156 results about "Cost matrix" patented technology

Variations of this invention provide durable, impact-resistant structural coatings that have both dewetting and anti-icing properties. The coatings in some embodiments possess a self-similar structure that combines a low-cost matrix with two feature sizes that are tuned to affect the wetting of water and freezing of water on the surface. Dewetting and anti-icing performance is simultaneously achieved in a structural coating comprising multiple layers, wherein each layer includes (a) a continuous matrix; (b) discrete templates dispersed that promote surface roughness to inhibit wetting of water; and (c) nanoparticles that inhibit heterogeneous nucleation of water. These structural coatings utilize low-cost, lightweight, and environmentally benign materials that can be rapidly sprayed over large areas using convenient coating processes. The presence of multiple layers means that if the surface is damaged during use, freshly exposed surface will expose a coating identical to that which was removed, for extended lifetime.

The invention discloses a multidimensional weighted 3D recognition method for dynamic gestures. At the training stage, firstly, standard gestures are segmented to obtain a feature vector of the standard gestures; secondly, coordinate system transformation, normalization processing, smoothing processing, downsampling and differential processing are performed to obtain a feature vector set of the standard gestures, weight values of all joint points and weight values of all dimensions of elements in the feature vector set, and in this way, a standard gesture sample library is constructed. At the recognition stage, by the adoption of a multidimensional weighted dynamic time warping algorithm, the dynamic warping distances between the feature vector set Ftest of the gestures to be recognized and feature vector sets Fc =1,2,...,C of all standard gestures in the standard gesture sample library are calculated; when the (m, n)th element S(m, n) of a cost matrix C is calculated, consideration is given to the weight values of all the joint points and the weight values of all the dimensions of the elements, the joint points and coordinate dimensions making no contribution to gesture recognition are removed, in this way, the interference on the gesture recognition by joint jittering and false operation of the human body is effectively removed, the anti-interference capacity of the algorithm is enhanced, and finally the accuracy and real-time performance of the gesture recognition are improved.

The invention discloses a path determination method, a path determination device, and a navigation instrument. The path determination method comprises the following steps: obtaining a starting point and an ending point of a to-be-determined path; obtaining data of obstacles in corresponding regions of the starting point and the ending point, wherein each obstacle is expressed by a polygon; the data of the obstacles are corresponding data of the polygons; determining general views of the corresponding regions according to the starting point, the ending point and the obstacle data; calculating the adjacent cost matrixes of the general views; and determining the shortest path from the starting point to the ending point according to the adjacent cost matrixes. Through the path determination method and the path determination device, the path is determined on the basis of the general views; the path determination process without a road network region is transformed into the path determination process with the road network region; and the path search accuracy is high in accuracy.

According to a stereoscopic image dense matching method and system based on LiDAR point cloud assistance, LiDAR point clouds in a projection acquired stereopair overlapping range are subjected to parallel filtering processing; the filtered point clouds are projected to an epipolar line stereopair and a parallax range of subsequent dense matching is determined; a pyramid is built, starting from a top layer of the pyramid, a cost matrix is transformed by adopting a triangulation network constraint, SGM dense matching is carried out, and left and right consistency detection is carried out so as to obtain a final parallax image of the top layer; a parallax image of a current layer of the pyramid is transferred to a next layer to be used as an initial parallax image, a parallax range of the next layer is correspondingly determined according to the parallax image of the current layer, and the next layer is used as a new current layer; and on the basis of the new current layer, processing is carried out as well to obtain a final parallax image of the current layer up to a bottom layer of the pyramid, a parallax image of an original image is output, and according to the parallax image of the original image, corresponding image points of the stereopair are obtained and the densely matched point clouds are generated.

The invention discloses a multi-UAV (unmanned aerial vehicle) helicopter and warship cooperating path planning method. The method comprises the steps of 1, calculating a route cost matrix according to the euclidean distance between a target node and a tactical node; 2, modeling the multi-UAV helicopter and warship cooperating path planning through the solved route cost matrix; 3, creating coding rules to enable corresponding between the solution of the built model and the position vector of particles in a particle group, and initializing the solution of the model; 4, iterating the initial solution by the improved particle group algorithm to obtain the optimal solution; 5, treating the scheme corresponding to the optimal solution as the optimal scheme for multi-UAV helicopter and warship cooperating path planning. With the adoption of the method, the multi-UAV helicopter and warship cooperating path planning structure can be determined, and the multi-UAV helicopter and warship cooperating path planning scheme can be quickly provided, so that the efficiency, reasonability and accuracy of preparing the cooperating route planning scheme can be improved, and as a result, the war power of a fleet can be increased.

Computer-implemented methods for allocating resources to items are provided. One or more assignment scores for each item / resource pair are determined by applying one or more application-specific strategies to each item / resource pair using game theory. A cost matrix is created by first summing the assignment scores for each item / resource pair and then multiplying each assignment score sum by an assignment cost associated with assignment a particular resource to a particular item. Finally, an assignment solution is found by applying a Hungarian method to the cost matrix.

The invention discloses an XPath query optimization method and system. The method comprises the following steps of: counting structural summary information of an extensive makeup language (XML) document through hierarchical encoding; counting value summary information by using a value-coding histogram and RPST, and performing an optimization algorithm for query optimization on an XPath expression by utilizing the statistical information, wherein the query optimization algorithm comprises the following steps of: 101-102, initializing a data structure and processing a single-step path; 103, judging whether a non-estimated path exists; 104, judging the path type; 105-109, estimating connection with lowest cost in all possible connection of a long path, and updating a cost matrix and a result set matrix by using corresponding data; 110-114, estimating an arrangement sequence with lowest path in a predicate path, updating a cost matrix and a result set matrix by using the corresponding data, and resorting the predicates according to an optimized sequence; and 115, reconstructing a query plan. According to the XPath query optimization method and system, the XPath query sentences can be effectively optimized, and the execution efficiency of the XPath query sentences is greatly improved.

A method constructs a code, wherein the code is a large-girth quasi-cyclic low-density parity-check code. A base matrix is selected for the code. A cost matrix corresponding to the base matrix is determined. A single element in the base is changed repeatedly maximize a reduction in cost. A parity check matrix is constructing for the code from the base matrix when the cost is zero, and an information block is encoded as a code word using the parity check matrix in an encoder.

A distributed spatial data query optimization method in a grid computing environment is applicable to the grid computing environment and comprises the following steps: (1) analyzing user queries to form a spatial join operation diagram of two or more spatial data grid services; (2) generating an estimation cost matrix of a spatial join operation which possibly exist among the spatial data grid services according to the spatial join operation diagram; (3) adopting a progressive query optimization method to update the estimation cost matrix orderly, and selecting a more preferable spatial join operation according to a formation rule of a spatial join operation balance tree and the estimation cost matrix; and (4) for the better spatial join operation selected in the step (3), generating a better spatial join operation execution proposal according to an executable parallel strategy of a spatial join computing grid resource situation and spatial subdivision. The method can adapt to the characteristics of dynamic change of the grid computing environment and rich computing resources, and can generate a better query execution proposal based on the characteristics, thus improving the efficiency of executing the distributed spatial data query in the grid environment.

The invention provides an inertial system spacecraft attitude control / angular momentum management method including four steps. The invention aims to solve the problems of control moment gyro angular momentum accumulation caused by gravitation gradient moment and other interference moments in an inertial system, the gravitation gradient moment is adopted to balance the gestures, and a space station angular momentum management controller based on pole assignment is designed. A space station linear model is established under the inertial system, the infeasibility of the inertial system angular momentum management in the pitch axis direction is analyzed, the pitch axis is decoupled from a rolling / yaw axis, and the CMG angular momentum in the pitch axis direction is not restrained, constant disturbance, disturbance being one-time of the track frequency, and disturbance being twice of the track frequency are brought into a state equation to suppress the influence to the pitch axis gestures, and a linear quadratic algorithm based on pole assignment is adopted to solve a feedback gain matrix. The algorithm prevents the selection of cost matrix Q, and based on the requirement of the system performance, the closed-loop poles can be configured to a specified area at the left side of a complex plane imaginary axis, and at the end, the feasibility of the algorithm is verified by the simulation results.

An interplanetary communications network, an interplanetary communications backbone network of Artificial Neural Network (ANN) nodes, an ANN node and a method of managing interplanetary communications. The backbone network operates as a neural network with each node identifying optimum paths, e.g., end-to-end through the backbone network from a distant planet to an earth node. Each node maintains a window matrix identifying reoccurring (e.g., periodically) communications windows between nodes and a propagation delay matrix identifying time varying propagation delays between nodes. Each node determines whether and how long to store packets locally to minimize path delays. Each node also maintains a link cost matrix indicating the cost of links to neighboring nodes and further determines whether and how long to store packets locally to minimize path delays at minimal link cost.

The invention discloses a multi-soft-constraint stereo matching method based on a cost matrix. The method comprises the following steps: calculating a three-dimensional matching cost matrix at first, then carrying out multiple-dimension downsampling, and forming a cost matrix pyramid; carrying out the corresponding multiple-dimension downsampling of an image, forming an image pyramid, and carrying out segmentation of all image layers; carrying out cost accumulation of self-adaption weight layer by layer and cost accumulation under the voting-type segmentation constraint secondly, and achieving the cost accumulation under the multiple-dimension constraint through transmitting the cost accumulation results of the upper layer to the lower cost matrix; and achieving stereo matching through combining a reliable point cost diffusion method in a bottom layer cost matrix. The method improves the stability and reliability of matching results, solves the matching problems of weak texture and repeated texture regions and parallax error discontinuous places, and can be used for improving modeling, related to the engineering application of stereo matching, based on images.

A method of optimizing a spatially dependent ground engaging task including the steps of defining a plurality of sub-areas within an area, calculating a cost of performing the task and coalescing cost matrices. The calculating step includes calculating a cost of performing the task for each of the plurality of sub-areas for each of a plurality of times. The cost of each sub-area being an element of one cost matrix of a plurality of cost matrices. Each of the plurality of cost matrices being associated with one of the plurality of times. The plurality of cost matrices including a first cost matrix and a second cost matrix. The coalescing step including coalescing the first cost matrix and the second cost matrix to define an operational path for the performance of the ground engaging task.

The invention, which belongs to the technical field of electronic countermeasures, in particular relates to a time-difference-information-based passive multi-station multi-target direction-finding cross-positioning method. According to the method, on the basis of a multi-radiation-source data association algorithm, observation data from multiple observation stations are associated to obtain a costmatrix C(p,q); and then a coordinate of a target is estimated by using an aggregation hierarchy clustering algorithm based on the obtained cost matrix C(p,q). The method has the following beneficialeffects: association of data from multiple stations is completed accurately and the location of the target is estimated finally and accurately. The method is simple and has the good effect.

The invention relates to a remote sensing image multi-objective association method. At first, multi-scale auto-convolution (MSA) characteristics of a target image are extracted according to MSA conversion, and a matching cost of any two targets is obtained through calculation of Euclidean distance among the target characteristics, namely similarity measurement is obtained. Multi-objective association in two remote sensing images is considered as two-dimensional distribution, a multi-objective association cost matrix (ACM) is constructed, then practical application is combined, and an objective function is constructed according to the maxim of relevance, namely a global optimization model is constructed. At last, a simulated annealing algorithm is improved, inner loop iterations and outer loop iterations are set, a new self-adaptive temperature updating function is designed, a temperature control mode is improved, and therefore time performance of the algorithm is improved on the basis that association accuracy is guaranteed.

The invention discloses a video target multi-target tracking method and device and a storage medium. The video target multi-target tracking method comprises the following steps: obtaining a first image feature of a target object and a second image feature of an observation object; performing feature similarity calculation of N feature categories on the first image feature and the second image feature to obtain N groups of feature similarity results; screening the N groups of feature similarity results based on the feature similarity of the rough set, and fusing the screened results to obtain afeature fusion result; based on maximum entropy intuitionistic fuzzy clustering, performing association cost matrix calculation according to the feature fusion result to obtain an association cost matrix calculation result; judging whether the target object is associated with the observation object or not according to the association cost matrix calculation result, and if yes, updating a target model; and if not, performing target trajectory management on the target object.

The invention relates to a non local stereopair dense matching method based on image gray scale guiding. The non local stereopair dense matching method based on image gray scale guiding includes the steps: performing cost computation: taking an improved HOG operator as a cost measure, computing the cost between homonymous pixels, taking the cost as the means of describing the similarity between the homonymous pixels, and establishing a cost matrix; performing cost accumulation based on image gray scale guiding, and obtaining a stable cost accumulation result; according to a WTA strategy, obtaining an initial disparity image, rejecting a mis-matching point and an occulsion point, and obtaining a refined disparity image; and finally according to the disparity image, generating a dense high-precision three dimensional point cloud. The non local stereopair dense matching method based on image gray scale guiding fully considers the edge gray scale characteristics, has relatively high matching precision on the disparity edge, uses an eight-direction iterative cost accumulation mode so as to increase the matching robustness of a texture lacking area, and can quickly obtain a dense high-precision three dimensional point cloud, thus having great application prospect in the field of aerospace photogrammetry, low altitude photogrammetry and close-range photogrammetry, automatic driving of unmanned vehicle.

The invention belongs to the technical field of electronic countermeasures, and specifically relates to a passive multi-station multi-target direction-finding cross location method based on angle information. The passive multi-station multi-target direction-finding cross location method based on angle information includes the steps: by means of a multi-radiation-source data association algorithm,associating the observation data of multiple observation stations to obtain a cost matrix C(p,q), and then according to the obtained cost matrix C(p,q), estimating the target coordinates by means of ak-mean value++clustering algorithm. The passive multi-station multi-target direction-finding cross location method based on angle information has the advantages of being able to accurately associating the data of multiple stations and finally accurately estimate the position of the target, being simple, and having preferable effect.

A video encoder includes a motion search module that determines a motion search motion vector for a region of a selected picture of the plurality of pictures. The motion search module determines the region by merging selected ones of a plurality of blocks of the selected picture based on an evaluation of a cost matrix associated with the plurality of blocks of the selected picture.

The present invention relates to a contour chord angle feature based identification method for a blocked target. The method comprises: establishing a template library of local features of a plurality of target images; extracting a contour feature of a target edge; constructing a chord angle feature descriptor of each contour point; describing a blocked contour by using a self-containing attribute of the chord angle feature descriptor, to obtain a chord angle feature description matrix of contour segments; calculating distances between the chord angle feature descriptors of target image contour points and the chord angle feature descriptors of the contour points of the local feature in the template library by using an L1 measurement method, to obtain a matching cost matrix; and calculating a similarity of the matching cost matrix by using an integral graph algorithm, so as to identify a partially blocked object. According to the present invention, a contour space position feature of a target shape can be extracted, and blocked targets can be identified, and scale invariance, rotational invariance and translation invariance are achieved, thereby increasing the accuracy and robustness of target identification and shape search.

The invention discloses a method for calculating coverage radiation indexes of urban public facilities. The method comprises the following steps: step S1, acquiring urban basic data and introducing the urban basic data into a file geodatabase; step S2, thinning demographic spatial point data; step S3, establishing a network data set; step S4, creating an OD (origin-destination) cost matrix; step S5, splitting a field and associated attribute; step S6, calculating a service demand amount-resident demand amount ratio of a service point according to a service location; step S7, calculating a service demand amount-resident demand amount ratio of a settlement place according to a settlement location; step S8, summarizing the coverage radiation indexes of the urban public facilities and drawing a coverage radiation index map of the public facilities. By calculating the coverage radiation indexes of the urban public facilities such as schools, hospitals and cultural facilities within a certain radius, the equalization degree of the urban public facilities is reflected, and the service capacity of the urban public facilities within a certain spatial range is reflected.

The invention belongs to the technical fields of pattern recognition and computer vision, and particularly discloses a rapid graph matching and recognition method based on skeleton graphs. The graph recognition accuracy is guaranteed, and meanwhile the graph matching speed is increased. The rapid graph matching and recognition method includes the implementation steps of (1) extracting outlines of graphs through a classic canny edge detection operator; (2) sampling the outlines of the graphs at equal intervals; (3) splitting the graphs with the sampling points as peaks of triangles; (4) building the internal skeleton structure graphs of the graphs; (5) extracting feature vectors of the skeleton graphs of the graphs; (6) calculating a matching cost matrix of the graphs; (7) finding optimal matching points of the graphs; (8) rotating the skeleton structure graphs of the graphs, and repeating the step (6) and the step (7); (9) outputting the minimum matching cost for serving as the similarity distance of the graphs. By means of the rapid graph matching and recognition method, under the condition that the certain recognition accuracy is maintained, the complexity of a shape descriptor operator is effectively lowered, and the graph matching speed is increased.

The invention relates to a stereoscopic image redirecting method which comprises: firstly establishing an energy equation according to the texture similarity and parallax similarity of pixels; establishing a cost matrix M according to the established energy equation and selecting a line with the lowest energy cost by dynamic programming; combining depth information with a plane saliency map to obtain a stereoscopic saliency map; performing spatial coherence filtering on the saliency map to obtain a final importance image IM; allocating a scaling factor to a left view; finding out a corresponding relation between the pixels in the left view and a right view according to theparallax of left and right views, and obtaining the scaling factor of the pixels of the right view; according to the scaling factor of each, redirecting the image by using a pixel fusion algorithm to obtain a final redirected image. The stereoscopic image redirecting method can reduce visual distortion.

A method for automatic mismatch correction is presented. The method includes identifying a feature of interest in a reference image volume and a target image volume. Furthermore, the method includes computing a cost matrix based on one or more pairs of image slices in the reference image volume and the target image volume. The method also includes identifying one or more longest common matching regions in the reference image volume and the target image volume based on the computed cost matrix. In addition, the method includes aligning the reference image volume and the target image volume based on the identified one or more longest common matching regions. A non-transitory computer readable medium including one or more tangible media, where the one or more tangible media include code adapted to perform the method for automatic mismatch correction is also presented. Systems and non-transitory computer readable medium configured to perform the method for automatic mismatch correction of image volumes are also presented.

Systems and methods are provided for tracking moving objects. A sensor system is configured to measure a position of each of a plurality of moving objects as a set of measurements. A track assignment component is configured to accept the set of measurements from the sensor system and assign a subset of the measurements to respective tracks. The tracks represents the motion of respective objects. The track assignment component represents a cost calculation component configured to provide a cost matrix from at least a change point detection analysis of a feature associated with the set of measurements and an object assignment component configured to assign the subset of the measurements to respective tracks. A filtering component is configured to update respective associated states of tracks representing the plurality of moving objects according to the set of measurements and the assignment of the subset of the measurements to respective tracks.

The invention provides a method and a system for measuring ocean moving target track similarity, and belongs to the technical field of ocean moving target track detection. The method comprises: receiving historical track data; preprocessing the historical track data to form first track data; randomly selecting one piece of unselected second track data from a preset database, the second track datacomprising n vectors; forming a plurality of sub-sequences according to the selected second track data; for each sub-sequence, calculating the Euclidean distance between the vector of the sub-sequenceand the vector of the first track data to form a cost matrix; calculating a cumulative cost matrix according to the cost matrix; obtaining DTW distances between corresponding sub-sequences of the first track data and the second track data according to a calculation result of the cumulative cost matrix; whether the DTW distance is smaller than a preset distance threshold value or not is judged; and under the condition that it is judged that the DTW distance is smaller than a distance threshold value, the calculated DTW distance and the corresponding cumulative cost matrix are associated and stored.

The invention relates to a multi-situational data and cost-sensitive integrated model-based place personalized semantic identification method. The method is specifically implemented by the following steps of 1) extracting effective features from various situational data of use logs of a smart phone, discovering user activities in acceleration data through clustering, and establishing user activity features of high-situational-level places; 2) according to activity distribution of the places, calculating semantic similarity of the places to obtain a cost matrix; 3) performing modeling on the features of the places in combination with the cost matrix, and introducing label-free place data for performing semi-supervised learning to obtain a plurality of cost-sensitive base classifiers; and 4) integrating the base classifiers to output an identification model, and performing personalized semantic identification on the places accessed by users. According to the method, the personalized semantic identification of the places is performed in combination with situational perception, cost-sensitive learning and semi-supervised learning; and the method has a wide application prospect in the fields of pervasive computing, location-based services and the like.

A shipping option cost matrix may be generated based on the postal address codes, the carrier transit time data and the shipment rate cards. Responsive to receiving an order, the generated shipping option cost matrix may be searched in real-time to determine least costly delivery option, based on order information, the order information comprising a scheduled fulfillment center, destination, expected delivery date and weight of a shipment.