Point location judgment method applied to visual map rendering technology

Abstract

The invention discloses a point location judgment method applied to a visual map rendering technology, and belongs to the technical field of map rendering, in visual map rendering, a target point makes a horizontal ray towards one direction, if the number of intersection points between the ray and a map boundary is an odd number, it is indicated that the point is in a map area, and if the number of intersection points between the ray and the map boundary is not an odd number, it is indicated that the point is in the map area. For a large-scale point location judgment task, a spatial index technology is adopted, and in the method, coordinates of a central point are determined based on four parameter points including a longitude minimum value, a latitude minimum value, a longitude maximum value and a latitude maximum value; the method comprises the following steps: calculating angles between coordinates of a central point and longitude and latitude points of a map boundary according to a trigonometric function formula, storing the angles into longitude and latitude data of each point, obtaining an angle relationship at one time, obtaining the angle data of each point in a production environment, calculating an angle value target theta between the central point and a target point in the same way, and obtaining the angle relationship between the target point and the central point. And the longitude and latitude points are traversed circularly, and only the left and right longitude and latitude points of the target theta are left.

Description

Technical Field

[0001] The present invention belongs to the field of map rendering technology, and in particular relates to a point determination method applied in visual map rendering technology. Background Art

[0002] The point determination method used in visual map rendering technology mainly involves how to determine whether a point is located in a specific area on the map.

[0003] Generally, there are tens of thousands of longitude and latitude points involved in map drawing, especially in cities with many islands like Wenzhou and Zhoushan, there may be tens of thousands of longitude and latitude points. According to the principle of ray method, it is necessary to calculate the value of the intersection based on the target point and two adjacent points in the longitude and latitude data according to trigonometric functions. The calculation will be done as many times as there are longitude and latitude points. The huge amount of calculation puts a lot of pressure on the CPU.

[0004] Based on this, the present invention designs a point determination method applied to visual map rendering technology to solve the above problems. Summary of the invention

[0005] The purpose of the present invention is to solve the problem that there are tens of thousands of longitude and latitude points involved in general map drawing, especially in cities with many islands like Wenzhou and Zhoushan, there are tens of thousands of longitude and latitude points. According to the principle of the ray method, it is necessary to calculate the value of the intersection according to the target point and two adjacent points in the longitude and latitude data according to trigonometric functions. The number of calculations is the same as the number of longitude and latitude points, and the huge amount of calculations puts a lot of pressure on the CPU. A point judgment method applied to visual map rendering technology is proposed.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions:

[0007] A point determination method applied to visual map rendering technology, comprising:

[0008] In visual map rendering, a horizontal ray is drawn from the target point in one direction. If the number of intersections between the ray and the map boundary is an odd number, it means that the point is within the map area. For large-scale point position judgment tasks, spatial indexing technology is used;

[0009] If the number of intersections between the ray and the map boundary is even, it means that the point is outside the map range;

[0010] Determine point p3 through the y coordinate of the target point and the x coordinate of p1, and determine the position of the intersection based on the trigonometric function relationship. If the x coordinate of p4 is greater than the target point, the target point is determined to be within the region, otherwise the target point is outside the region. If the x coordinate of p4 is equal to the x coordinate of the target point, it means that the target point is point p4.

[0011] When the number of one-way intersections between the target point and the polygon is odd, a fixed target point is set in the area. In the actual scene, the target point may be on the left side of p1, between p1 and p2, or on the right side of p2.

[0012] As a further description of the above technical solution:

[0013] The polar coordinate method is used in the process of drawing the visualization map to exclude most of the points that do not need to be calculated, and all longitude and latitude data are traversed in a loop. The loop traversal is one-time, and the purpose is to extract polar coordinates for use in the production environment. The four parameters of the minimum longitude, the minimum latitude, the maximum longitude and the maximum latitude are extracted to form a polar coordinate matrix.

[0014] As a further description of the above technical solution:

[0015] The center point connection method is used in the process of drawing the visualization map:

[0016] Based on the four parameter points of minimum longitude, minimum latitude, maximum longitude and maximum latitude, determine the coordinates of the center point, calculate the angle between the coordinates of the center point and the longitude and latitude points of the map boundary according to the trigonometric function formula and store it in the longitude and latitude data of each point, and obtain the angle relationship once. In the production environment, obtain the angle data of each point, calculate the angle value targetθ between the center point and the target point in the same way, loop through the longitude and latitude points, and only leave the two longitude and latitude points on the left and right of targetθ;

[0017] Determine whether the target point is located inside the line connecting two adjacent points. If so, the point is within the map area, otherwise, it is outside the map area.

[0018] As a further description of the above technical solution:

[0019] The center point connection method includes:

[0020] Calculate the arc value between the center point and all the longitude and latitude points on the map boundary, sin(θ) = opposite side / hypotenuse, θ = arcsin(θ), and use the inverse trigonometric function to calculate the angle between all longitude and latitude points and the center point, and store it in the longitude and latitude data of the point, p(lon, lat, θ);

[0021] pointTarget, calculates the angle between the point and the target point in the same way, based on the stored latitude and longitude data of each point, that is, the stored angle relationship between each point and the center point, loops through all map boundary points, and finds the two adjacent points on the left and right of the target point according to the angle relationship. There must be two adjacent points, one with a smaller angle than the target point, and the other with a larger angle than the target point.

[0022] As a further description of the above technical solution:

[0023] Whether the target point is located inside the line connecting two adjacent points is determined as follows:

[0024] According to the coordinates of p1 and p2, θ4 is calculated, θ4 == θ5, the distance from the center point to p2 is known, and the length of L1 is calculated according to the angle between θ2 and θ5;

[0025] After calculating the length of L1, the distance L2 from the center point to the intersection of p1 and p2 is calculated based on θ1 and θ5. If this distance is less than the distance from the target to the center point, the target is judged to be outside the trajectory line, otherwise it is inside the trajectory line, that is, it is located in the map area.

[0026] As a further description of the above technical solution:

[0027] The spatial index technology is a data structure used for fast query of spatial data, including building a spatial index and querying a spatial index;

[0028] Build spatial index: First, you need to build a spatial index for the polygons on the map;

[0029] Query the spatial index: Then, based on the point information, query the spatial index to determine whether the point is located inside a polygon.

[0030] As a further description of the above technical solution:

[0031] The spatial index is constructed by using a quadtree index to grid the map space, and then recursively divide the geographic space into four parts to construct a quadtree until a self-set termination condition is met and the number of graphics elements associated with each node does not exceed a certain value.

[0032] As a further description of the above technical solution:

[0033] The quadtree index establishment step comprises:

[0034] Determine the root node MBR according to the spatial data range and establish the root node, and insert the polygon objects intersecting with the central axis of the root node into the corresponding bucket in order according to the type of intersection with the central axis;

[0035] Divide the node into 4 sub-quadrants according to the central axis and establish the corresponding sub-tree, store the polygons whose MBR is completely contained in the sub-quadrant range in the sub-tree, and set the clue pointer PPtr of the sub-tree to the parent node;

[0036] Repeat step 2 recursively for the four subtrees until the number of polygons in the subtree reaches the node splitting threshold, and obtain a quadtree index without containment relationship.

[0037] As a further description of the above technical solution:

[0038] For each polygon object, use PPtr to search for and identify the parent polygon towards the root, and add the polygon to the CPL pointer array of the corresponding inner ring of the parent polygon;

[0039] Scan the CPL and identify and insert virtual polygon objects based on the correspondence between the inner ring and the sub-polygon.

[0040] As a further description of the above technical solution:

[0041] The two-dimensional mapping algorithm based on the quadtree structure in the visual map drawing process:

[0042] Optimization model construction of ORB-SLAM,ORB-SLAM algorithm uses bundle adjustment method to optimize point positioning information,and gives priority to building sensor models of monitors for pixel points and,space points;

[0043] Z x,y =QWP α (1);

[0044] Among them, z represents the pixel depth value, P x,y represents the image pixel coordinates, Q is the internal parameter matrix of the monitor, W is the pose, P α is the world coordinate;

[0045] Formula (1) is expressed as k = h (i, l), and the observation k is the P of formula (1) x,y , (i,l) represent the pose W and map point P respectively α , introduce sensor observation error e = kh (i, l), that is, camera observation and calibration error, ORB-SLAM uses nonlinear graph optimization technology, the noise type can be ignored, during the operation of the system, the image is continuously loaded into the system over time, and the accumulated state is adopted (i 1 ,i 2 ,…,i n ,l 1 ,l 2 ,…,l m ) expression, because each frame contains a large number of observed map points, therefore, the number of l is greater than the number of i, that is, m>>n, and the cost function is established:

[0046]

[0047] to i t and l f Perform a first-order Taylor expansion:

[0048]

[0049] Among them, B t,f and E t,f is the Jacobian matrix.

[0050] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0051] 1. In the present invention, based on the four parameter points of minimum longitude, minimum latitude, maximum longitude and maximum latitude, the coordinates of the center point are determined, and the angles between the coordinates of the center point and the longitude and latitude points of the map boundary are calculated according to the trigonometric function formula and stored in the longitude and latitude data of each point. The angle relationship is obtained once. In the production environment, the angle data of each point is obtained, and the angle value targetθ between the center point and the target point is calculated in the same way. The longitude and latitude points are traversed in a loop, leaving only the two longitude and latitude points on the left and right of targetθ. This time, the loop traversal is only for comparing the angle values, and the performance loss is very small.

[0052] 2. In the present invention, for large-scale point judgment tasks, spatial index technology is used to improve processing efficiency. Spatial index is a data structure used to quickly query spatial data, which can improve the speed and accuracy of point judgment.

[0053] 3. In the present invention, the quadtree indexing technology is highly efficient for inserting, deleting and querying spatial data, and is particularly suitable for dynamic updating of spatial data. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 A schematic diagram of a point position determination method in a visual map rendering technology proposed by the present invention using a ray method to determine whether a point is within a map area;

[0055] Figure 2 A schematic diagram of a polar coordinate matrix in a point determination method applied to visual map rendering technology proposed by the present invention;

[0056] Figure 3 A schematic diagram of a point position determination method in a visual map rendering technology proposed by the present invention, using a center point connection method to determine whether a point is within a map area;

[0057] Figure 4 A schematic diagram of determining whether a target point is inside a line connecting two adjacent points in a point position determination method used in a visual map rendering technology proposed by the present invention DETAILED DESCRIPTION

[0058] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0059] Please see attached Figure 1 -Attached Figure 4 The present invention provides a technical solution: a point determination method applied to visual map rendering technology, comprising:

[0060] In visual map rendering, a horizontal ray is drawn from the target point in one direction. If the number of intersections between the ray and the map boundary is an odd number, it means that the point is within the map area. For large-scale point position judgment tasks, spatial indexing technology is used;

[0061] If the number of intersections between the ray and the map boundary is even, it means that the point is outside the map range;

[0062] Determine point p3 through the y coordinate of the target point and the x coordinate of p1, and determine the position of the intersection based on the trigonometric function relationship. If the x coordinate of p4 is greater than the target point, the target point is determined to be within the region, otherwise the target point is outside the region. If the x coordinate of p4 is equal to the x coordinate of the target point, it means that the target point is point p4.

[0063] When the number of one-way intersections between the target point and the polygon is odd, a fixed target point is set in the area. In the actual scene, the target point may be on the left side of p1, between p1 and p2, or on the right side of p2.

[0064] Specifically, Figure 2 As shown, the polar coordinate method is used in the process of drawing the visualization map to exclude most of the points that do not need to be calculated, and all the longitude and latitude data are traversed in a loop. The purpose of the loop traversal is one-time, and the purpose is to extract polar coordinates for use in the production environment. The four parameters of the minimum longitude, the minimum latitude, the maximum longitude and the maximum latitude are extracted to form a polar coordinate matrix.

[0065] Specifically, Figure 3 and Figure 4 As shown, the center point connection method is used in the process of drawing the visualization map:

[0066] Based on the four parameter points of minimum longitude, minimum latitude, maximum longitude and maximum latitude, determine the coordinates of the center point, calculate the angle between the coordinates of the center point and the longitude and latitude points of the map boundary according to the trigonometric function formula and store it in the longitude and latitude data of each point, and obtain the angle relationship once. In the production environment, obtain the angle data of each point, calculate the angle value targetθ between the center point and the target point in the same way, loop through the longitude and latitude points, and only leave the two longitude and latitude points on the left and right of targetθ;

[0067] Determine whether the target point is located inside the line connecting two adjacent points. If so, the point is within the map area, otherwise, it is outside the map area.

[0068] Specifically, Figure 3 and Figure 4 As shown, the center point connection method includes:

[0069] Calculate the arc value between the center point and all the longitude and latitude points on the map boundary, sin(θ) = opposite side / hypotenuse, θ = arcsin(θ), and use the inverse trigonometric function to calculate the angle between all longitude and latitude points and the center point, and store it in the longitude and latitude data of the point, p(lon, lat, θ);

[0070] pointTarget, calculates the angle between the point and the target point in the same way, based on the stored latitude and longitude data of each point, that is, the stored angle relationship between each point and the center point, loops through all map boundary points, and finds the two adjacent points on the left and right of the target point according to the angle relationship. There must be two adjacent points, one with a smaller angle than the target point, and the other with a larger angle than the target point.

[0071] Specifically, Figure 3 and Figure 4 As shown, whether the target point is located inside the line connecting two adjacent points is determined as follows:

[0072] According to the coordinates of p1 and p2, θ4 is calculated, θ4 == θ5, the distance from the center point to p2 is known, and the length of L1 is calculated according to the angle between θ2 and θ5;

[0073] After calculating the length of L1, the distance L2 from the center point to the intersection of p1 and p2 is calculated based on θ1 and θ5. If this distance is less than the distance from the target to the center point, the target is judged to be outside the trajectory line, otherwise it is inside the trajectory line, that is, it is located in the map area.

[0074] Specifically, the spatial index technology is a data structure for quickly querying spatial data, including building a spatial index and querying a spatial index;

[0075] Build spatial index: First, you need to build a spatial index for the polygons on the map;

[0076] Query the spatial index: Then, based on the point information, query the spatial index to determine whether the point is located inside a polygon.

[0077] Specifically, the spatial index is constructed by using a quadtree index, the map space is gridded, and then the geographic space is recursively divided into four parts to construct a quadtree until a self-set termination condition is reached and the number of graphics elements associated with each node does not exceed a certain value.

[0078] Specifically, the quadtree index establishment step includes:

[0079] Determine the root node MBR according to the spatial data range and establish the root node, and insert the polygon objects intersecting with the central axis of the root node into the corresponding bucket in order according to the type of intersection with the central axis;

[0080] Divide the node into 4 sub-quadrants according to the central axis and establish the corresponding sub-tree, store the polygons whose MBR is completely contained in the sub-quadrant range in the sub-tree, and set the clue pointer PPtr of the sub-tree to the parent node;

[0081] Repeat step 2 recursively for the four subtrees until the number of polygons in the subtree reaches the node splitting threshold, and obtain a quadtree index without containment relationship.

[0082] Specifically, for each polygon object, PPtr is used to search and identify the parent polygon toward the root, and the polygon is added to the CPL pointer array of the corresponding inner ring of the parent polygon;

[0083] Scan the CPL and identify and insert virtual polygon objects based on the correspondence between the inner ring and the sub-polygon.

[0084] Specifically, the two-dimensional mapping algorithm based on the quadtree structure in the visual map drawing process is:

[0085] Optimization model construction of ORB-SLAM,ORB-SLAM algorithm uses bundle adjustment method to optimize point positioning information,and gives priority to building sensor models of monitors for pixel points and,space points;

[0086] Z x,y =QWP α (1);

[0087] Among them, z represents the pixel depth value, P x,y represents the image pixel coordinates, Q is the internal parameter matrix of the monitor, W is the pose, P α is the world coordinate;

[0088] Formula (1) is expressed as k = h (i, l), and the observation k is the P of formula (1) x,y , (i,l) represent the pose W and map point P respectively α , introduce sensor observation error e = kh (i, l), that is, camera observation and calibration error, ORB-SLAM uses nonlinear graph optimization technology, the noise type can be ignored, during the operation of the system, the image is continuously loaded into the system over time, and the accumulated state is adopted (i 1 ,i 2 ,…,i n ,l 1 ,l 2 ,…,l m ) expression, because each frame contains a large number of observed map points, therefore, the number of l is greater than the number of i, that is, m>>n, and the cost function is established:

[0089]

[0090] to i t and l f Perform a first-order Taylor expansion:

[0091]

[0092] Among them, B t,f and E t,f is the Jacobian matrix.

[0093] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A point determination method applied to visual map rendering technology, characterized in that: include: In visual map rendering, a horizontal ray is drawn from the target point in one direction. If the number of intersections between the ray and the map boundary is an odd number, it means that the point is within the map area. For large-scale point position judgment tasks, spatial indexing technology is used; If the number of intersections between the ray and the map boundary is even, it means that the point is outside the map range; Determine point p3 through the y coordinate of the target point and the x coordinate of p1, and determine the position of the intersection based on the trigonometric function relationship. If the x coordinate of p4 is greater than the target point, the target point is determined to be within the region, otherwise the target point is outside the region. If the x coordinate of p4 is equal to the x coordinate of the target point, it means that the target point is point p4. When the number of one-way intersections between the target point and the polygon is odd, a fixed target point is set in the area. In the actual scene, the target point may be on the left side of p1, between p1 and p2, or on the right side of p2.

2. According to the point determination method applied to visual map rendering technology according to claim 1, it is characterized in that: The polar coordinate method is used in the process of drawing the visualization map to exclude most of the points that do not need to be calculated, and all longitude and latitude data are traversed in a loop. The loop traversal is one-time, and the purpose is to extract polar coordinates for use in the production environment. The four parameters of the minimum longitude, the minimum latitude, the maximum longitude and the maximum latitude are extracted to form a polar coordinate matrix.

3. According to claim 2, a point determination method applied to visual map rendering technology is characterized in that: The center point connection method is used in the process of drawing the visualization map: Based on the four parameter points of minimum longitude, minimum latitude, maximum longitude and maximum latitude, determine the coordinates of the center point, calculate the angle between the coordinates of the center point and the longitude and latitude points of the map boundary according to the trigonometric function formula and store it in the longitude and latitude data of each point, and obtain the angle relationship once. In the production environment, obtain the angle data of each point, calculate the angle value targetθ between the center point and the target point in the same way, loop through the longitude and latitude points, and only leave the two longitude and latitude points on the left and right of targetθ; Determine whether the target point is located inside the line connecting two adjacent points. If so, the point is within the map area, otherwise, it is outside the map area.

4. The point determination method used in visual map rendering technology according to claim 3 is characterized in that: The center point connection method includes: Calculate the arc value between the center point and all the longitude and latitude points on the map boundary, sin(θ) = opposite side / hypotenuse, θ = arcsin(θ), and use the inverse trigonometric function to calculate the angle between all longitude and latitude points and the center point, and store it in the longitude and latitude data of the point, p(lon, lat, θ); pointTarget, calculates the angle between the point and the target point in the same way, based on the stored latitude and longitude data of each point, that is, the stored angle relationship between each point and the center point, loops through all map boundary points, and finds the two adjacent points on the left and right of the target point according to the angle relationship. There must be two adjacent points, one with a smaller angle than the target point, and the other with a larger angle than the target point.

5. The point determination method used in visual map rendering technology according to claim 4 is characterized in that: Whether the target point is located inside the line connecting two adjacent points is determined as follows: According to the coordinates of p1 and p2, θ4 is calculated, θ4 == θ5, the distance from the center point to p2 is known, and the length of L1 is calculated according to the angle between θ2 and θ5; After calculating the length of L1, the distance L2 from the center point to the intersection of p1 and p2 is calculated based on θ1 and θ5. If this distance is less than the distance from the target to the center point, the target is judged to be outside the trajectory line, otherwise it is inside the trajectory line, that is, it is located in the map area.

6. The point determination method used in visual map rendering technology according to claim 5 is characterized in that: The spatial index technology is a data structure used for fast query of spatial data, including building a spatial index and querying a spatial index; Build spatial index: First, you need to build a spatial index for the polygons on the map; Query the spatial index: Then, based on the point information, query the spatial index to determine whether the point is located inside a polygon.

7. The point determination method used in visual map rendering technology according to claim 6 is characterized in that: The spatial index is constructed by using a quadtree index to grid the map space, and then recursively divide the geographic space into four parts to construct a quadtree until a self-set termination condition is met and the number of graphics elements associated with each node does not exceed a certain value.

8. The point determination method used in visual map rendering technology according to claim 7 is characterized in that: The quadtree index establishment step comprises: Determine the root node MBR according to the spatial data range and establish the root node, and insert the polygon objects intersecting with the central axis of the root node into the corresponding bucket in order according to the type of intersection with the central axis; Divide the node into 4 sub-quadrants according to the central axis and establish the corresponding sub-tree, store the polygons whose MBR is completely contained in the sub-quadrant range in the sub-tree, and set the clue pointer PPtr of the sub-tree to the parent node; Repeat step 2 recursively for the four subtrees until the number of polygons in the subtree reaches the node splitting threshold, and obtain a quadtree index without containment relationship.

9. The point determination method used in visual map rendering technology according to claim 8 is characterized in that: For each polygon object, use PPtr to search for and identify the parent polygon towards the root, and add the polygon to the CPL pointer array of the corresponding inner ring of the parent polygon; Scan the CPL and identify and insert virtual polygon objects based on the correspondence between the inner ring and the sub-polygon.

10. The point determination method used in visual map rendering technology according to claim 9, characterized in that: The two-dimensional mapping algorithm based on the quadtree structure in the visual map drawing process: Optimization model construction of ORB-SLAM,ORB-SLAM algorithm uses bundle adjustment method to optimize point positioning information,and gives priority to building sensor models of monitors for pixel points and,space points; fromP x,y =QWP α (1); Among them, z represents the pixel depth value, P x,y represents the image pixel coordinates, Q is the internal parameter matrix of the monitor, W is the pose, P α is the world coordinate; Formula (1) is expressed as k = h (i, l), and the observation k is the P of formula (1) x,y , (i,l) represent the pose W and map point P respectively α , introduce sensor observation error e = kj (i, l), that is, camera observation and calibration error. ORB-SLAM uses nonlinear graph optimization technology, and the noise type is negligible. During the operation of the system, the image is continuously loaded into the system over time, and the accumulated state is (i1, i2, ..., i n ,l1,l2,…,l m ) expression, because each frame contains a large number of observed map points, therefore, the number of l is greater than the number of i, that is, m>>n, and the cost function is established: to i t and l f Perform a first-order Taylor expansion: Among them, B t,f and E t,f is the Jacobian matrix.

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