generate an intermediate polygon having a plurality of vertices, a number of the plurality of vertices being fewer than a number of the plurality of points. The processing circuitry performs a second set of operations on the intermediate polygon based on traits of the plurality of vertices to generate a final polygon with a contour that represents the input polygon, the contour including at least one section that extends in a third direction different than the first direction and the second direction.

A system for generating three-dimensional models of a physical environment such as a room. In some cases, the system may utilize a two-dimensional floor, room, or house plan to generate, close and/or orthogonalize wall segments. The system may then generate a three-dimensional model by projecting the wall segments into a three-dimensional space and inserting objects.

A map fusing method includes receiving a source graph and a target graph. The source graph is representative of a source map and the target graph is representative of a target map and includes nodes and edges that connect the nodes. The method further includes processing each of the source graph and the target graph in a graph convolutional layer to provide graph convolutional layer outputs related to the source graph and to the target graph, processing each of the graph convolutional layer outputs for the source graph and the target graph in a linear rectifying layer to output node feature maps related to the source graph and the target graph. The method further includes selecting pairs of node representations from the node feature maps related to the source graph and the target graph and concatenating the selected pairs to output selected and concatenated pairs of node representations.