1137 results about "Space model" patented technology

An image generating apparatus comprising: a camera or a plurality of cameras; space reconstructing means for mapping the input image from said camera, into a predetermined space model of a predetermined three-dimensional space; point-of-view converting means of synthesizing an image viewed from an arbitrary virtual point of view in said predetermined three-dimensional space by referencing to said space data mapped by said space reconstructing means; and displaying means of displaying the image converted by said point-of-view converting means.

A face detection and / or detection method includes acquiring a digital color image. An active appearance model (AAM) is applied including an interchannel-decorrelated color space. One or more parameters of the model are matched to the image. Face detection results based on the matching and / or different results incorporating the face detection result are communicated.

System and method for the indexing and retrieval of semantically annotated information units from a collection of semantically annotated indexed information units in response to a query using an ontology-based IR model. The retrieval method comprises: receiving a semantically annotated query with semantic annotations to individuals or classes within a determined populated base ontology; embedding, as a set of weighted-mentions to individuals or classes within the populated base ontology, the semantically annotated query in a semantic representation space of an ontology-based metric space IR model; obtaining the representation in the semantic representation space for every indexed information unit; computing the Hausdorff distance between the space representation of the query and the space representation of all the indexed information units of the collection; retrieving and ranking, the relevant information units based on the computed Hausdorff distance.

The present invention relates to a method and apparatus for creating a 3D image of vehicle surroundings. The method according to the present invention includes the steps of: mapping images captured by a plurality of cameras installed in a vehicle to a virtual plane defined by a 3-dimensional space model having a container shape with a flat bottom surface and a top surface which has an increasing radius; and creating a view image having a viewpoint of a virtual camera by using the image mapped to the virtual plane. According to the present invention, it is advantageous that an image of vehicle surroundings including surrounding obstacles can be expressed naturally and three-dimensionally. It is also advantageous that an optimal image of vehicle surroundings can be provided by changing the virtual viewpoint according to a traveling state of the vehicle. There is also the advantage that a user can conveniently adjust the viewpoint of the virtual camera.

The image generation device includes distance calculation means for calculating a distance between a space model and an imaging device arrangement object model which is a model such as a vehicle having a camera mounted, according to viewpoint conversion image data generated by viewpoint conversion means, captured image data representing captured image, a space model, or mapped space data. When displaying an image viewed from an arbitrary virtual viewpoint in the 3D space, the image display format is changed according to the distance calculated by the distance calculation means. When displaying a monitoring object such as a vicinity of a vehicle, a shop, a house or a city as an image viewed from an arbitrary virtual viewpoint in the 3D space, it is possible to display the monitoring object in such a manner that the relationship between the vehicle and the image of the monitoring object can be understood intuitionally.

The invention discloses an underground space high-precision positioning method based on laser scanning and sequence encoded graphics. Aiming at the rapid high-precision positioning, orientation, altitude determination and navigation of moving targets in a GPS signal-free underground well of a mine, the method can make the breakthrough in key directions from the design, decoding and optimized layout of the encoded graphics, the economical and rapid acquisition of a fine and accurate road network-a three-dimensional well network space model consisting of underground tunnels of mine, a high-precision positioning algorithm of the moving targets in well restraint spaces (precise resolving of position, direction, altitude parameters), a three-dimensional well network space matching algorithm, athree-dimensional navigation technology to a final navigation platform and terminal control system, and the like, thus key technologies for underground rapid high-precision positioning and navigationas well as software and hardware systems are formed to eventually achieve the leaping-development of a underground unmanned mining technology for the mine in our country. Besides, the method disclosed in the invention can also meet the application demands of large urban underground space, deep and long traffic tunnel, large grotto, large building interior, large overpass and subway space on the rapid high-precision positioning and navigation of the moving targets, thereby pushing forward the development of the underground space positioning technology in our country.

The invention discloses a method for mining data in construction regulation field based on associative regulation mining technology; 1. a construction regulation text vector space model is generated, 2. a construction regulation data vector space model is generated, 3. the construction regulation data vector space model is subject transposition to generate a construction regulation data feature vector space model, namely, a frequent feature set is generated, and 4. construction regulation data association degree is calculated and an association rule is output. The method can mine the data in construction regulation field, provides higher recall ratio for a user inquiring data, recommends associative query contents, and solves the technical problem that the existing association analysis technologies can not carry out association analysis on outlier data.

The invention discloses a method for constructing a full-space three-dimensional digital earth model. The method includes that an ellipsoid earth space mathematical model is constructed based on a center of gravity control system (CGCS) 2000 China geodetic coordinate system; an earth surface dissection network is generated based on a fictitious graticule; an earth surface digital elevation model is generated in an insertion mode; a geometric structure module of earth space inner and outer ring layers is fitted by interpolations; a three-dimensional body element mesh of the earth space inner and outer ring layers is generated based in geological cells; an attribute element three-dimensional distribution model of the earth space inner and outer ring layers is fitted by the interpolations; a geographical coordinate is converted into a geocentric space three-dimensional rectangular coordinate; an earth space model multi-scale expression mechanism based on level of detail (LOD) is constructed; three-dimensional visualization is performed; earth space positions are checked; and three-dimensional analysis is performed. According to the method, the automaticity and the adaptability are high, and an earth space solid model containing the inner and outer ring layers can be rapidly and automatically reconstructed in three-dimensional space to be displayed on a computer display screen in a three-dimensional visualization mode to support space analysis of various professionals.

Disclosed is a rolling bearing remaining life prediction method based on feature fusion and particle filtering. According to an index calculation process, firstly, original features are extracted from bearing vibration signals, the extracted original features are clustered by the adoption of a relevance clustering method, then, one typical feature is selected from each cluster to form optimal feature sets, and finally the feature sets are fused by the adoption of a weight fusion method into a final recession index. According to a life prediction process, firstly, smoothing and resampling are carried out on the recession index, the time interval is adjusted to be an expected value, state-space model initial parameters are calculated by the adoption of least square fitting, then, model parameters are updated in real time according to new observation data, and finally the remaining life of a bearing can be predicted. According to the rolling bearing remaining life prediction method based on feature fusion and particle filtering, the difference between the life prediction result and a true value is small, and the application effect is good.

The method for the identifying of multiple input, multiple output (MIMO) Hammerstein models that includes modeling of the linear dynamic part of a Hammerstein model with a state-space model, and modeling the nonlinear part of the Hammerstein model with a radial basis function neural network (RBFNN).

The contamination level estimation method for high voltage insulators collects samples of naturally contaminated insulators and builds an image data set for the collected insulators. Flashover voltages of several insulators samples are measured. ESDD levels of the collected insulators are estimated. Images are input to image processing algorithms to extract representative features. The images are segmented. Transforming the image from RGB color space into grayscale model excludes the background from the image. Subsequently, the segmented images are transferred back to RGB color space model using matrix manipulation. Since contaminants on the insulator surface affect the color of the insulator, the segmented image is transformed from RGB to HSV color space which is used for extracting statistical and linear algebraic features from the hue image. A trained artificial neural network correlates the extracted features to the contamination levels enabling testing of other contaminated insulators.

A method of using fisheye image to generate stereoscopic panorama includes shooting out a numbers of fisheye image by fisheye camera according to specified sequence, confirming character point air at overlapped region of adjacent images and setting-up stereoscopic space model as per obtained matching point pair, calculating out position of original image on stereoscopic space and resampling original fisheye image according to calculated out parameter in order to generate out stereoscopic panorama.

A probabilistic digital signal processor using data from multiple instruments is described. Initial probability distribution functions are input to a dynamic state-space model, which operates on state and / or model probability distribution functions to generate a prior probability distribution function, which is input to a probabilistic updater. The probabilistic updater integrates sensor data from multiple instruments with the prior to generate a posterior probability distribution function passed (1) to a probabilistic sampler, which estimates one or more parameters using the posterior, which is output or re-sampled in an iterative algorithm or (2) iteratively to the dynamic state-space model. For example, the probabilistic processor operates on fused data using a physical model, where the data originates from a mechanical system or a medical meter or instrument, such as an electrocardiogram or pulse oximeter to generate new parameter information and / or enhanced parameter information.

The invention discloses an active disturbance rejection control robust guaranteed cost design and parameter setting method. The method includes steps: 1, establishing an uncertain linear system state space model; 2, establishing a full-dimensional extension state observer, to be more specific, establishing a system extension state space model, and establishing the full-dimensional extension state observer; 3, establishing a state feedback control structure; 4, analyzing system robust stability and robust performance upper bound; 5, controlling system parameter optimization. The method is applicable to active disturbance rejection controllers of minimum phase systems and non-minimum phase systems, and optimal control performances under given performance indexes of controller systems can be guaranteed under uncertainty conditions.

The invention provides an uncertain mechanical arm fixed time track following control method with input saturation, which can overcome influences of mechanical arm control input saturation effect anduncertainty, and improves robustness of a system. The method comprises the following steps: establishing a kinetic equation of an n-freedom rotary joint rigid mechanical arm system with a viscous friction item; according to the established kinetic equation and a mechanical arm track error following signal, establishing a following error kinetic equation which takes parameter uncertainty into consideration; establishing a state space model of mechanical arm track following errors; establishing a fixed time disturbance observer according to the established space model; establishing a fixed timenon-singular terminal sliding mode surface according to the mechanical arm track following error signal; preliminarily determining each joint drive motor control moment instruction of a mechanical arm, and integrating a moment output range of a performer, thereby obtaining each joint control moment of the mechanical arm. The invention relates to the field of mechanical arm control.

In some example embodiments, a position recognition method of an autonomous mobile robot may include: dividing a grid map into a plurality of spaces; extracting, by a processor, learning data of each of the plurality of spaces; generating, by the processor, space models of each of the plurality of spaces using the extracted learning data; and / or recognizing, by the processor, a current position of the autonomous mobile robot based on the extracted learning data, the space models, and actual range scan data input through the autonomous mobile robot.

A probabilistic digital signal processor for medical function is described. Initial probability distribution functions are input to a dynamic state-space model, which operates on state and / or model probability distribution functions to generate a prior probability distribution function, which is input to a probabilistic updater. The probabilistic updater integrates sensor data with the prior to generate a posterior probability distribution function passed to a probabilistic sampler, which estimates one or more parameters using the posterior, which is output or re-sampled in an iterative algorithm. For example, the probabilistic processor operates using a physical model on data from a medical meter, where the medical meter uses a first physical parameter, such as blood oxygen saturation levels from a pulse oximeter, to generate a second physical parameter not output by the medical meter, such as a heart stroke volume, a cardiac output flow rate, and / or a blood pressure.

The invention belongs to the technical field of multi-document summarization and provides a multi-document summarization method based on text segmentation, which comprises the following steps of: using HowNet to obtain a concept, building a concept vector space model, conducting text segmentation by adopting an improved DotPlotting model and a sentence concept vector space, calculating sentence weight by using the built concept vector space model, generating a summary according to the sentence weight, the text segmentation and the similarity situation, and evaluating the generated summary by using the ROUGE-N evaluation method and using F_Score as an evaluation index. According to the result, the multi-document summarization by using a text segmentation technique is effective, relevant documents provided by users can be gathered to form a summary by adopting the multi-document summarization method, the summary is displayed to the users in a proper way, the information acquisition efficiency is greatly improved, the practicability is high and the popularization and application values are greater.

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 present invention provides an apparatus and method for camera parameter calibration which is capable of easily and simply setting physical and optical characteristic parameters of a camera in order to acquire information on actual measurement of an image provided through the camera with high accuracy. The camera parameter calibration apparatus and method has an advantage of correct image analysis that it is capable of increasing accuracy of information of measurement through an image only with an intuitive interface manipulation, without taking a time-consuming and incorrect actual measurement procedure, by determining parameters of the space model corresponding to the image by displaying a 3D space model corresponding to a real space of the image on the image and changing and adjusting visual point parameters such that the 3D space model matches the display image, and regarding the determined parameters of the space model as camera parameters of the image.

A method and information management system of structure health comprises transducer subsystem, data collection subsystem, data management subsystem, data storage device subsystem, diagnosis and analysis subsystem, real time monitor and data query subsystem. It is featured as setting up said data management subsystem based on commercial databank management system, enabling diagnosis and analysis subsystem to carry out parameterization by utilizing monitored building 3-D space model set based on 3-D GIS technique in order to obtain multiple mode parameter.

The invention relates to a multiple target tracking-based passenger flow statistics method which comprises the following steps: a deformable part model is used for subjecting a marked human shape sample to off line training operation, and a human shape part model can be obtained; the human shape part model comprises a root filter, a part filter and a space model for positions of parts relative to a root; the human shape part model is used for subjecting each image frame in a video to human shape object detection operation, a two stage track association method is adopted for tracking pedestrian objects in image scenes, movement tracks of pedestrians being detected are obtained, and the pedestrian objects can be counted in real time according to the movement tracks and movement directions in a camera-covered zone. Front end cameras adopted in the multiple target tracking-based passenger flow statistics method are deployed above entries and exits of indoor environments such as supermarkets, supermarkets and the like; vertical or overlooking sampling operation can be performed; tilting sampling scenes can be optimized in a specific manner, the objects can be detected in the camera-covered zone, the number of people going in and out can be counted in real time while the pedestrians are detected and tracked, and correct rates of pedestrian object statistics exceed 90%.

A probabilistic digital signal processor using data from multiple instruments is described. Initial probability distribution functions are input to a dynamic state-space model, which operates on state and / or model probability distribution functions to generate a prior probability distribution function, which is input to a probabilistic updater. The probabilistic updater integrates sensor data from multiple instruments with the prior to generate a posterior probability distribution function passed (1) to a probabilistic sampler, which estimates one or more parameters using the posterior, which is output or re-sampled in an iterative algorithm or (2) iteratively to the dynamic state-space model. For example, the probabilistic processor operates on fused data using a physical model, where the data originates from a mechanical system or a medical meter or instrument, such as an electrocardiogram or pulse oximeter to generate new parameter information and / or enhanced parameter information.

A probabilistic digital signal processor is described. Initial probability distribution functions are input to a dynamic state-space model, which operates on state and / or model probability distribution functions to generate a prior probability distribution function, which is input to a probabilistic updater. The probabilistic updater integrates sensor data with the prior to generate a posterior probability distribution function passed (1) to a probabilistic sampler, which estimates one or more parameters using the posterior, which is output or re-sampled in an iterative algorithm or (2) iteratively to the dynamic state-space model. For example, the probabilistic processor operates using a physical model on data from a mechanical system or a medical meter or instrument, such as an electrocardiogram. Output of the physical model yields an enhanced output of the original data, an output to a second physical parameter not output by the medical meter, or a prediction, such as an arrhythmia warning.

The invention provides a method for measuring submarine density and sound velocity based on multi-path reflection theory; based on plane wave reflection theory and snell law, the method comprises: extablishing equations with submarine reflection coefficients of multiple paths, measuring the time of arrival, the nearby reflection angle and energy at seabed of each path by equipment such as a vertical array and a sound source so as to finally obtain submarine density and sound velocity; the measured submarine density and sound velocity can be used to solve the positioning problem of passive objects in an unknown condition of submarine environment in shallow sea. The beneficial effects of the invention are that: the method uses obliquely incident sound wave of a sound source; the reflection wave energy is large; the emitting sound source is not limited by high power or narrow directivity; the method can measure submarine density and sound velocity independently; although earth sound parameters of each layer of a multilayer submarine medium can not be measured, equivalent density and sound velocity under a submarine semi-infinite space model can be measured; and the method has the advantages of a simple and practical experiment platform, low price, low computational complexity and the like.

The invention discloses a job recommending method, and belongs to the technical field of recommending systems. The job recommending method has the advantages that the Matthew effect is avoided, the problem of cold start is solved, and the populations are well utilized to realize personalized recommending. The job recommending method comprises the following steps of obtaining user data and job data; establishing a user preference vector space model and a job vector space model; according to the user preference vector space model and the job vector space model, calculating multi-domain scoring values based on contents, obtaining first scoring values of jobs, and sequencing, so as to obtain a job set; when one job is submitted and belongs to the job set, calculating the scoring valves of the corresponding job based on the similarity of user background information according to the user preference vector space model and the job data, and obtaining second scoring valves of the corresponding job; according to the first scoring valves and the second scoring valves, obtaining the mixed scoring valves of the corresponding job, and sequencing, so as to obtain a recommending list.

The invention provides a map building method and system based on data fusion of two laser radars as well as a map. The method comprises a step of building a point cloud map and also comprises the following steps: performing calibration and data fusion on the two laser radars; performing interframe point cloud coarse registration by adopting a rapid space model point cloud registration algorithm; and performing pose correction by adopting the nearest neighbour iteration, so that optimal interframe transformation is obtained and accurate interframe point cloud splicing is realized. The method provided by the invention firstly performs space and time synchronization on the double laser radars and performs the data fusion on the laser radars; then the interframe point cloud coarse registrationis performed by adopting the rapid space model point cloud registration algorithm, and point cloud registration correction is performed by utilizing the nearest neighbour iteration point cloud registration, so that high-precision interframe point cloud splicing is realized; and finally building of the point cloud map is completed.

The invention discloses a method of modeling a hybrid MMC state space model, a steady-state analytical model and a small signal model, belonging to the technical field of power system transmission anddistribution. The state space model includes deducing the modulated signals and output voltage reference values of the lower and upper legs of each phase to obtain the circuit dynamic model in the static coordinate system, and obtaining the dynamic phasor model of the hybrid MMC in the rotating coordinate system through the coordinate change. The steady-state analytical model includes based on the state space model, deriving the steady-state analytical model, and analyzing the solution of the steady-state analytical model under a variety of constraints. The small signal model includes deriving the small signal model of the total capacitance voltage of the bridge arm sub-module and the circulation current of the bridge arm, integrating the small signal model of the open-loop control, and deducing the small signal model of the closed-loop control on the basis of considering the control system. The method of the invention is applicable to the joint modeling of an AC system and a DC network, as well as the engineering design and operation characteristic analysis of a hybrid MMC.

Movement of a vehicle such as a boat (30) is guided by dynamically monitoring parameters and generating instructions for the operator. The instructions are at a level to attain a number of sub-goals to reach a goal position (33) from a current position (32). Each sub-goal is attained in a single vehicle manoeuvre such as straight-ahead or rotation, each manoeuvre being instructable to the operator. The instructions are generated using a space model (12) of the space around the vehicle, an operator model (11) of operator vehicle control characteristics, and a vehicle model (12) of vehicle movement characteristics.

The invention discloses a short-term speed prediction method for a signal intersection road section. The method comprises the following steps: (1) integrating and processing traffic data, matching road section speed data and signal lamp operation data, and respectively constructing an intersection traffic data set and a road network traffic data set aiming at an intersection and a road network; (2) carrying out input data space-time modeling, comprising a traffic space model and a traffic time sequence model; and (3) constructing a prediction model, and based on a depth graph convolutional network GCN and a recurrent neural network RNN, constructing a short-term speed prediction model of the signal intersection road section by utilizing a generative adversarial network GAN framework. The short-term speed prediction method for the signal intersection road section provided by the invention is high in prediction accuracy.