208 results about "Point model" patented technology

A system, method and computer program product is provided for interactive user navigation in a real-time 3D simulation. An assembly builder permits a user to build customized physics-based assemblies for user navigation in a variety of virtual environments. These assemblies are stored in a library and are then accessed by a navigation run-time module that runs in conjunction with, or as a part of, a visual run-time application. The navigation run-time module receives high-level user goal requests via a simple and intuitive user interface, converts them into a series of tasks, and then selects the appropriate assembly or assemblies to perform each task. As a result, complex navigation may be achieved. Once selected, an assembly provides a physics-based eye-point model for user navigation. Collisions between the assembly and objects in the simulation are resolved using a real-time physics engine, thus ensuring smooth, cinematic-style eye-point modeling in addition to real-time control.

The invention discloses a roadside parking space detection device based on computer vision, comprising an omnidirectional vision sensor and a microprocessor, wherein the omnidirectional vision sensor is installed at the roadside with parking spaces; the microprocessor is used for analyzing the parking space state according to the data of a parking space video shot by the omnidirectional vision sensor; and the microprocessor comprises an omnidirectional image acquisition unit, a parking space customizing module, a parking space state detection module based on a sampling point model, and a parking space state information releasing module. The invention provides the roadside parking space detection device which is based on the computer vision, has the advantages of wide detection range, high detection precision, good detection instantaneity, high cost performance, strong environmental adaptation capability and good expandability and sustainable development, is convenient to implement and maintain and is convenient to realize on an embedded system.

The invention discloses a method for quickly measuring a blade of a large-sized water turbine, which is characterized by comprising the following steps: firstly, sticking a mark point to the surface of the blade, then shooting a group of photos from different angles as measured primary data, and inputting the data to a computer to carry out analytic processing; by carrying out image detection for the group of photos in a measurement software, identifying the mark point in each photo and positioning the center of the mark point, and matching the mark points with the same name; finally, reconstructing a three-dimensional coordinate of corresponding object points according to a plurality of two-dimensional coordinates of the mark points, fitting a sparse framework model of a target by the reconstructed three-dimensional mark points, then scanning the surface of the blade block by block by using a binocular grating scanning method to acquire a local dense point cloud, and aligning the dense point cloud to an overall coordinate system according to the local mark points to acquire a dense point model of the blade; and by comparing the dense point model with a CAD designed model after aligning, calculating a three-dimensional processing error of the surface of a workpiece.

The invention discloses a travelling robot positioning system based on a single camera. In the system, a point model is adopted for representing an environmental model, an off-line map is calibrated, an action model and an observation model are established for carrying out position updating and road sign calibration, Monte Carto particle filter technology is adopted, particle swarm distribution with weights is adopted for representing robot pose estimation, the weights and the distribution of particles are updated through road sign matching processing, field particle distribution is rasterized, and a sub-region with maximal particle density is selected for positioning the robot. As an independent platform, the system greatly improves the map calibration technology on the environmental model, has great flexibility on the identification of ground line sections, and just needs re-calibration but not needs model re-establishment after environment change. The model reduces the matching complexity in visual processing and improves calculation efficiency. The Monte Carlo localization algorithm is expanded on the information integration processing technology, thus ensuring the real-time property and robustness of the system.

The invention discloses a unmanned aerial vehicle (UAV) path determination method and apparatus for reconstructing a three-dimensional model, the method comprising the steps of: constructing a three-dimensional point model forming an outline of a captured building; determining a photographing points of a flight path of the UAV around the building so that a camera on the UAV can capture a corresponding point set covering the three-dimensional point model at each photographing point and the overlap ratio of the point sets captured by the camera at adjacent photographing points is greater than an overlap ratio threshold; instructing the UAV to fly along the flight path and instructing the camera to photograph the building at corresponding photographing points. The method can calculate minimum photographing point sets satisfying a three-dimensional reconstruction requirement just by acquiring the height and the two-dimensional orthograph of a three-dimensional reconstructed target, so as to provide guidance for a three-dimensional reconstruction data acquisition process, to ensure that the acquired images meet the three-dimensional reconstruction requirement, to avoid the collection of redundant image information, and to improve the efficiency of the three-dimensional reconstruction process.

The invention provides a question-answering system combining emotion recognition and output. The question-answering system comprises an input module, a denoising module, an emotion analysis module, an emotion decision module and an output module. The input module is used for inputting user questioning information and user parameter information and converting the user questioning information and the user parameter information into standard text formatting information. The denoising module is used for carrying out denoising and module structuralization processing on the text formatting information. The emotion analysis module is used for building an emotion feature point model and extracting emotion feature points from the user questioning information through the emotion feature point model. The emotion decision module is used for building an emotion decision model and judging the current emotion of a user and the current circumstance where the user is located based on the emotion feature points of the user through combinatorial computing by combining the records and habits of the user. The output module is used for outputting a corresponding result according to the current emotion of the user. The emotion information of the user is combined, the user intention is speculated more accurately, intimate answers are given according to the actual situation of the user, and user experience is greatly promoted.

A computer system and method of simulating the behavior of an oil and gas reservoir including changes in the margins of frangible solids. A system of equations including state equations such as momentum, and conservation laws such as mass conservation and volume fraction continuity, are defined and discretized for at least two phases in a modeled volume, one of which corresponds to frangible material. A material point model technique for numerically solving the system of discretized equations, to derive fluid flow at each of a plurality of mesh nodes in the modeled volume, and the velocity of at each of a plurality of particles representing the frangible material in the modeled volume. A time-splitting technique improves the computational efficiency of the simulation while maintaining accuracy on the deformation scale. The method can be applied to derive accurate upscaled model equations for larger volume scale simulations.

The invention relates to a ship-navigation buoy collision risk degree estimation method based on an automatic identification system (AIS), and belongs to the technical field of navigation channels. The ship-navigation buoy collision risk degree estimation method comprises the steps that a feature point model of a ship is built by obtaining static information in AIS information of the underway ship, and according to the feature point model of the ship, real-time and historical ship positions of the ship, and the heading, the ship position, the heading and the navigation path of ship feature points are predicted; and according to prediction information of the feature point model of the ship and position data of a navigation buoy and the ship, the nearest meeting distance between the navigation buoy and the feature point model of the ship and the traveling distance needed by the ship for reaching the meeting point are calculated, the collision risk degree is estimated in real time according to a collision risk degree estimation model, and the collision risk degree threshold value is calculated in real time according to a collision risk degree threshold value calculating model. Throughthe judging result, a camera on the navigation buoy can be triggered to take photos, and warning reminding can be conducted on the ship; and according to the ship-navigation buoy collision risk degree estimation method, distance measurement sensors or other sensors do not need to be newly additionally arranged, and then whether the ship and the navigation buoy collide or not can be effectively prejudged.

The invention discloses a mark point automatic registration method based on model matching. The method comprises the following steps of (1)obtaining image data containing mark points; (2) constructing a mark point model; (3) reading in the obtained image data, conducting anisotropic diffusion filtering on images, and automatically extracting a skin three-dimensional grid from the images; (4) adopting an ICP algorithm to be matched with the mark point model and the skin three-dimensional grid, and obtaining the coordinate of the center of each mark point on the skin three-dimensional grid in an image space coordinate system; (5) adopting the ICP algorithm to be matched with the center of each mark point of the image space and the center of each mark point of the actual space, obtaining a rotating matrix R and a translational vector quantity T between the image space coordinate system and the actual space coordinate system, and completing registration of the mark points. According to the mark point registration method, the multiple mark points can be rapidly registered, the obtained rotating matrix R and the obtained translational vector quantity T of the image coordinate system and the actual coordinate system are more accurate, manual interference is reduced, the precision of the registration of the mark points is improved, and the mark point automatic registration method has good robustness.

The invention discloses a precession target micro-Doppler extracting method based on instant frequency modulation rate estimation. The precession target micro-Doppler extracting method based on instant frequency modulation rate estimation comprises the steps that (1) an equivalent scattering point model of a spatial precession conical target is established, echo signals of the conical target are received by a radar, echo sequences are obtained from the echo signals by using the equivalent scattering point model; (2) frequency modulation rates of the echo sequences are estimated with a relaxation demodulation line frequency modulation method; (3) the frequency modulation rates of the echo sequences are processed through a random sampling consistency algorithm, and P frequency modulation rate curves are obtained; (4) integral operation is carried out on the P frequency modulation rate curves respectively, and P instant micro-Doppler frequency estimation curves are obtained. According to the precession target micro-Doppler extracting method based on instant frequency modulation, high estimation accuracy can be obtained under the situation of the lower signal to noise ratio. The precession target micro-Doppler extracting method based on instant frequency modulation can be applied to analysis of the micro-Doppler frequency of the spatial precession conical target.

The invention provides a method for establishing a MicroBlog user interest inference model. The method comprises an interest label calculation model, an interest model used for MicroBlog text content extraction and a blogger interest point model used for blogger social relationship extraction, and the three models are fused through a model fusion strategy to obtain the final MicroBlog user interest inference model. The method combines personal information, MicroBlog contents and the social relationship, adopts a USER strategy that all MicroBlog contents of the same blogger are mixed by aiming at the sparsity problem of the MicroBlog contents, mines an implicit theme of the MicroBlog by a LPA (Label propagation algorithm), puts forwards a social label propagation algorithm on the basis of a network formed by blogger attention, and calculates influence on the blogger by various interest labels. The method exhibits good identification capability and information filtering capability, and filters false information to identify false bloggers before recommendation is carried out, so that the recommendation quality and accuracy of a recommendation system can be improved, and better experience is brought for the blogger.

The invention discloses a method for expressing the processing of roads on a map. The method comprises the following steps: 1, importing road data of a map; 2, classifying roads; 3, coding the map vector data of the roads and giving the polygonal expression, particularly, creating three surface polygon models of road polygons, crossing polygons and road isolation zone polygons, two point models ofcrossing nodes and road blind end nodes and a line model of road center line, and coding the features of each road polygon model, creating an attribute table for the three major road models of points, lines and surfaces, and generating the map vector date in a compressed format at the same time; and 4, decoding and displaying the database. The invention has the advantages of simple method, low data redundancy, strong data analysis function and high graphic transmission speed, and meanwhile, the invention further has the advantages of high road classification accuracy and low cost. The invention can fully present the complicated urban road system through the different classification of surface road elements and the creation of road models.

The invention relates to a single sign-on method in a point to point mode. Being different from the existing single sign-on method based on a customer server mode, the method manages the single sign-on life cycle of a customer by using valid period of certificate of the customer, and the customer can sign on for a plurality of times with single certification. The method completes the cross-certification of an application system and an identity certification server; the shared encryption key of communication parties is initialized, and a safe channel between the customer and the application system is established. Through the the identity certification server and the cross-certification of the application system, any application system can independently carry out identity certification, thus weakening the status of a central identity certification server, avoiding the defect of single-point failure in traditional customer/ service mode and being characterized by low cost for system operation, high efficiency and good safety performance.

A method for producing a 3D facial animation using a single facial video stream, includes producing a representative joint focused on a major expression producing element in a 3D standard facial model, producing a statistical feature-point model of various facial expressions of different people in the 3D standard facial model, moving each feature-point of the statistical feature-point model by tracking a change in facial expressions of the video stream, calculating a transformation coefficient of the representative joint corresponding to a variation of the feature-point of the 3D standard facial model, and producing a 3D facial animation by applying the calculated transformation coefficient to transform the representative joint.

The invention belongs to the technical field of image processing and particularly relates to a texture mapping method based on triangular mesh simplification. The texture mapping method comprises the following steps: simplifying a triangular network model and establishing a spring-mass-point model; parameterizing the spring-mass-point model to a final position of a rectangular region; by utilizing a process of simplifying the triangular network model, calculating an initial position of a deleted point in the parameterized rectangular region to obtain positions of all vertexes of an initial model in the parameterized rectangular region; parameterizing the initial model to establish the spring-mass-point model; fixing the boundary vertex and triggering inner point iteration until the position of an inner point is balanced to obtain a spring-mass-point model revised parameterized coordinate; and carrying out normalization processing to obtain a texture coordinate of a grid vertex, and carrying out texture mapping. According to the method, the texture coordinate of each triangular network grid vertex does not need to be solved and texture mapping can be directly carried out; the time complexity of the method can be reduced to the great extent and the time performance is improved.

The invention discloses an intelligent extraction method and device for table cells of financial statements. The intelligent extraction method for table cells of financial statements includes the following steps: downloading a target table image of financial statements from a server; performing image tilt correction on the target table image; using a table outline border target detection model based on deep learning to detect the table area of the target table image, and obtaining a table area image; on the obtained table area image, using a table intersection point model based on depth learning to locate the table intersection points; and performing ordering, screening and regrouping on the coordinates of the table intersection points so as to obtain each table cell. The scheme of the intelligent extraction method and device for table cells of financial statements can accurately and quickly extract the table cells of financial statements, uses algorithms to realize accurate identification, can greatly improve the work efficiency of checking financial statements, can reduce the labor cost, and can reduce the error rate.

Systems, methods and articles that provide dynamic calibration of eye tracking systems for wearable heads-up displays (WHUDs). The eye tracking system may determine a user's gaze location on a display of the WHUD utilizing a calibration point model that includes a plurality of calibration points. During regular use of the WHUD by the user, the calibration point model may be dynamically updated based on the user's interaction with user interface (UI) elements presented on the display. The UI elements may be specifically designed (e.g., shaped, positioned, displaced) to provide in-use and on-going dynamic calibration of the eye tracking system, which in at least some implementations may be unnoticeable to the user.

The invention discloses a three-dimensional reconstruction method and system in intelligent transportation. The three-dimensional reconstruction method comprises the steps of obtaining information of a detection scene, achieving extraction and dynamic tracking of target feature points in the detection scene, achieving feature point automatic completion and conducting three-dimensional reconstruction on targets through a distribution reconstruction algorithm. The three-dimensional reconstruction method comprises the following steps of S101, carrying out camera calibration, S102, synchronously obtaining original video images with scene depth information, S103, tracking feature points of the targets in a video scene, S104, selecting video key frames, S105, reconstructing the selected frames, S106, packaging subsets, and S107, obtaining a final three-dimensional model. According to the three-dimensional reconstruction method and system in intelligent transportation, an improved KLT tracking algorithm is adopted, a feature point model is optimized, and tracking efficiency is improved; the key frames are extracted to serve as the subsets, and the subsets are reconstructed and finally are merged, so that the problems that the obtained video frames are relatively short, and depth obtaining of image information is influenced by tracking losing of feature points in the scene, faults and the like are solved.

The invention discloses a face pose estimation method, device and apparatus, and belongs to the technical field of image recognition. The method comprises the following steps: reading a picture to beestimated; according to the first model, identifying face feature points of a picture to be estimated; according to the second model and the human face feature points, identifying the human face waiting attitude angle of the picture to be estimated. The invention can directly generate real-time face posture angle data and continuously output predicted value, which can be widely used in the application field of real-time and continuously judging face posture. The method can generate training and testing data sets of face posture, avoid manual labeling and improve data set accuracy. At the sametime, a new loss function is proposed for the convolution neural network feature point model in the first model. The new loss function is more conducive to computer operation and speeds up the computational efficiency of the model.

The invention relates to a time change and disordered multi-image-based four-dimensional modeling method, which is technically characterized by comprising the following steps: automatically extracting characteristic points for each image from which thousands of characteristic points can be extracted generally according to different resolutions by a sift algorithm, partitioning a three-dimensional point set to acquire separate buildings, calculating the depth information of each building on the image, and performing shading judgment by using the size of the depth. By carefully observing the change rule of the city, the buildings are integrally built or detached, so the buildings are used as basic units. The method has the advantage of improving the accuracy of image time sequence deduction by using characteristic descriptors to automatically match the characteristic points among the images and further abstracting a primary three-dimensional point model. Meanwhile, thousands of three-dimensions are abstracted into a plurality of buildings so as to greatly improve the efficiency of local search algorithm.

The invention belongs to the field of unmanned aerial vehicle cooperative information processing technologies and discloses an unmanned aerial vehicle cluster collaborative obstacle avoidance-reconstruction processing method. According to the method, the force constructing rules of a traditional AP method are improved; the unmanned aerial vehicle cluster of a mass point model is designed to generate the control law of standard configurations; the magnitude and direction of a control force are controlled through bijection transformation; and a general cluster configuration is generated, and thereconstruction control of the configuration is realized. The improved AP method has the advantages of strong global optimization capacity, low requirements for optimization problems, parallel mechanism, and the like. The algorithm of the invention has higher flexibility. Each unmanned aerial vehicle only needs to sense adjacent environment information to generate its own virtual force, has the characteristics of easiness in expansibility and distributedness; and when the improved algorithm is adopted to plan routes, a calculation process can be simplified, a judgment cycle can be shortened, and therefore, the cost of the implementation of the method of the invention can be decreased.

Disclosed is a facility tomato supplemental lighting adjustment and control method based on a growth model. Three growth stages of the tomato seedling stage, the flowering stage and the fruiting stage are selected, the tomato leaf net photosynthetic rates at different temperatures and with concentrations of carbon dioxide and light intensities are measured, corresponding light saturation points at different temperatures and with concentrations of carbon dioxide are obtained, and a tomato optimized light saturation point model is built; the temperature, the concentration of carbon dioxide and the light intensity in the tomato growth environment are monitored in real time, whether the current light intensity is at the light saturation point corresponding to the current temperature and the current concentration of carbon dioxide is judged according to the growth stage of tomatoes and the tomato optimized light saturation point model, and if not, an LED light source is used for light supplementation until the light intensity reaches the light saturation point. The invention further provides a facility tomato supplemental lighting adjustment and control system based on the growth model, intelligent and quantitative light supplementation of the tomatoes is achieved, and great significance is brought to energy-saving and high-efficiency production of the facility tomatoes.