271 results about "Height map" patented technology

Systems and methods are provided for displaying data, such as 3D models, having spatial coordinates. In one aspect, a height map and color map are generated from the data. In another aspect, material classification is applied to surfaces within a 3D model. Based on the 3D model, the height map, the color map, and the material classification, haptic responses are generated on a haptic device. In another aspect, a 3D user interface (UI) data model comprising model definitions is derived from the 3D models. The 3D model is updated with video data. In another aspect, user controls are provided to navigate a point of view through the 3D model to determine which portions of the 3D model are displayed.

This invention relates to one mobile robot 3D sensor method, which comprises steps of environment information acquiring, environment information self adapting filter, environment coordinate exchanging and 3D sensing. This invention gets robot environment information through one sense platform composed of 2D laser radar, rotation bench and step motor. This invention also provides one dynamic self-adaptive filter to realize dynamic filter noise removing aim for environment information interference.

The invention provides a level sensor configured to determine a height level of a surface of a substrate, comprising a detection unit arranged to receive a measurement beam after reflection on the substrate, wherein the detection unit comprises an array of detection elements, wherein each detection element is arranged to receive a part of the measurement beam reflected on a measurement subarea of the measurement area, and is configured to provide a measurement signal based on the part of the measurement beam received by the respective detection element, and wherein the processing unit is configured to calculate, in dependence of a selected resolution at the measurement subarea, a height level of the measurement subarea, or to calculate a height level of a combination of multiple measurement subareas.

Methods and apparatus for detecting obstacles in the flight path of an air vehicle are described. The air vehicle utilizes a radar altimeter incorporating a forward looking antenna and an electronic digital elevation map to provide precision terrain aided navigation. The method comprises determining a position of the air vehicle on the digital elevation map, selecting an area of the digital elevation map in the flight path of the air vehicle, based at least in part on the determined air vehicle position, and scanning the terrain representing the selected map area with the forward looking antenna. The method also comprises combining the digital elevation map data for the selected map area with radar return data for the scanned, selected area and displaying the combined data to provide a representation of the terrain and obstacles in the forward flight path of the air vehicle.

The invention discloses a method for selecting an autonomous landing area of an unmanned aerial vehicle (UAV) under a complex environment based on visual SLAM, which is used for solving the technical problem of poor practicability of the existing UAV landing area control method. According to the technical solution, the method comprises the steps of obtaining an image sequence via an overlooking monocular camera carried by a UAV mobile platform, calculating the pose of the UAV in real time via an SLAM algorithm and establishing a sparse point cloud map, and meshing the point cloud map to construct a two-dimensional grid height map; then dividing the grid map according to the height in combination with a Means shift image segmentation algorithm, and finally screening an area that is farthest from a potential obstacle and is suitable for landing of the UVA according to the landing height requirement. According to the method, the pose of the UAV is calculated by adopting the monocular visual SLAM and estimated in real time, the two-dimensional grid height map is constructed, and the area suitable for landing of the UVA is screened. The method, which does not depend on a landmark, has good practicability.

Reconstructing the shape of the surface of an object in greater than two dimensions is performed using a noise-tolerant reconstruction process and/or a multi-resolution reconstruction process. The noise-tolerant reconstruction process can be a Bayesian reconstruction process that adds noise information representing the noise distribution in optical image(s) of the object to surface gradient information estimated from the images to determine surface height information that defines the shape of the surface of the object in greater than two dimensions. In the multi-resolution reconstruction process, for each resolution of the image, the surface gradient information is estimated and the surface height information is calculated using the estimated surface gradient information. To obtain the final surface height map, the surface height information from each resolution is combined to reconstruct the shape of the surface of the object in greater than two dimensions. The multi-resolution reconstruction process can be used with the Bayesian reconstruction process or with another decomposition process, such as a wavelet decomposition process.

A method, system, and computer-readable storage medium are disclosed for simulation of an erodible tip. A brush tool representing an erodible media is modeled as a height map. Information is collected about a user manipulation of a stylus representing a stroke made on a virtual canvas with the brush tool. A mark to be made on the virtual canvas is determined dependent on the brush tool model and the collected information. The determined mark is rendered. A change in the height map of the brush tool due to the stroke is determined dependent on the brush tool model and the collected information. One or more subsequent marks are rendered in response to manipulation of the brush tool dependent on the determined change in the height map.

The invention relates to a non-contact measuring method, in particular to visual measuring method of a stockpile in a large-scale stock ground. The method comprises the following steps of: (1) constructing a visual measuring system of stock ground; (2) mounting a binocular vision subsystem; (3) establishing a geometric model of a CCD (Charge Coupled Device) camera; (4) calibrating the parameters of the CCD camera; (5) collecting images; (6) processing the images; (7) searching and matching angular points; (8) confirming the three-dimensional coordinate values of an object point; and (9) interpolating a curve and establishing a height map in a world coordinate system; and (10) measuring the volume. The visual measuring method of the invention automatically eliminates the image distortion caused by a wide-angle lens, can automatically and accurately match the angular points of a left view and a right view, automatically generates the three-dimensional space coordinates of the object point by utilizing an image data conversion relation, optimizes the three-dimensional angular point distribution and constructs the height map of the world coordinate system so that the volume a geometrical irregular stockpile can be simply, intuitively and accurately calculate.

The invention discloses a formation fracture space reconstruction method based on rock core measure. The formation fracture space reconstruction method based on the rock core measure comprises the following steps: step 1 of selecting fracture rock core, step 2 of scanning and processing a fracture rock sample through non-contact type measure system and obtaining a surface chart, step 3 of acquiring form data through a three-dimensional point cloud data reverse engineering software, step 4 of exporting the form data, generating a point cloud file, step 5 of generating the point cloud file to a fracture space grid chart by using a matrix laboratory ( MATLAB), step 6 of drawing contour lines, step 7 of processing and generating a space height map, and step 8 of conducting necessary rotation and move to the space height map, and obtaining a reconstruction fracture space model. The formation fracture space reconstruction method based on the rock core measure has the advantages that the height of the reconstruction fracture space model acquired through reconstruction is the same as an actual fracture form, precision is improved significantly, feasibility and practicability are achieved, digital simulation research of mesomechanics can be well satisfied, and necessary reference for further research of reservoir network fracture plane, output volume prediction and pressure sensitivity test is served.

The invention discloses an accelerated terrain rendering method based on a graphics processor. Not only a problem of a T-shaped crack occurring in a level of detail (LOD) rendering process can be solved effectively, but also operation resource of a central processing unit (CPU) is saved, and a processing performance of the CPU is improved due to the fact that calculation is based on the graphics processor. By means of the method, a large-scale terrain can be rendered on a computer only supporting Direct three-dimensional (3D) 9 in high quality and high performance mode, and the method can be widely applied to 3D games and virtual reality application programs. The accelerated terrain rendering method includes the following steps: dividing an original terrain image into a plurality of terrain blocks with same area; using LOD terrain rendering arithmetic, and building different LOD-level vertex buffer and index buffer; using a quad-tree to organize the whole original terrain, each leaf node corresponds to a terrain block; rendering the terrain; using a graphics processing unit (GPU) to conduct Vertex Shader programming, obtaining height value of a terrain block vertex from a height map by using a vertex texture sampling function; and modifying the height value of a vertex.

The invention discloses a traffic image semantic segmentation method based on a multi-feature map. The method comprises the following steps: obtaining a multi-feature map training sample: a disparitymap, a height map and an angle map; constructing a network model, training the network model, inputting the trained network model and a six-channel test image into the network model, outputting a probability value that each pixel belongs to each object category in the six-channel image via a multi-class classifier softmax layer, then predicting the object category to which each pixel in the six-channel image belongs, and finally outputting an image semantic segmentation map. By adoption of the traffic image semantic segmentation method based on the multi-feature map provided by the invention,the fusion of a color image with a depth map, the height map and the angle map, more feature information of the image can be obtained, and it is conducive to understanding the road traffic scene and improving the semantic segmentation accuracy. According to the traffic image semantic segmentation method based on the multi-feature map provided by the invention, by means of the learned effective features, the object category to which each pixel in the image belongs can be predicted, and the image semantic segmentation map is output.

The invention discloses a method of restoring a three-dimensional human body posture from an unmarked monocular image in combination with a height map. The method comprises the following steps: 1) a color image and a height image are used for training to obtain a deep convolutional network-based two-dimensional joint point recognition model; 2) a video frame image sequence and a camera parameter are inputted, and a height map corresponding to each frame of image is calculated; 3) the video frame image and the height map obtained in the second step are inputted, and the two-dimensional joint point recognition model obtained through training the first step is used to obtain two-dimensional joint point coordinates of a human body in each frame of image; and 4) the two-dimensional joint point coordinates obtained in the third step are inputted, and the human body three-dimensional posture is restored according to an optimization model. During the two-dimensional joint point recognition process, the color image and the height image are used integrally, and the two-dimensional joint point recognition accuracy is improved; and time sequence consistency constraints are added to the optimization model which can restore the three-dimensional human body posture from the two-dimensional joint point, and thus the restored three-dimensional human body posture is closer to the real human body posture.

A method and apparatus for using a predetermined portion of terrain elevation maps in a database for aiding in computing a three-dimensional position of a wireless station. Instead of using the entire terrain model of the earth or an entire country, the database consists of an incomplete model, which includes only the most populous areas or specific regions. This reduces the size of the information in the database, which in turn reduces the amount of time to compute the positions of the wireless device.

A lithographic apparatus applies a pattern onto a substrate using an optical projection system. The apparatus includes an optical level sensor and an associated processor for obtaining a height map of the substrate surface prior to applying the pattern. A controller uses the height map to control focusing with respect to the projection system when applying the pattern. The processor is further arranged to use information relating to processing previously applied to the substrate to define at least first and second regions of the substrate and to vary the manner in which the measurement signals are used to control the focusing, between the first and second regions. For example, an algorithm to calculate height values from optical measurement signals can be varied according to differences in known structure and/or materials. Measurements from certain regions can be selectively excluded from calculation of the height map and/or from use in the focusing.

Methods and apparatuses (including systems and devices), including computer-implemented methods for segmenting, correcting and/or modifying a three-dimensional (3D) model of a subject's oral cavity to determine individual components such as teeth, gingiva, tongue, palate, etc., that may be selective and/or collectively digitally manipulated. In some implementations, artificial intelligence uses libraries of labeled 2D images and 3D dental models to learn how to segment a 3D dental model of a subject's oral cavity using 2D images, height map and/or other data and projection values that relate the 2D images to the 3D model. As noted herein, the dental classes can include a variety of intra-oral and extra-oral objects and can be represented as binary values, discrete values, a continuum of height map data, etc. In some implementations, several dental classes are predicted concurrently.

The invention discloses a DEM super-resolution method based on a convolutional neural network. The method includes following steps: (1) obtaining a super-resolution convolutional neural network through training according to low-resolution image data and high-resolution image data corresponding to each other in advance; (2) extending to-be-processed low-resolution DEM data by employing an interpolation method, and obtaining quasi-high-resolution DEM data having the same scale with expected high-resolution DEM data; (3) obtaining a gradient map of the quasi-high-resolution DEM data by employing en edge extraction operator; (4) inputting the gradient map to the super-resolution convolutional neural network, and obtaining an estimation gradient map of the high-resolution DEM data; and (5) reconstructing a height map of the high-resolution DEM based on constraint of the estimation gradient map and the to-be-processed low-resolution DEM data. According to the super-resolution method, the robustness is high, and the precision of the reconstruction result is high.

A sample, which has a mesa portion having a pattern thereon, is placed on a Z table. Light is irradiated to the mesa portion through an optical system and light reflected by the mesa portion is received to measure a height of the mesa portion. A height map of the mesa portion is created based on a height of a corner position. A height using the height map is corrected based on a deviation of a measured value from a target value, and a temporal variation of a focal position of light irradiated to the mesa portion. An optical image of the pattern is obtained while controlling the Z table based on the corrected height of the mesa portion. The optical image is compared with a reference image and a defect is determined when a difference value between the optical image and reference image is more than a predetermined threshold value.

The invention relates to a three-dimensional point cloud model data compression method based on four-side patch segmentation. The method comprises the following steps of (1), segmenting the surface ofan input point cloud model to a plurality of quadrangular patches; (2), successively performing parameterization and resampling processing on the quadrangular patches, and obtaining two-dimensional image data; performing regular resampling on the patches, wherein after resampling, each patch can be described by a height picture, thereby converting three-dimensional data to two-dimensional image data and reducing data volume; (3), performing wavelet coding on the two-dimensional image data by means of an EZW algorithm, and realizing progressive compression of a three-dimensional point cloud model; and (4), performing decoding and model reconstruction. An existing OT algorithm has a remarkable sawtooth phenomenon on the condition of low bit rate, and the method according to the invention well settles the defect. On the condition of the same bit rate, the method according to the invention realizes a better visual effect. The method of the invention increases three-dimensional model datacompression rate.