156 results about "Distance constraints" patented technology

The invention relates to a three-dimensional wire frame structure method and system fusing a binocular camera and IMU positioning. On the basis of binocular vision, the invention initializes and fusesinertial measurement information by using a divide-and-conquer strategy, implements tracking, positioning and drawing, and can robustly run in indoor and outdoor environments and complex motion conditions. On the basis of accurate positioning, 3D wireframe reconstruction and iterative optimization are carried out based on the posture of the key frame. Linear segments are matched by local featuresand spatial geometric constraints and back-projected into three-dimensional space. Through the angle and distance constraints, the straight line segments are divided into different sets. Based on thegrouping results, the fitting region is determined and the straight line segments are merged. Finally, a 3-D wireframe structure is output. The invention fuses multi-source information to improve thestability and robustness of the system on the traditional vision-based positioning and mapping method. At the same time, line information is added to the key frame to sparsely express the structuralcharacteristics of the three-dimensional environment, which improves the computational efficiency.

A method and system for dynamically representing cluster analysis results. In accordance with the method and system of the present invention, a hierarchical tree is graphically displayed. The hierarchical tree represents cluster analysis of relationships between multiple items utilizing an initial distance constraint value, wherein the graphical display includes a graphically alterable threshold indicator positioned within the hierarchical tree that graphically marks the distance constraint value. The presentation of the graphical display of the hierarchical tree is dynamically altered to reflect a user-determined distance constraint value, in response to user-controlled alteration of the graphical position of the threshold indicator, such that upon changing a distance constraint for a cluster analysis, the hierarchical tree which graphically represents the cluster analysis is dynamically altered.

The invention, which belongs to the computer vision field, provides a flexible-target-based close-range large-field-of-view calibrate method of a high-speed camera and relates to a close-range large-field-of-view binocular-visual-sense camera calibration method in a wind tunnel. According to the method, a flexible target is used for fill an overall calibration view field for calibration; the internal region of the target is formed by a planar chessboard mesh and distances between angular points of the chessboard mesh are known; the external region of the target is formed by cross target rods perpendicular to each other and a plurality of coding marking points with known distances are distributed on the target rods uniformly. During calibration, regional and constraint calibration is carried out on a high-speed camera by using different constraint information provided by different regions of the target. When the internal region of the target is calibrated, calibration is carried out by using a homography matrix; and the external region is calibrated by using distance constraints of the coding marking points. According to the invention, the cost is lowered and the operation portability is realized. During calibration, distortion of different regions is considered by using the regional and constraint camera calibration method, so that the calibration precision is improved.

The invention provides a parking space detection method. The method comprises the following steps: constructing a large-scale, annotated looking-around image data set for a parking space perception problem; improving a target detection framework YOLOv2 framework based on deep learning to complete parking space control point detection; pairing each two detected control points to form point pair combination, performing preliminary screening on the distance constraints, designing a custom model to classify point pairs of parking space control points that satisfy the distance constraints on the basis of a shallow model AlexNet based on a classification model of deep convolutional neural network, and judging the type of a parking space and the entrance line direction to complete parking space deduction. The parking space detection method provided by the invention is an important component of an autonomous parking system in unmanned driving, the position of the parking space can be detectedonly by cameras around the vehicle body, and a technical support is provided for the autonomous parking. The parking space detection method provided by the invention is not only high in detection precision, but also is high in response speed, and is stable and reliable.

The invention provides a fast updating method of road network based on trajectory adaptive clustering, characterized in that the method comprises: whether the trajectory points match with the originalroad network is judged by the distance constraint condition and the direction constraint condition between the collected moving trajectory data and the acquired original road network data, Unmatchedtrajectory points are obtained by matching results, Adaptive trajectory clustering is carried out for the unmatched trajectory points, and for each trajectory clustering, the curve fitting of the trajectory points is carried out by using the optimal master curve fitting method, the road centerline is extracted, the driving direction of the road and the single / two-way information are recognized, and then the fusion of the changing road and the original road network is completed. The method can be used to identify the changing area of urban road network quickly, extract and update the fine geometrical structure of the changing road in complex scenario, and identify and update the semantic information of road driving direction, single / two-way and so on.

The invention relates to an intelligent chess playing control method and a control system, and belongs to the field of intelligent battle platforms. The invention provides the intelligent chess playing control method and the control system, in order to overcome shortcomings of an existing playing system which can support offline playing only and cannot simultaneously solve problems on physical distance constraint and real playing feeling. The intelligent chess playing control method comprises the following steps: acquiring a frame in a video flow and taking the acquired frame as a current frame; recognizing central position coordinates of markers at four corners of a chessboard; conducting projective transformation on an image; and acquiring a moving way of a user through threshold analysis and inputting the moving way into a decision algorithm so as to obtain optimum chessman locating positions. According to the remote playing system provided by the invention, the chessboard image is acquired by virtue of a camera, chessman moving data is extracted and the chessman moving data is transmitted to the online user by virtue of a server; and then, chessman moving steps of the online user are acquired by virtue of an embedded platform through the server and the steps are transmitted to a single chip by virtue of a serial port, and subsequently, chessmen are moved by controlling a mechanical arm. The intelligent chess playing control method and the control system provided by the invention are applicable to intelligent chess playing platforms.

The invention discloses a visual position-pose measurement method based on point-line combination characteristics, which belongs to the technical field of computer vision measurement and relates to a method applicable to measurement on the position and pose of a split-type cylinder-like object moving at high speed. The surface point-line combination characteristics of the cylinder-like object moving at high speed are acquired by a binocular visual system; a target axis and a local coordinate system can be obtained through five steps of calibrating by a high-speed camera, segmenting a point-line characteristic image, extracting characteristic marks, matching the characteristic marks, and acquiring the position and the pose, and then target position-pose information is acquired according to the target axis and the local coordinate system; the point-line combination characteristics consists of circle reflection marks with two axes respectively formed at the front segment and the rear segment of a target object coinciding with target axes, and four point reflection marks which are uniformly distributed at the circumference of the middle segment of the target object and are restrained from different distances to the circle at the front end. The problems that the axis of the cylinder-like object is not easy to acquire, the precision of the acquired axis is low, and the surface mark can not be precisely positioned due to the repeated assembly of the split-type object are solved by utilizing straight-line characteristics of strong anti-noise capacity and large information amount which are matched with point characteristics.

The invention discloses a point cloud automatic registering method based on a point characteristic histogram. The point cloud automatic registering method is characterized in that multi-station acquisition of point cloud data of a measured object is carried out, and a reference station and a to-be-registered station are determined; m sampling points are selected from the cloud data of two stations randomly, and any three of the sampling points do not share a line, and every two sampling points satisfy a distance constraint principle; the corresponding point pair matching of the two stations are carried out, and the corresponding point pair triangular network of the reference station sampling point set and the to-be-registered station sampling point set are almost congruent; the transformation matrix of the point cloud data of the to-be-registered station is acquired, and point characteristic histogram difference values are calculated to acquire matching errors; the transformation matrix corresponding to the minimum matching error is selected; the point cloud data of the superposed area of the point cloud data of the two stations is calculated, and a refined registration matrix is acquired by an iterative closest point algorithm. The point cloud automatic registering method is used to solve the problem that when the point cloud superposition degree of two adjacent stations is small or the superposed area characteristics are not obvious, the point cloud data matching is easily trapped by the local minimum solution, and has advantages of high accuracy and high integral efficiency.

The invention discloses a secondary structure spatial distance constraint-based protein conformation search method. According to the method, feature vectors are formed by utilizing a spatial length ofeach secondary structure in a target protein and information of spatial distance between central residues of every two adjacent secondary structures so as to serve as space limitation conditions under a basic framework of a genetic algorithm, so that a solution space is searched in a relatively small conformation space under the condition that an energy function is given; and meanwhile, the spatial distance information is added in a selection operator, so that the inaccuracy of the energy function is made up and then the accuracy of structure modeling is effectively improved. The invention discloses the secondary structure spatial distance constraint-based protein conformation search method which is relatively high in sampling efficiency, relatively high in prediction accuracy and low incalculation cost.

The invention discloses an intelligent vehicle path planning method based on bidirectional extension random trees. The method comprises the following steps of generating a curve, and constructing twoextension trees which are opposite in starting point when an obstacle exists on the curve; generating a random point on the map, and searching for a node of the extension tree nearest to the random point; judging whether an obstacle exists on a connecting line of the random point and the node; if yes, generating a random point again, and if not, taking a new node on the connecting line of the random point and the node; judging whether an obstacle exists on the connecting line between the nearest node and the new node; if yes, generating the random point again, otherwise, updating the node according to the obstacle safety distance constraint; afterwards, selecting a father node and a child node of the node according to the intelligent vehicle maximum steering constraint and the node; judging whether the distance between the two extension trees is smaller than a set threshold value or not, if being greater than the set threshold value, generating a random point again, otherwise, reversely selecting the path of the node to the starting point and the path of the node to the target point according to the nodes of the two extension trees to form an intelligent vehicle planned path.

The invention discloses an image super-resolution reconstruction processing method. On the basis of adaptive sparse representation reconstruction research, a series of corresponding sub-dictionaries are obtained through image block subset learning, and then an optimal sub-dictionary is adaptively selected for each reconstructed image block, so that more accurate sparse representation modeling can be carried out and the algorithm effect and efficiency can be improved. In order to improve the capability of a sparse representation model, a nonlocal self-similarity prior item is introduced, a nonlocal self-similarity model is improved by utilizing a bilateral filtering thought, and spatial position distance constraints among pixels are introduced, so that image edge information is better kept. Moreover, distance measurement of nonlocal self-similarity is improved, so that the calculation amount is reduced. An experiment proves that the noise influence can be effectively suppressed and image edge details can be kept, and the method has a certain superiority in the aspects of peak signal-to-noise ratios and visual effects.

The invention discloses a method for expanding coverage of vehicle networking security information broadcast and includes the steps of designing a non-uniform backoff window initial value selective probability according to dynamitic regulation of a backoff window constraint sequence Xr and forwarding nodes spaced source nodes by different distances, and conditions to be met for the constraint sequence Xr in a scenario of actual security information forwarding application; calculating a Gamma r distance constraint factor through a relative distance dr and structuring the constraint sequence Xr through the Gamma r factor; and initializing the initial value of a backoff window counter and accessing to a backoff process to realize access control of shared media after the initial value of the backoff window is generated in each forwarding node under the constraint of the constraint sequence Xr. The method for improving the vehicle networking security information broadcast coverage has the advantages that the purpose of improving effective coverage of multi-hop broadcasting of security information within time slot in a CCH (channel check handler) channel is achieved by improving the probabilities of forwarding data packages in the time slot of the nodes relatively distant from the source nodes at one jump reach and the like.

The invention discloses a rapid positioning method based on TDOA (Time Difference Of Arrival), mainly aiming to solve the problems when a tested target performs position solution depending on TDOA detected by a plurality of signal receivers under near and long distance scenes. The method mainly comprises the steps of: coordinate and distance equation establishment, centre distance solution, object coordinate solution, distance constraint and spherical surface relation constraint establishment, and solution of object coordinate corrected solution. The method can solve the problem of passive detection and positioning of an underwater vehicle, and can also be used for solving other positioning problems based on TDOA, such as radio positioning, ultrasonic wave positioning, indoor positioning, etc. Compared with a commonly used Chan algorithm, the rapid positioning method based on TDOA solves the problem of inconformity of near distance and long distance algorithms and existence of fuzzy solution, and furthermore improves precision and stability; compared with a Taylor algorithm, the rapid positioning method based on TDOA does not need external initial value and recursion operation, substantially reduces arithmetic labor, but does not change precision and stability.

The invention provides a remote sensing ship detection method based on a characteristic pyramid structure full convolutional neural network, and mainly solves the problems of mutual overlapping of horizontal contour bounding boxes and low coverage and detection rate in the prior art. The method comprises the following steps: 1, selecting and cutting a sample picture in an existing remote sensing data set, and dividing the sample picture into a training sample and a test sample; 2, training the full convolutional neural network by using an overall loss function composed of a category loss function with pixel distance frame minimum constraint and a shape loss function; 3, inputting a test sample into the trained full convolutional network, outputting the test sample as a characteristic matrix of each pixel point, and performing coordinate transformation to obtain coordinates of the contour bounding box; and 4, screening and combining the pixel contour bounding boxes to obtain a detectionresult image and a coordinate file. According to the method, the contour boundary frame with the angle can be generated for the remote sensing ship image, the detection rate is high, the boundary isaccurate, and the method can be used for extracting the ship target from the remote sensing image shot by the optical sensor.

The invention discloses a dynamic adaptive speed look-ahead control method of continuous small line segment trajectories. The method comprises the steps that S1 the maximum speed of connecting points is calculated and the speed look-ahead number of segments is determined; S2 entering a deceleration area or not is judged, and the process jumps to the step S3 if the judgment result is no; S3 initial speed and end speed are compared; and the process jumps to the step S4 if the initial speed is greater than the end speed; S4 whether the deceleration distance constraint condition is met is judged; and the process jumps to the step S7 if the judgment result is yes, or the process jumps to the step S5; S5 whether the deceleration distance in which the initial speed reduces to the end speed is less than the current line segment displacement length is judged, and the process jumps to the step S7 if the judgment result is yes, or the process jumps to the step S6; S6 the maximum initial speed of the current segment displacement length constraint is searched and cycling is performed until tracing back to the look-ahead start point; S7 the non-look-ahead path is updated and whether the segment of the current line segment is less than the look-ahead number of segments is judged, and the process jumps to the step S2 if the judgment result is yes, or the process jumps to the step S8; and S8 speed look-ahead control is ended. High-speed connection of transition speed between the continuous trajectories can be effectively realized so that the processing time can be greatly shortened and the processing efficiency can be enhanced.

The invention discloses a synergistic target tracking method for dual unmanned planes under a communication constraint. In the method, two unmanned planes are controlled to synergistically track a ground target; in the tracking process, when judging that the lead plane per se is in a forced approaching state, the lead plane rapidly meets the requirement of a detection range constraint again; if the lead plane is not in the forced approaching state, the priority is given to precision, and the lead plane enhances the precision of target observation data; a wing plane is same as the lead plane in the aspects of forced approaching state and principle of precision enhancement; the motion range of the wing plane is limited in a small range with connecting line of the two planes as a center, so that the wing plane can track the lead plane with a enough velocity component to ensure that a distance between the lead plane and the wing plane is less than a set value. By means of the method, the communication distance constraint can be met to provide the communication support for synergy; the detection range constraint of the lead plane can be met to provide guarantee for target tracking; and during flight the tracking accuracy can be analyzed in real time and the track can be optimized to provide guarantee for tracking quality.

The invention discloses a mobile network quantum key distribution system based on near field communication and a distribution method thereof. The inspection of the distribution environment of near field communication key can be realized and the user validity of mobile equipment can be verified by a striking distance constraint module, a user authentication module, a key distribution module, a mobile terminal key storage module, a key synchronous module, a quantum encryption file transmission module, a mobile terminal key storage, a key pool, a near field communication device and a fingerprint module which are connected. The server end is realized to be synchronous with the key at a gateway terminal, the secrete storage of the quantum key of the mobile network as well as the encryption communication of the mobile equipment and the server terminal are realized by distributing the quantum key of the mobile network based on a near field communication protocol. The mobile network quantum key distribution system has the features of high portability and light application of the mobile equipment.

A method for colony conformation space optimization based on a distance constraint selection strategy comprises the following steps: under a differential evolution algorithm framework, adopting a Rosetta Score3 coarseness knowledge energy model to effectively reduce a conformation space search dimension number and improve the convergence rate of an algorithm; introducing a fragment packaging technique based on knowledge to effectively improve prediction accuracy; utilizing character constraints of a distance spectrum in protein structure to make more structurally similar protein conformations enter a colony, so as to reduce errors caused by energy function inaccuracy and obtain more excellent local conformations; and performing more effective sampling on conformation space in combination with a high global searching capability of the differential evolution algorithm, so as to obtain conformations highly similar to a natural structure. The Rosetta Score3 coarseness knowledge energy model is adopted to effectively reduce the conformation space search dimension number and improve the convergence rate of the algorithm and prediction accuracy.

The invention discloses a multi-target human body posture detection method and system related to the field of image processing. The method includes the steps of acquiring a target image; extracting joint point information of the target image; acquiring matching information between joint points according to the joint point information and distance constraints between the joint points; and combiningthe joint points according to the matching information to complete the human body posture estimation according to the matching information. Further, acquiring the target image also comprises the steps of scaling the target image to construct an image pyramid; and obtaining a scaled image of the target image at different scales by setting a pyramid layer number and a scaling standard. According tothe invention, through addition of the distance constraint condition between the joint points, the problem of wrong joint point matching between different targets can be solved.

Systems and methods govern participation in and enforce a limit on the number of nodes that can participate in a cryptocurrency or other distributed computing network. Unlike other approaches, systems and methods herein do not require excessive use of resources. Admission of a node to a network is governed by the consensus of pre-existing nodes using a process or physical characteristic of the candidate node to determine its eligibility. One instantiation uses physical location as the unique physical characteristic, with a distance constraint to force geographic separation between nodes. Another uses signal response time over the network as a proxy for distance, relying on the fact that network nodes cannot respond to an interrogation before it is received. Combined with an appropriate time constraint, this enables network space to be used as an analog for geographic space, despite the fact that network transmission speeds and paths are variable.

The invention discloses a vector map matching navigation method for a linear target in aviation, which comprises the following steps: preparing a base vector diagram and a template vector diagram for map matching, unifying the base vector diagram and the template vector diagram under a same vector precision level, and extracting included angle characteristics of the template vector diagram and the base vector diagram; sequentially utilizing a distance constraint condition, a sequence constraint condition and an error constraint condition to gradually limit size of a feasible solution space; clustering pose parameters of the feasible solution space, taking a class containing most pose parameters as a correct matching relationship; and further computing the pose parameters to be errors for correcting an inertial navigation system by matching positioning results. The method provided by the invention can overcome shortages of space efficiency and time efficiency in the existing grid image matching navigation method for aviation and avoids the problems of large data volume, low efficiency and the like in the grid image matching; in addition, the method provided by the invention overcomes influence of small-scale change on a vector map and can achieve vector map matching under rotation, translation and small-scale change.

The invention discloses a dual constraint based selection calling method of an LOD (Level of Detail) model in a three-dimensional scene. The dual constraint based selection calling method comprises entering into the three-dimensional scene; obtaining a viewpoint coordinate of a user and a center coordinate of the current object in the three-dimensional scene; calculating the sight distance and judging whether the current object is within the field of view of the user or not; calculating the interest degree of the user of a three-dimensional model and calling the user required level number of the current object model; combining with the distance constraint condition to select to call the user required LOD model of the current object; rendering and drawing the selected model; judging whether objects in the three-dimensional scene are traversed or not. According to the dual constraint based selection calling method of the LOD model in the three-dimensional scene, the LOD model can be selected to be called based on the interest degree and the distance, the requirements for the high image quality of the high interest degree of object of the user are met, meanwhile the weakening treatment is performed on the low interest degree of object of the user, and the rendering speed of a system is improved under the condition that the basic visual demand of the user is satisfied.

The invention discloses a distance-constrained photogrammetric high-precision target positioning method. The method comprises the following steps of: the step 1, calibrating parameters in a camera; the step 2, shooting a target image containing an indium steel ruler; the step 3, measuring coordinates of the target point image; the step 4, calculating the three-dimensional coordinate of the target point by adopting a least square method, and taking the three-dimensional coordinate as the initial value of the physical coordinate of the target point; the step 5, acquiring initial values of elements of the external orientation of the image; the step 6, calculating the net adjustment of the distance constraint; and the step 7, performing adjustment iteration convergence determination, determining the correction number calculated each time until the difference limiting requirement is met, and obtaining the high-precision coordinate of the target point. The method does not need to independently arrange control points, can obtain millimeter-level target point location precision, is simple and quick, reduces operation time, has high measurement speed, and greatly improves measurement operation efficiency.

The invention puts forward a radar track initiation method based on location information and Doppler information in order to solve the technical problem that the existing sequential processing technical method is of low track initiation efficiency. The method is implemented by the steps as follows: calculating the maximum unambiguous velocity; selecting a track head from measurement vectors scanned at the kth time, and calculating a radial velocity set; building a distance constraint accord to the radial velocity; building a space constraint according to the maximum velocity; during (k+1)th scanning, associating measurement vectors which are on the same Doppler channel with the track head and meet the two constraints; using effective measurement vectors to update the distance constraint, and continuing the association operation; building a stable track according to the track initiation criterion; and traversing the measurement vectors scanned at the kth time and a corresponding radial velocity set. The method of the invention is of high track initiation efficiency, and can be used in target tracking.

The invention discloses an infrared and visible remote sensing image registration method based on salient region analysis, which can be used for registration of infrared and visible remote sensing images in aerospace and aviation. The method comprises the steps of: acquiring infrared and visible images of the same scale and direction according to longitude and latitude information; extracting salient regions beneficial for feature matching in the infrared images according to the feature consistency principle; extracting SIFT (Scale Invariant Feature Transform) feature points in two images and calculating feature descriptors; and carrying out feature matching according to the similarity, the scale and the distance constraint of the features; carrying out weighting and sequencing of the feature matching results according to salient images; selecting a subset of matching results with translation consistency; calculating the transformation matrix of maximal inner points of the subset according to the selected feature points; and transforming the infrared images into the same coordinate system as the visible images. Based on the method, the influence of wrong matching results on results is restrained, and the problem of infrared and visible image registration caused by different sensor types is solved.

The invention discloses a precise registration method of a damaged part based on an improved ICP (Inductively Coupled Plasma) algorithm. The method comprises the steps of carrying out advanced registration to generally adjust two models to correct position by adopting a three-point aligning method; precisely registering by adopting an improved ICP algorithm; combining a corresponding point curvature constraint and a corresponding point distance constraint in the process of precisely registering, and realizing the automatic elimination on damage point cloud by setting the curvature constraint and a distance threshold value, so as to obtain corresponding points of a non-damaged area, realize the precise registering of the non-damage area to obtain the morphology of a damaged area quickly and accurately. The method has the significant effects of taking full account of the change of the surface size and morphology of a damaged part in the process of registering precisely, and ensuring the accuracy of the corresponding point of the registering point cloud by combining the corresponding point curvature constraint and the corresponding point distance constraint.

A method for location tracking on a distributed basis using multiple locations. which utilizes a pairwise application of distance constraints and vicinities for determining locations. The location of a particular node is represented by a group of points (as opposed to a single point) defined by the vicinity.

The invention relates to a car-sharing matching method. The car-sharing matching method comprises the following steps of 1, according to the departure time constraint to screen drivers; 2, according to the European-style Pickup distance constraint to screen drivers; 3, utilizing the latest time constraint and cost constraint to screen drivers (European-style distance); 4, utilizing the Pickup minimum road distance constraint to screen drivers; 5, utilizing the latest time constraint and cost constraint to screen drivers (minimum road distance); 6, executing matching. The car-sharing matching method is suitable for the quick matching of a car-sharing system.

The invention discloses a spatial-keyword query method and system based on spatial distance constraints. The method and system are suitable for use in the field of information query technology. The method includes: acquiring spatial keywords, the spatial distance constraints and a target number input by a user, wherein the spatial keywords include a to-be-queried geographic location and a to-be-queried text keyword set; acquiring a set of spatial text objects in a preset spatial range, wherein the spatial text objects include geographic locations and a text keyword set; dividing the spatial range into grids according to a preset rule, and carrying out coding for each grid; establishing an inverted table for the set of the spatial text objects according to the text keywords, and establishing an aggregate linear quadtree for each text keyword; and obtaining a query result set according to the to-be-queried geographic location, the to-be-queried text keyword set, the spatial distance constraints, the grids, corresponding codes of the grids, the inverted table and the target number. According to the method, query and updating efficiency can be effectively improved, and maintenance timefor the tree can be reduced.