The present invention discloses a pedestrian trajectory prediction method and system based on a multi-interaction spatio-temporal graph network, which belong to the field of pedestrian trajectory prediction. The method includes: extracting multi-interaction features of pedestrians in video frames; for each frame in a video sequence, abstracting each pedestrian in the frame as a vertex, connecting the pedestrian(s) with other pedestrians to form an edge(s), where the vertex attribute is the multi-interaction feature of the pedestrian so as to obtain a multi-interaction spatio-temporal graph network; for each multi-interaction spatio-temporal graph, obtaining spatial dependencies of each pedestrian with other pedestrians in the spatio-temporal graph, and optimizing the attribute of each vertex through the spatial dependencies between pedestrians; the vertices of adjacent time points of the pedestrians are connected to obtain time dependencies of the pedestrians, and then infer a trajectory of a future time point(s).

Image processing to discriminate imaged objects that are adjacent or overlapping. Non-empty cells of the image that contain portions of the objects, and empty cells that lack any portions of the objects, are all determined. A global convex hull is defined to surround the non-empty cells of the image. Voids, including at least a first void and a second void, are found within the global convex hull, each being composed of contiguous empty cells and having a corresponding void boundary. A separation line is defined based on a first separation line endpoint along the void boundary of the first void and a second separation line endpoint along the void boundary of the second void, to separate two of the objects in the image. An output may be produced that includes indicia of at least portions of distinct boundaries of the objects in the image based on the separation line.

A method for determining a similarity between curves performed by an electronic device includes extracting a candidate curve corresponding to at least a part of a blood vessel and a source curve corresponding to a guidewire from a blood vessel image, sampling the same sampling number of points from each of the candidate curve and the source curve, calculating a similarity level between the candidate curve and the source curve based on the points sampled from the candidate curve and the points sampled from the source curve, and determining whether the candidate curve and the source curve are similar, based on the calculated similarity level.

A generation device includes processing circuitry configured to receive a plurality of inputs of road map data including longitude/latitude data on lane information indicating a center line of a lane, longitude/latitude data on a road shoulder line, and longitude/latitude data on a lane marker, and refer to the road map data and generate a first polygon indicating a region of a lane based on a plurality of intersections on the lane marker or the road shoulder line crossed by a vertical line from the lane information.

An object detection method, for detecting a target object, comprising: capturing at least two detection portions with a first aspect ratio from an input image with a second aspect ratio; confirming whether any object is detected in each of the detection portions and obtaining corresponding boundary boxes for detected objects; and wherein the first aspect ratio is different to the second aspect ratio.

A method of analysing the quality of a welding area of an absorbent sanitary article is disclosed. During a learning step, a plurality of welding operations are performed both with a sufficient quality and with an insufficient quality, and the welding area generated for each welding operation is monitored via a camera. During a training step, the pixel data of the welding areas monitored during the learning step is processed for training a classifier configured to estimate a welding quality as a function of respective pixel data of a respective welding area. Accordingly, during a normal welding operating step, the welding quality may be estimate via the classifier, thereby improving the environmental sustainability of the production process.

An image processor includes an imaging device that captures an image of a road surface around a vehicle V, and a control portion that detects a marker drawn on the road surface from the captured image. The control portion connects a plurality of broken markers to create a single marker when the detected marker is broken into plural.

Systems and methods are disclosed, including a non-transitory computer readable medium storing computer executable instructions that when executed by a processor cause the processor to identify a first image, a second image, and a third image, the first image overlapping the second image and the third image, the second image overlapping the third image; determine a first connectivity between the first image and the second image; determine a second connectivity between the first image and the third image; determine a third connectivity between the second image and the third image, the second connectivity being less than the first connectivity, the third connectivity being greater than the second connectivity; assign the first image, the second image, and the third image to a cluster based on the first connectivity and the third connectivity; conduct a bundle adjustment process on the cluster of the first image, the second image, and the third image.

A computer-implemented method for CAD volume extrusion operator detection in a CAD 3D model representing a mechanical part. The method includes obtaining a segmentation of the CAD 3D model. The CAD 3D model includes a skin representing an outer surface of the mechanical part. The segmentation comprises segments each representing a skin portion. The method further includes iteratively grouping segments. Segments of a pair are grouped when: each segment of the pair is an extrusion surface and a union of the segments is an extrusion surface having a same extrusion axis as the segments, or each segment of the pair is an extrusion surface and one of the two segments is a closing plane for the other segment. The method further includes determining one or more CAD volume extrusion operators, each corresponding to a respective group.

Disclosed is a diagnostic apparatus for a chronic obstructive pulmonary disease (COPD) based on prior knowledge CT subregion radiomics, belonging to the field of medical imaging. The diagnostic apparatus comprises: a subregion partitioning module based on prior knowledge configured for partitioning a CT lung image of a patient into three subregions based on the CT values of the interior of the lung, wherein the CT value of the interior of the lung of a subregion 1 is in the range of (−1024, −950), the CT value of the interior of the lung of a subregion 2 is in the range of (−190, 110), and the CT value of the interior of the lung of a subregion 3 is in the range of (−950, −190); a feature extraction module configured for extracting the radiomics features of the three subregions, respectively, and obtaining the LAA-950I features.