30 results about "Trajectory compression" patented technology

The invention discloses a bus GPS correction method based on abnormal point elimination and a trajectory compression algorithm. The method comprises the following steps: step 1, acquiring historical GPS data of a specified bus route; step 2, performing filtration treatment on the acquired historical GPS data of the specified bus route by applying a local abnormal factor algorithm; step 3, simulating GPS trajectory data of the specified bus route; and step 4, based on the GPS coordinate point information of the specified bus route, performing trajectory correction on the real-time GPS data acquired from message-oriented middleware by utilizing the GPS trajectory data of the specified bus route, and taking the coordinate value of the midpoint of two coordinate points closest to the real-timeGPS point on the GPS trajectory of the specified bus route as a correction point of a bus GPS location drift point. The method provided by the invention can improve the accuracy of the GPS route point of a specific vehicle shift on a map location.

The invention discloses a trajectory preprocessing method for a taxi data set. The method comprises the steps of firstly obtaining trajectory data, wherein each sampling trajectory point comprises longitude, latitude and timestamp information; secondly analyzing the trajectory data, performing abstract storage in entity objects, numbering trajectories, and adding trajectory point IDs; thirdly searching for missing values of the trajectories, and supplementing the missing values by utilizing a linear interpolation method or a mean value method; fourthly clustering the trajectory points, detecting abnormal points, and accurately analyzing and processing the abnormal points; fifthly detecting a data redundancy region, extracting redundant data and performing trajectory compression; sixthly searching for the trajectory points at the corners in the trajectories, generating a corner point set, combining and adjusting the corner point set, and performing trajectory cutting according to the corner point set; and finally updating and outputting the trajectory information. According to the method, the missing values can be processed; the abnormal points can be detected and processed; and complex and overlapped trajectories can be cut.

The invention belongs to the field of ship data management, particularly relates to a ship trajectory data screening method and device, and aims at solving the problems that in an existing method, thejudgment precision of trajectory points is not high, and important trajectory points can be lost. According to the method, ship trajectory data stored in a period of time is used as to-be-screened data, a ship moving trajectory is used as a first to-be-tested curve, and a retention point of the first to-be-tested curve is determined through a Douglas algorithm; the ship moving track between two adjacent reserved points is taken as a second to-be-measured curve, and the reserved points are determined for each second to-be-measured curve through a method based on an angle limit value; and the information data of the track points corresponding to the reserved points obtained twice are taken as a data screening result. According to the method, the track compression precision is improved, andtrack points with large spatial feature information amount are greatly reserved; when the data in the track segment is screened, a multi-thread parallel computing method is adopted, so that the algorithm execution time is shortened, and the real-time data processing requirement is met.

The invention relates to the field of ship trajectory compression, in particular to a ship trajectory compression method based on course and navigational speed change rate, which comprises the following steps: step 1, AIS data processing: performing quality control on AIS data, and constructing a single-ship AIS time series data record; step 2, coordinate system conversion: converting longitude and latitude coordinates into coordinates under a Mercator coordinate system; 3, constructing a track compression model; ship trajectory feature points are extracted by taking the navigational speed change rate and the course change rate as indexes to compress ship trajectory data; by applying the method, effective compression of the ship trajectory data is realized, the constraint indexes of the compression method consider ship position information and own motion characteristics, the consistency of ship trajectory characteristics before and after compression is ensured, and a foundation is laidfor improving the mining efficiency based on the ship trajectory data.

The invention provides a geographic position trajectory optimization method and device, which can remove abnormal points in a trajectory. In addition, repeating points in the trajectory can be removed with a trajectory compression mode to achieve the purposes of reducing the network transmission pressure and saving the disk storage space. The method comprises the following steps: acquiring original geographical position trajectory data; removing the abnormal points in the original geographical position trajectory data to obtain a geographical position abnormal point removed trajectory; compressing the geographic position abnormal point removed trajectory to obtain a geographical position optimization trajectory.

The invention discloses a compression method and a decompression method of a handwritten terminal track, belonging to the field of image compression. The method for compressing the trajectory of the handwriting terminal includes: calculating the coordinate difference between the actual coordinates of each trajectory point and the predicted coordinates of the point; performing entropy encoding on the coordinate difference to obtain a code word to complete the compression of each trajectory. The decompression method of the trajectory of the handwriting terminal includes: performing entropy decoding on the saved codewords to obtain the coordinate difference between the actual coordinates of each trajectory point and the predicted coordinates of the point; obtaining the predicted coordinates of each trajectory point according to the predicted tap coefficient; The coordinate difference between the predicted coordinates and the actual coordinates of the point and the predicted coordinates of the point is used to obtain the actual coordinates of each track point. In the present invention, the correlation of the coordinates of the track points is utilized when compressing and encoding the track, which overcomes the disadvantage of large storage space caused by uniformly adopting fixed-length encoding to encode the track in the prior art.

The invention discloses a spatio-temporal trajectory compression method based on a trajectory dictionary, comprising two parts of establishing a trajectory dictionary set and performing trajectory compression based on the trajectory dictionary set. In this manner, for spatial trajectory data and temporal trajectory data, three methods of trajectory establishment and two algorithms of trajectory compression are proposed, which guarantee the compression rate, guarantee the high quality of trajectory compression, and have the advantages of high reliability and high accuracy. At the same time, themethod has a wide market prospect in database, data analysis, data mining, trajectory data query and analysis, and the application and popularization of trajectory data mining.

The invention relates to a spatio-temporal trajectory data compression processing method, which comprises the following steps of: splitting accessed data, and calculating a complete base station information table; grouping the data according to the device numbers, and sorting a plurality of copies of data in each group; generating a first track compressed data block and establishing parameter information; marking longitudes and latitudes of the track compression data blocks; performing iteration processing on each part of data in each group in sequence; establishing a plurality of track compressed data blocks and sequentially judging the type of each track compressed data block; calculating the time difference between two adjacent static data blocks to assign the time difference; and repeating the steps to complete the compression of each group of track compression data blocks in sequence. According to the method, the type of each track compressed data block is judged, and each dynamic data block is assigned according to the judged speed of each dynamic data block, so that the data can be efficiently compressed, the accuracy of extracting the characteristics of the compressed data can be ensured, and the accuracy of extracting the characteristics of the compressed data can be ensured. And the data compression efficiency of the method disclosed by the invention is effectively improved.

The embodiment of the invention provides a rapid track prediction method for a large-scale moving object, a medium and equipment. According to the invention, the pressure of large data volume is relieved through track compression, soft rewards and punishment measures are adopted, that is to say, after matching succeeds, the mean value of the Gaussian probabilities of two corresponding adjacent historical rule points is used as a similarity reward to prevent reward and punishment measures from being too sharp, so that track prediction accuracy is improved. After the compressed historical regular track with the highest similarity with the compressed current track is obtained, the real-time performance is improved through an interpolation completion method under the condition that the track prediction accuracy is not reduced.

The invention discloses a track compression method. Aiming at the defects in the prior art, the solution thought of the method is to globally optimize a feature trajectory sub-chain obtained by simplifying and compressing a line segment based on a global optimization thought, and comprehensively consider various influence factors such as a deviation angle, a vertical Euclidean distance, a trajectory segmentation number and the like; evaluation indexes capable of comprehensively reflecting space and time characteristics of a compression result are established, so that the contradiction between the compression efficiency and effective information retention and the contradiction between the compression efficiency and the original track as similar as possible are well balanced. The invention further discloses a track compression device. Compared with the prior art, the method and the device have the advantages that off-line compression that all tracks contain a large amount of effective information and are high in accuracy can be achieved, and the accuracy and efficiency of overall operation of track compression are improved.

A trajectory data compression method based on LSTM prediction and smooth analysis thoughts and a moving object trajectory data compression method based on LSTM prediction apply a deep learning model to the traditional trajectory compression field, use a neural network to predict and obtain a distance error and a direction error, and use a smooth analysis thought to determine a compression threshold. The method does not need manual setting of an error threshold value, considers the distance and the direction at the same time, fully retains important information of an original track, obtains the error and determines the error threshold value according to the characteristics of the compressed track compared with a traditional track compression algorithm, can be better suitable for track data with different characteristics; the problems that a traditional track compression algorithm is poor in compression effect, errors are manually found, and an error threshold setting experiment is tedious are solved.

In order to effectively solve the problem of multi-scale self-adaptation in track compression, the invention provides a rapid track compression method based on an effective distance, provides a new feature weighting method, takes the feature effective distance as a feature value of track compression, and can effectively measure the straightness of a track section in a specific time; parallel computing of track compression is supported, and the track compression efficiency can be improved; online compression is supported, and track drawing efficiency can be improved.

The invention discloses an indoor Wifi positioning data preprocessing and trajectory reconstruction method, comprising the following steps: A, defining an indoor space POI; B, extracting correspondingpositioning data according to mac, and forming a mac behavior trajectory, Strj = { p1..., pi, pj,...pn }; C, analyzing the signal loss and an AP point, and judging the invalid trajectory; D, intersecting trajectory points in the Strj trajectory with the indoor POI, ranking all points in the POI, and constructing a temporary trajectory sequence Strjtmp = { p1,..., pi,...pn }; E, merging the trajectory points in the same POI, namely only keeping the earliest and latest trajectory points in a continuous time period in the POI, reconstructing a trajectory Strjnew = { p1,..., pi,...pn }; F, mapping the trajectory data to a two-dimensional plane based on which the drift points and the jump points in the trajectory are deleted; and G, implementing step E again, and merging the trajectory pointsin the same POI, thus realizing trajectory compression, and completing the extraction of a new trajectory. According to the invention, indoor space characteristics and indoor trajectory characteristics are met, the result is reliable, and the processing efficiency is high.

The bus GPS deviation correction method based on abnormal point elimination and trajectory compression algorithm designed by the present invention comprises the following steps: Step 1: obtaining the historical GPS data of the designated bus route; Step 2: applying local The abnormal factor algorithm is used for filtering; Step 3: Simulate the GPS trajectory data of the specified bus route; Step 4: Based on the GPS coordinate point information of the specified bus line, use the specified bus route to real-time GPS data obtained from the message middleware The GPS track data of the bus is used for track correction, and the coordinate value of the midpoint of the two coordinate points closest to the real-time GPS point on the GPS track of the specified bus route is taken as the correction point of the bus GPS positioning drift point. The invention can improve the accuracy of the GPS route point on the map position of a specific vehicle shift.

The invention relates to a cosine vertical distance discrimination method, device and equipment for vector trajectory compression. The method comprises the following steps: firstly, acquiring an original vector trajectory data set, constructing a loop body, then sequentially taking three points to form a triple during circulation; and when the triple is processed, dividing each triple into two layers, wherein on the point level, the distance between the front and back adjacent edges of the middle element of the triad is taken as a condition, and the triad is identified to form a dense point set or a sparse point set, and on the online level, a local track formed by connecting triads in sequence is recognized as a curve line condition and a curve line condition through taking a cosine value as a judgment condition; and finally, judging whether the middle vertex elements in each condition are compressed or not further through different vertical distance threshold values d_max and d_min. In the whole processing process, various conditions are considered, a plurality of judgment values are used and work cooperatively, and finally each intermediate point element which does not meet the condition is compressed. Compared with an existing processing method, the invention has a better compression effect and a higher processing speed.

The invention provides a time trajectory representation and compression framework that can fully utilize data features, and relates to the field of trajectory compression, especially the compression of time trajectory. The large and redundant vehicle trajectory data leads to many overheads in data storage, communication and processing. Currently, raw trajectories are usually decomposed into spatial paths and time series. This paper proposes a new framework for time series compression, including a representation constructor and four compressors. Specifically, we first construct a time trajectory representation with four elements, which has low entropy and storage; then construct four compressors to compress the corresponding four types of elements respectively, and improve the compression efficiency.

The present application relates to a cosine vertical distance discrimination method, device and equipment for vector trajectory compression. Among them, the original vector trajectory data set is obtained first, and a loop body is constructed, and then three points are sequentially taken to form a triplet during the loop, and each triplet is divided into two levels when the triplet is processed. At the level, the distance between the front and rear adjacent sides of the middle element of the triplet is used as a condition to first identify the triplet as a dense point set or a sparse point set; at the online level, the cosine value is used as the judgment condition to recognize the local trajectory of the triplet in order There are two cases of curved line and curved line, and finally judge whether to compress the intermediate vertex elements in each case through different vertical distance thresholds d_max and d_min. The whole processing process considers multiple situations, uses multiple judgment values, and works together with each other, and finally compresses each intermediate point element that does not meet the conditions. Compared with the existing processing method, it has better compression effect and faster processing speed.

The invention discloses a ship trajectory compression method and system based on ship behavior characteristics, and the method comprises the steps: carrying out the preprocessing of missing value data in a ship trajectory, and constructing a feature matrix; performing density-based clustering on the feature matrix I by using a DBSCAN algorithm to obtain track fragments of different ship behaviors; using a k-Means method to divide the trajectory segment into an anchoring stage, a sailing stage and a fishing stage; and carrying out adaptive compression on the ship trajectory according to different behaviors. According to the method, effective compression of the ship trajectory data is realized, the specific behavior characteristics of the ship trajectory are considered in the compression method, the consistency of the characteristics of the ship trajectory data before and after compression is ensured, the compression of the ship trajectory data is also realized, and the fluency of trajectory query related functions of a ship management system is ensured.

The invention relates to a trajectory compression error evaluation method based on time synchronization speed, and belongs to the technical field of spatio-temporal data processing. The method comprises the following steps: firstly, reading data of a whole track, and respectively calculating speeds in longitude and latitude directions according to space-time positions of the track; compressing the track through various compression algorithms; and based on a speed linear change hypothesis, calculating an error between the time synchronization speed of each track point and the actual speed, and then calculating an average value to obtain a time synchronization speed error of the compressed track. According to the method, modeling is carried out on the speed error of the compressed track based on the speed linear change hypothesis, an SVE model is designed to evaluate the speed error of the compressed track compared with an original track, and the blank of lack of a speed error evaluation method in the current industry is filled. In addition, the evaluation method provided by the invention also has the advantages of small error influence, uniform change along with the compression ratio, strong performance and wider application.

The invention discloses a trajectory compression method, comprising: S1. Scanning the trajectory to be compressed to obtain a fixed point in the trajectory to be compressed; the trajectory is a path generated by a moving object moving in space, and the fixed point is the starting point of the trajectory, Road section intersection or end point; S2, query the pre-configured frequent successor table, and determine whether the successor of the fixed point in the trajectory to be compressed is the most frequent successor fixed point of the fixed point; the subsequent fixed point is the next fixed point adjacent to the fixed point; if so, then Execute step S3; S3, represent the most frequent subsequent fixed points with negative numbers to obtain a set of fixed points and negative numbers, which is the compressed trajectory. Correspondingly, the present invention also provides a method for decompressing the compressed track obtained by applying the above track compression method. By adopting the embodiment of the present invention, it is possible to perform lossless compression on a track with a high compression rate and high efficiency by using the track characteristics.

The invention discloses a trajectory compression method based on a sliding window. Firstly, the current trajectory point to be compressed in the sliding window and the vertical distance of a straight line from a reference trajectory point with a maximum offset distance to its initial trajectory point and an end trajectory point are respectively calculated; Then make a judgment: if any of these two distances is greater than the distance threshold for trajectory compression, add the current trajectory point to be compressed to the compressed trajectory set, and use the current trajectory point to be compressed as the start of the sliding window track point to set a new sliding window; otherwise, according to the size of the two distances, update the maximum offset distance reference track point, and move the current track point to be compressed and the end track point of the sliding window back by one position at the same time. The above processing is repeated until the compression of all track points is completed. The method can effectively speed up the track compression processing speed, improve the operation efficiency, and reduce the complexity of the algorithm.

The invention discloses a vehicle trajectory compression method based on sequence similarity. The method is as follows: 1) Synthesize the trajectory of vehicles with the same ID in unit time into a long trajectory; the long trajectory is Trajectory ID ={(l 1 ,t 1 ),(l 2 ,t 2 ),…,(l n ,t n )}, where the information collected for the nth time includes position l n , time information t n , denoted as the collection point (l n , t n ); 2) Cut the long trajectory according to the set speed threshold to obtain multiple segmented trajectories; 3) Based on the sequence similarity between the segmented trajectories, perform global trajectory compression on the long trajectory. The invention greatly saves storage overhead.

The invention relates to a method and device for detecting the dizziness degree of a user in a virtual environment and a storage medium, and belongs to the technical field of computers. The method comprises the steps that moving track information of the user in a three-dimensional space coordinate system of the virtual environment is acquired; the moving track information is processed based on a track compression algorithm to obtain compression ratio data and track compression ratio variable quantity data of the moving track information; the compression ratio data and the track compression ratio variable quantity data are input into a pre-trained dizziness degree estimation model to obtain a dizziness degree prediction result. The track compression data in the virtual environment is used as the input data of the vertigo degree estimation model, a user does not need to wear redundant sensors and does not need to be separated from the virtual environment, and the immersion experience of the user in the virtual environment is not affected. Moreover, the system completely depends on basic virtual reality equipment, does not need to additionally configure a sensor, simplifies the system structure, and has higher popularization and application potential.

The invention relates to a spatio-temporal trajectory aggregation pattern mining algorithm based on R* tree index, comprising three steps of trajectory compression, trajectory clustering and aggregation detection. The algorithm comprehensively utilizes the motion direction, motion speed and offset information of the trajectory data to compress the trajectory and improve the compression effect of the algorithm; uses the line segment DBSCAN based on the R* tree index to cluster the trajectory segments to improve the efficiency of the algorithm clustering. Relevant experiments show that the algorithm has improved mining effect compared with similar algorithms. The next work is to apply this algorithm to the actual trajectory data aggregation pattern mining task to improve the effect of data mining.

The invention discloses a spatiotemporal DP method based on extraction of ship trajectory feature points, which belongs to the technical field of ship trajectory compression. , and then remove the noise points; Step 2: Identify and retain the characteristic trajectory points such as the change of the ship's course, the speed of the ship, and the ship's entry and exit from a certain area; Step 3: Use the starting point and end point of the ship's trajectory and the characteristic trajectory points retained in Step 2. As the initial point, the AIS data is compressed while considering the spatiotemporal characteristics of the AIS data. The invention can effectively compress the redundant AIS data, the difference between the compressed ship trajectory and the original trajectory is very small, and at the same time, the information of the change point of the ship's motion state and the boundary point of the ship's entry and exit areas can be retained, and the reuse value space is large, and it can be used for the history of the ship. Data analysis and ship behavior identification lay the foundation for data processing.

The invention provides a space-time trajectory compression and segmentation state expression method and device. The method comprises the steps: extracting offline trajectories in batches; carrying outprimary filtering processing; constructing track point representation; carrying out secondary filtration and compression; and performing trajectory state expression based on the speed. The inventionprovides a space-time trajectory compression and segmentation state expression method and device, which not only can fully reserve the motion characteristics of the trajectory, but also can compress the redundant part of the trajectory, reduce the memory space, improve the efficiency of display expression, and solve the problem that part of trajectory characteristics are lost in the existing technical scheme.

The invention discloses a novel trajectory tracking method based on space-time constraint through a method in the field of network security. Comprising a moving object needing moving trajectory and a server for managing the moving object for moving trajectory tracking, and the server tracks the position of the current moving object and compresses the trajectory at the same time. Wherein moving objects located in a circular area, a strip-shaped area and a quasi-rectangular area are tracked and compressed by adopting an algorithm adapting to the quasi-rectangular area, and compressed track data meeting requirements are obtained and stored in a server. According to the method provided by the invention, a compression track meeting requirements is obtained while the position of a current moving object can be tracked by a server, and space-time constraints of circular, strip-shaped and quasi-rectangular regions are supported. And the time complexity and the space complexity are relatively low.

The present invention relates to an online track compression method and device, computer equipment and computer-readable storage medium. The method includes: intercepting a set of track points from an original track; initializing a current track to be compressed, and adding the starting point of the current track to be compressed In the compressed track; according to the starting point and end point of the current track to be compressed, traverse backward from the end point to the starting point, and check whether the track points in the current track to be compressed are compressible points one by one; if they are all compressible points, execute compression , move the starting point of the current track to be compressed to the track point where the end point of the current track to be compressed is located, and then move the end point of the current track to be compressed to the last track point in the group of track points; when it is checked that a track point is not a compressible point , then move the end point of the current track to be compressed to the track point that is not a compressible point; determine whether to end the compression. The present invention can process with constant time and space, and achieve higher compression ratio.

The invention relates to a processing method for compressing space-time trajectory data, comprising: splitting the accessed data to calculate a complete base station information table; grouping the data by device numbers and sorting multiple pieces of data in each group; generating a first One track compressed data block and establish parameter information; mark the latitude and longitude of the track compressed data block; sequentially perform iterative processing on each piece of data in each group; establish multiple track compressed data blocks and determine the type of each track compressed data block in turn; calculate The time difference between two adjacent static data blocks is assigned to it; the steps are repeated to complete the compression of each group of track compressed data blocks in sequence. The invention determines the type of each track compressed data block, and assigns value to each dynamic data block according to the speed of each dynamic data block after the determination, so that the data can be efficiently compressed while ensuring that the features of the compressed data are extracted. and the data compression efficiency of the method of the present invention is effectively improved.