Abstract: The present disclosure relates to a method for controlling a movable platform. The method may include obtaining a target object selection operation input by a user on an interaction interface, the interaction interface displaying a three-dimensional model of an operation area, the target object selection operation configured to determine a position of a target object in the operation area; determining a target orientation of the movable platform when the target object is operated based on an orientation of the three-dimensional model displayed on the interaction interface when the target object selection operation is obtained; and determining a target position of the movable platform when the movable platform performs operation on the target object based on the position of the target object, the target orientation, and an operation distance of the movable platform.

Abstract: A shooting method is provided, including: obtaining position information of a shooting object; planning a first circumnavigation route and a second circumnavigation route for surrounding shooting of the shooting object based on the position information; controlling a UAV to move along the first circumnavigation route and the second circumnavigation route respectively; and controlling the UAV to shoot the shooting object by a camera mounted on the UAV during movement to obtain multiple images of the shooting object. Images collected on the first circumnavigation route and images collected on the second circumnavigation route share homologous image points of the shooting object. The images are used to establish a three-dimensional model of the shooting object. Thus, the shooting efficiency of the UAVs is improved for shooting images for three-dimensional reconstruction.

Abstract: A method for generating a special effect for social networking interaction in a virtual environment of a game is performed by an electronic device. The method includes: displaying an object presentation interface of a target battle of the game when loading a virtual scene corresponding to the target battle, the object presentation interface being used for displaying a plurality of virtual objects participating in the target battle; receiving a special effect generating instruction for a first virtual object of the plurality of virtual objects, the special effect generating instruction being used for instructing to generate a special effect based on the first virtual object, and the first virtual object corresponding to a user of the electronic device triggering the special effect; and generating the special effect identifying the first virtual object in the object presentation interface.

Abstract: A control method and device for an unmanned aerial vehicle, and a non-transitory computer readable storage medium are provided. The control method may include: acquiring shooting control information, the shooting control information including a height of a shooting target object, a mission height, and an overlapping ratio; determining the target flight route and a shooting interval based upon the shooting control information; and controlling an unmanned aerial vehicle to fly according to the target flight route and to photograph the shooting target object according to the shooting interval by using a photographing device during the flight. The mission height may be a distance between a plane where a target flight route is located and a plane where the shooting target object is located, and a starting plane for computing the overlapping ratio may be the plane where the shooting target is located.

Abstract: The present disclosure relates to a method for controlling a movable platform. The method may include obtaining a target object selection operation input by a user on an interaction interface, the interaction interface displaying a three-dimensional model of an operation area, the target object selection operation configured to determine a position of a target object in the operation area; determining a target orientation of the movable platform when the target object is operated based on an orientation of the three-dimensional model displayed on the interaction interface when the target object selection operation is obtained; and determining a target position of the movable platform when the movable platform performs operation on the target object based on the position of the target object, the target orientation, and an operation distance of the movable platform.

Abstract: A machine vision-based tree recognition method and device are provided. The machine vision-based tree recognition method may include obtaining a top view image containing a tree and processing the top view image to obtain pixel position information of a tree center of the tree and tree radius information corresponding to the tree center in the top view image.

Abstract: The present disclosure relates to a method for determining initiation positions of fretting fatigue cracks. The processed inner circular hole test workpiece is placed on a stage of an optical microscope, wherein the inner hole surface to be measured is perpendicular to the scanning beam direction of the microscope; measurement is performed along the real contact orientation between the inner hole surface of the inner circular hole test workpiece and the pin shaft. From the measured surface morphology and profile image, rectangular target areas with a coverage rate of 75%˜90%, and the amplitude distribution function, surface skewness and surface kurtosis values of the respective surface profiles are extracted from the target areas. By comparing the positive/negative of and the magnitude of the skewness and kurtosis values measured in the target areas, the side where the initiation position of fretting fatigue cracks is located can be determined.

Abstract: A method for simplifying a three-dimensional mesh model includes obtaining N non-boundary edges of the three-dimensional mesh model; for each non-boundary edge of the N non-boundary edges, determining a deletion error of the non-boundary edge, determining a deletion weight of the non-boundary edge according to a feature parameter of each vertex of two vertices of the non-boundary edge, and adjusting the deletion error of the non-boundary edge according to the deletion weight of the non-boundary edge to obtain an adjusted deletion error of the non-boundary edge; and simplifying the three-dimensional mesh model according to the adjusted deletion errors of the N non-boundary edges. N is an integer larger than one.

Abstract: A point cloud generation method and system, and a computer storage medium are provided. The method includes: initializing a spatial parameter of each pixel in a reference image; updating the spatial parameter of each pixel through propagation of adjacent pixels; comparing the spatial parameter of each pixel after the propagation with that before the propagation to determine whether a change occurs, if a change occurs, performing classification based on differences in a depth and a score after versus before the propagation, and changing the spatial parameter within a range; calculating the score of changed spatial parameter of each pixel, and updating spatial parameters of at least some pixels to spatial parameters whose scores reach a preset threshold range; determining, based on an updated spatial parameter of each pixel, a depth map corresponding to the reference image; and generating a dense point cloud image based on the depth map.

Abstract: The present disclosure includes a depth image fusion method. The method includes obtaining one depth image and a reference pixel positioned in one of the depth images; determining a candidate queue corresponding to the reference pixel, the candidate queue storing one pixel to be fused that has not been fused in the depth image; determining a fusion queue corresponding to the reference pixel in the one of the depth images in the candidate queue, and pressing pixel to be fused in the candidate queue to the fusion queue, the fusion queue storing one selected fusion pixel in the depth image; obtaining feature information of the selected fusion pixel in the fusion queue; determining standard feature information of the fused pixel; and generating a fused point cloud corresponding to one of the depth images based on the standard feature information of the fused pixel.

Abstract: Embodiments of the present disclosure provide a method for processing camera parameters. The method includes obtaining an environmental image set, the environmental image set including a first type image and two or more second type images, a direction of a light sensing element of the camera capturing the first type image being different from the direction of the light sensing element of the camera capturing the two or more second type images; calculating internal parameters of the camera based on a plurality of target object image points on the first type image and the two or more second type images in the environmental image set. The camera is mounted on an aircraft. The camera is configured to capture a plurality of environmental images of an environment below the aircraft. The calculated internal parameters of the camera include an image position of the principal point of the camera.

Abstract: A three-dimensional (3D) reconstruction system based on aerial photography includes an unmanned aerial vehicle (UAV), a ground station, and a cloud server. The ground station is configured to determine an aerial photography parameter for indicating an aerial photography state of the UAV based on a user operation and transmit the aerial photography parameter to the UAV. The UAV is configured to receive the aerial photography parameter transmitted by the ground station; fly based on the aerial photography parameter and control an imaging device carried by the UAV to acquire aerial images during a flight; and transmit the aerial images to the cloud server. The cloud server is configured to receive the aerial images and generate a 3D model of a target area based on the aerial images.