JP5002929B2 - Three-dimensional space analysis apparatus and program - Google Patents

Description

  The present invention relates to an apparatus and a program for realizing regional situation grasping by providing information based on spatial analysis on a three-dimensional map space.

  In recent years, development of 3D map data has progressed, and it has become widely available, such as being commercially available. These are roughly classified into feature data representing a three-dimensional shape such as a house and a building, and terrain data representing undulations on the ground surface. It is data that models the real world with high accuracy, including 3D polygon data with high position accuracy and shape accuracy by utilizing surveying technology and texture image data that expresses the surface state in detail. By simply displaying these data with CAD software etc., the real world can be virtually reproduced on a computer, and a simple landscape simulation such as how it looks when looking at a specific gaze direction from a specific viewpoint is possible. Become.

  Furthermore, it is possible to realize detailed understanding of the local situation by various analysis simulations using a spatial analysis function such as a geographic information system. For example, as a conventional technique for analyzing terrain data, displaying the result, and grasping the local situation, there is a visible region analysis for evaluating visible / invisible (or presence / absence of visibility) from a specified position (for example, Patent Document 1). . Further, there is a visual frequency analysis for evaluating “easy to see” from the surroundings regarding an object of interest such as a feature or topography (for example, Non-Patent Document 1).

JP-A-5-027676

Keiichi Oku et al., “Selection of Important Areas for Forest Landscape Management and Development of Classification Methods”, Forest Research Institute, 1996 Research Results Selection http://www.ffpri.affrc.go.jp/labs/kouho /seika/1996/96-17.html

  In the prior art, a three-dimensional space analysis function is often provided for each data type such as terrain and features, and it has been difficult to integrate and use these heterogeneous data for a three-dimensional space analysis. Also, the unit of 3D spatial analysis is a detailed area (partial area of each constituent polygon of 3D map data), and multiple types of spatial analysis results for each detailed area are combined in any combination, and further combined with 3D map data. Output was not considered. It is an object of the present invention to provide a three-dimensional space analysis apparatus and program that solve these problems.

  In order to achieve the above object, the outline of the invention disclosed in the present application will be described as follows. A means for building a cell by dividing each constituent polygon of a three-dimensional map into a plurality of planes and managing the cells in association with the constituent polygon, and generating analysis parameters for a three-dimensional space analysis including an analysis designated position based on an analysis instruction from a user Means for identifying the constituent polygons of the three-dimensional map to be analyzed based on the analysis parameters and constructing an indexed search table; means for executing a three-dimensional space analysis for the cell using the search table; A plurality of three-dimensional space analysis results associated with the cell, integrated management, a plurality of three-dimensional space analysis result combining and managing drawing parameters for combining, and the plurality of three-dimensional space analysis results based on the drawing parameters A unit for synthesizing the three-dimensional space analysis result, and further combining and outputting the synthesis output of the analysis result and the three-dimensional map data; And wherein the door.

  According to the present invention, three-dimensional map data of a plurality of types can be integrated and utilized by performing a three-dimensional space analysis using cells, and further, a detailed spatial analysis for a partial region in each constituent polygon can be performed. Become. Moreover, according to a user request | requirement, a some analysis result can be combined and displayed on the fly by arbitrary combinations, and those comprehensive evaluations etc. are attained. With the above configuration, a plurality of line-of-sight analysis results and the like can be provided as composite information in an arbitrary combination, and advanced spatial analysis such as visual frequency analysis and visible region analysis becomes possible.

  These effects enable detailed and high-speed spatial analysis of complex three-dimensional map spaces, provide immediate and highly visible information that meets various user requirements, and can effectively support user decision-making. .

  Hereinafter, an embodiment of the present invention will be described in detail with reference to the drawings. In the present application, examples of visible region analysis and visual frequency analysis mainly using line-of-sight analysis will be described, but the present invention is not limited to this embodiment, physical simulation such as parabolic motion, A combination of these multiple analysis methods may be used. Moreover, the analysis method combined and the number of results are not limited to those presented in the examples. In addition, the embodiment described below may be defined by a program that is read and executed by a computer, or is realized by hardware or cooperative processing of both (system, network service, etc.) ).

  FIG. 1 is a diagram illustrating an example of a functional configuration according to an embodiment of the present invention. The three-dimensional space analysis function 100 is connected to the following means and constitutes the entire system. That is, an input unit 101 such as a mouse or a keyboard that accepts input of analysis instructions and drawing parameter settings from the user, and an output of a monitor that outputs information obtained by synthesizing various analysis results and 3D map data to the user It is a three-dimensional map database 103 comprising means 102 and 3D shape data such as features and terrain that model a complicated spatial situation. Here, the three-dimensional map database 103 may be held in an external connection through an ODBC interface or the like, a connection through a network, or inside the three-dimensional space analysis function 100. Moreover, in order to integrate and use various types of 3D map data, a plurality of 3D map databases may be used in combination.

  The three-dimensional space analysis function 100 is configured by the following means. The cell construction means 110 reads the three-dimensional map data, and constructs a “cell” that is a basic element / minimum constituent unit for three-dimensional space analysis and analysis result management. The analysis parameter generation unit 111 generates an analysis parameter in response to an instruction operation from the user on the three-dimensional space data. Here, the analysis parameter specifies the contents of the analysis processing, such as the analysis designated position, the analysis altitude at the analysis designated position, the type of map object existing at the position, and the analysis direction calculated from the normal vector of the constituent polygon. Refers to a parameter. The search table construction means 112 identifies the constituent polygons of the map object to be subjected to spatial analysis according to the analysis parameters (analysis designated position, etc.), and constructs a search table in which they are structured, registered and indexed. The three-dimensional space analysis means 113 spatially analyzes the three-dimensional map data using various methods such as line-of-sight analysis and physical simulation using the search table. The analysis result management unit 114 integrates and manages a plurality of analysis results obtained by the three-dimensional space analysis unit in association with the cells. Thereby, the three-dimensional space analysis results from a plurality of designated positions, analysis results obtained by different analysis methods, and the like can be collectively managed, and various combinations can be used. The drawing parameter management unit 115 manages drawing parameters used when the plurality of analysis results are integrated and output for drawing. Here, the drawing parameter refers to a parameter that specifies the content of the drawing process, such as a combination calculation method of multiple analysis results and an expression method thereof. The composite output generation unit 116 combines the plurality of analysis results according to the drawing parameters, generates information by combining them, and further combines with the three-dimensional map data as necessary to output to the output unit 102. With the above configuration, a combination of a plurality of analysis results can be switched on-the-fly in accordance with a user operation (action) such as a three-dimensional space analysis or drawing parameter setting, and the combined result can be output.

  FIG. 2 is a diagram showing an example of the entire processing flow of the three-dimensional space analysis function in one embodiment of the present invention. First, three-dimensional map data is read from a three-dimensional map database and divided into partial areas to construct a cell for three-dimensional space analysis 200. In order to divide various types of 3D map data such as terrain, features, and virtual figures described later with reference to FIG. 22 into similar cells, in the subsequent analysis, the 3D map data is processed by targeting the cells. Integrated analysis can be handled in a unified manner without distinction. Thereafter, the presence / absence of an instruction from the user is determined, and the process waits until an instruction from the user is received. If there is an instruction from the user, the process branches according to the content 201. When an analysis instruction is received from the user, first, various analysis parameters related to the three-dimensional space analysis method, such as the analysis specified position specified in the three-dimensional map according to the instruction, the analysis altitude and the analysis direction at the position, are set. Generate 202. Subsequently, based on the analysis parameter, the constituent polygons of the map object are structured and indexed, and a search table that enables high-speed search in the spatial analysis processing is constructed 203. A three-dimensional space analysis is executed 204 using the analysis parameters and the search table. Further, when a drawing setting instruction is received from the user, drawing parameter setting is executed 205. In any case, a plurality of analysis results are collected in accordance with the drawing parameter to generate composite output data 206, and the result is output to the output means by the screen drawing output 207 to wait for an instruction from the user. Return. Further, when an instruction to change the viewpoint is received from the user, the screen drawing output is directly called 207 as simple redrawing 207.

Hereinafter, cell construction will be described with reference to FIG. 3 and will be described in detail with reference to FIGS.
FIG. 3 is a diagram showing an example of the cell construction processing flow (200) in the embodiment of the present invention. First, the 3D map data is read 300, and the analysis target range is limited 301 according to the memory capacity, processing performance requirements, etc. in order to reduce the amount of data handled. Subsequently, a loop is made for all map objects 302 and for all polygons 303 to construct cells. In other words, equidistant constituent points are arranged on each polygon, and a triangle is formed using them. For some constituent points that protrude outside the polygon, the entire polygon is filled with cells 305 by drawing it into the polygon. The generated cell group is stored 306 in association with the polygon in a table management format which will be described later with reference to FIG. By repeating the above procedure for all polygons 307 and further for all map objects 308, a cell construction process is realized. Finally, a memory is allocated according to the total number of generated cells, and a cell analysis result table for storing and managing the analysis results is constructed 309.

  Here, the cell size may be a preset value such as a system initial setting value, a setting input may be received from a user, or may be dynamically changed according to a user request regarding analysis accuracy. For example, the cell size is set small when detailed analysis is required, and the cell size is set large when high-speed analysis is required. In addition, various mesh division methods may be applied. For the analysis target range, use preset values such as system default values, accept setting input from the user, select a specific map leaf or mesh of 3D map data, or analyze memory capacity, etc. You may change dynamically according to the environmental condition of the computer which performs a process. Further, as will be described later with reference to FIG. 22, the three-dimensional map data to be cell-constructed is not limited to features and terrain, and may include virtual figures. In addition, as for topographic data, a DEM (Digital Elevation Model) other than a polygon may be used to convert a polygon by constructing a surface from three adjacent elevation points on the DEM, and a cell may be constructed using that. .

  FIG. 7 is a diagram showing an example of data hierarchy management in an embodiment of the present invention. Data is hierarchically managed in the form of a tree, and data indicating the overall situation corresponding to the root of the tree is a scene 700. The scene includes a scene 701 to be analyzed and a scene 702 not to be analyzed. The scene to be analyzed includes a large number of map objects 703 such as features and terrain to be analyzed, each map object includes a plurality of polygons 704, and each polygon includes a plurality of cells 705 ( Flow 306). Further, with respect to the analysis target scene 701, map objects are grouped for each zone 706, which is a space unit suitable for analysis, according to the spatial arrangement, and space indexing management is performed as a search table described later in FIG. With the above configuration, it is possible to appropriately limit the analysis target cells, and it is possible to speed up complicated three-dimensional space analysis processing. That is, instead of performing a complicated three-dimensional space analysis for all the cells, first, focusing on the zone and limiting the analysis range, the processing objects can be reduced. Furthermore, focusing on a polygon that is a parent element including a plurality of cells, a three-dimensional space analysis can be executed using the polygon as a representative figure (or a bounding volume in the CG field) as necessary. It is possible to select whether or not to perform a three-dimensional space analysis (detailed analysis) for each cell as a child element according to the analysis result of the polygon.

  FIG. 8 is a diagram showing an example of a data management format in one embodiment of the present invention. FIG. 8A shows a management format of the polygon shape 800, which manages a component point list for each component surface (polygon) of each map object. FIG. 8B shows a management format of correspondence 801 between polygons and cells, and a cell ID list is managed for each polygon. FIG. 8C shows a management form of the cell shape 802, in which the component point list is managed for each cell. FIG. 8D shows a management format of the cell analysis result 803, and a plurality of analysis results are integrated and managed for each cell. By integrating and managing a plurality of analysis results in association with cells, as described later in FIG. 16, they can be combined to generate integrated analysis results having various contents. Here, in the line-of-sight analysis and the like, the cell management of the presence or absence of the line-of-sight is performed as binary data of ON / OFF, but various types of data may be managed in the cell according to the analysis content. For example, continuous value data such as a distance from the analysis target position. If gradation representation is used in cell drawing, information can be provided to the user as high saturation at a short distance and low saturation at a long distance. As a result, it is possible to grasp not only the presence / absence of a line of sight but also the situation in consideration of the influence of the atmosphere, such as being easily visible or difficult to see.

  FIG. 9 is a diagram showing an example of cell construction in one embodiment of the present invention. FIG. 9A shows the feature data 900 to be analyzed, and FIG. 9B shows an example of a polygon 901 constituting the feature. FIG. 9C shows an example in which the cell 902 is constructed by dividing the polygon into detailed areas without any interruption. By adopting a triangle, which is the smallest structural unit of a surface figure, as the cell shape, high-speed and stable analysis and drawing processing can be realized. Of course, a polygon, a rectangle, a circle, or the like having an arbitrary number of constituent points may be used. With the cell configuration as described above, using cells as the basic unit and performing spatial analysis for each cell, details that target only the partial region of the polygon, not the spatial analysis of the entire feature or the entire constituent polygon Spatial analysis becomes possible.

  FIG. 9D shows an example in which the results of spatial analysis for each cell in FIG. 9C are stored and rendered. For example, in a line-of-sight analysis from the front of a feature, an obstacle or the like is present in front of the right side, and this corresponds to a spatial analysis result 910 in which only a partial range on the left side is visible. Similarly, FIG. 9E corresponds to a spatial analysis result 911 in which an obstacle or the like is present in front of the left side of the feature and only a partial range on the right side is visible. FIG. 9F is an example in which the spatial analysis results of FIG. 9D and FIG. If a plurality of spatial analysis results are combined and output by various operations such as addition (SUM calculation), information provided by combining the plurality of analysis results can be provided.

  FIG. 9G shows an example in which the cell frame is hidden and the feature is output, and the spatial analysis result by the addition (SUM calculation) in FIG. Thereby, it is possible to simultaneously grasp the spatial analysis result while grasping the detailed state of the feature including the texture and the fine structure. Since the spatial relationship between a specific position on the feature such as a specific window on the feature and the spatial analysis result can be directly grasped visually, it is possible to provide effective information for detailed city analysis and the like. Further, it is possible to change the drawing parameters as necessary by paying attention to the interaction of a plurality of spatial analysis results. For example, FIG. 9 (g) shows an addition (SUM operation), FIG. 9 (h) shows a logical output (AND operation) 921, and FIG. 9 (i) shows a logical output (OR operation) 922. It is the result. With the above configuration, it is possible to grasp the situation by synthesizing and outputting the situation analyzed from various viewpoints on the surrounding features in a complicated urban area. It is also possible to evaluate detailed analysis results at specific positions (such as windows and advertisement spaces) on the feature, and various applications such as evaluation of real estate value and examination of effective installation positions of outdoor advertisements are possible.

  As described above, by constructing the cell having the configuration described in FIGS. 3 and 7 to 9, all the subsequent analysis and drawing processes can be performed only on the cell. In addition, a plurality of spatial analysis results under various conditions can be integrated and managed in cells having the same structure. As a result, even in a data environment in which a plurality of types of map objects (features, topography, virtual figures, etc.) are mixed, integration processing can be performed with a consistent and simple functional configuration and man-machine interface. Further, the unit of the three-dimensional space analysis can be set as a detailed region (a partial region of each constituent polygon of the three-dimensional map data) while handling different types of three-dimensional map data in an integrated manner. In addition, since the method of spatial analysis and the management method of analysis results can be separated, not only multiple analysis results (such as line-of-sight analysis results from different positions) by the same space analysis method, but also different space analysis methods (line-of-sight analysis) And the results of physical simulation, etc.) can be integrated and managed in a common cell management system. As a result, advanced application based on a total of different types of spatial analysis methods is possible, such as a line-of-sight analysis range from the flying object and a liquid spraying range from the flight path of the flying object by physical simulation.

  The search table construction will be described below with reference to FIGS.

  FIG. 4 is a diagram showing an example of a search table construction processing flow (203) in one embodiment of the present invention. Here, the details of the search table will be described in detail with reference to FIGS. 7 and 10, but for each zone (for each unit direction, for example, every 30 degrees) according to the direction (azimuth angle) of the stereoscopic map data viewed from the analysis designated position By constructing a spatial index and registering the three-dimensional map data (and each constituent polygon) in ascending order of the distance, the three-dimensional map data existing in a specific direction can be searched at high speed.

  As a flow of the construction process, first, an analysis parameter (such as an analysis designated position serving as a center point of a search table) is acquired 400. Subsequently, based on the analysis parameters, the three-dimensional map data included in the analysis target range is acquired 401, 402 for all map objects, 403 for all polygons included in the map object, and a loop for all constituent points of the polygons. Rotate 404. The azimuth and distance of the constituent point as viewed from the analysis designated position are calculated, the rightmost and left (and upper and lower if necessary) azimuth angles are obtained 405, and the constituent point closest to the analysis designated position is obtained. Get the distance 406. The above procedure is repeated 407 for all constituent points, and an inclusion zone is specified 408 from the obtained azimuth angle. Depending on the situation, there are polygons that span multiple zones, but indexing registration 410 is performed so that all the inclusion zones are in ascending order of distance. Here, if necessary, hidden surface removal described later in FIG. 11 may be performed, and polygons that do not affect the analysis may be excluded from the table in advance 409. The above procedure is repeated 411 for all polygons, 412 for all map objects, and a search table is constructed. By utilizing the search table described above, high-speed processing can be performed even in a three-dimensional space analysis for detailed cells.

  FIG. 10 is a diagram showing an example of search table construction by the space division method in one embodiment of the present invention. At the time of the first analysis, as the preprocessing of the three-dimensional space analysis, the three-dimensional map data 1001 included in the analysis target range 1003 is read from the wide-area three-dimensional map data 1000. FIG. 10A shows an example in which the analysis designated position 1002 is explicitly designated manually, and an area of a given or arbitrary size is set as the analysis target range 1003 (flow 401). By using a high-speed search table structured by a quad tree or the like, the processing for searching or acquiring a three-dimensional map may be accelerated. In addition, the size of the analysis target range may be set using a predetermined value, manually set parameters, or automatically set according to conditions such as memory capacity. Further, the shape of the analysis target range may be a square or a circle that can be easily calculated, a rectangle that matches the mesh boundary of the 3D map data, or the like. As a result, in the subsequent search table construction and 3D space analysis, only the 3D map data in the range is targeted for analysis, so even if wide-area and large-capacity 3D map data is used, the data used for the analysis The amount can be reduced appropriately. As a result, the amount of calculation processing can be reduced, and high-speed analysis processing can be realized even in detailed analysis of a complex urban space. Here, this function was positioned as part of the search table construction, but it is not necessary to change the analysis target range every time the analysis specified position is specified, and the system initial setting position given in advance when the system is started can be used. It may be automatically specified by a space search function or the like. In general, since the 3D map database has a large capacity, a low-capacity 3D map data of the region of interest may be cut out using this function and stored in advance in a notebook PC or the like for mobile use.

  Furthermore, it is possible to realize high-speed processing in subsequent analysis by managing the three-dimensional map data in the analysis target range in a format that facilitates spatial analysis. In the example shown in FIG. 10B, the search table 1010 of the discrete polar coordinate system 1011 with the analysis designated position 1002 as the center is configured, and each constituent polygon of the three-dimensional map data in the analysis target range is classified by direction (discretely Indexed and registered (flow 408). In addition, stereoscopic map data extending over a plurality of zones is registered in duplicate in each zone. Thereby, in a spatial analysis in a specific direction centered on the analysis designated position, only the map object 1020 existing in the zone 1012 in the direction can be specified, and an efficient and high-speed spatial analysis process can be performed. In addition, the feature may be indexed by sorting in order of distance (flow 410). This allows limited access to only a group of features that are closer to the specified analysis position (center) than the target feature, and enables advanced spatial analysis such as line-of-sight analysis between the specified analysis position and the target feature. Can be realized.

  FIG. 11 is a diagram illustrating an example of hidden surface removal (flow 409) in polygon registration according to an embodiment of the present invention. FIG. 11A and FIG. 11B are examples of backside removal in one map object. When the map object to be analyzed is composed of planar polygons and is a closed solid figure, the polygon 1101 on the front side of the object and the polygon 1102 on the back side when the line-of-sight vector 1100 direction is viewed from the analysis designated position. Exists. When performing a linear three-dimensional space analysis such as a line-of-sight analysis, the backside polygon may be excluded from registration targets when the search table is constructed. As a result, the number of polygons to be calculated in the subsequent spatial analysis can be reduced by nearly half, and the processing speed can be increased. Specifically, a normal vector is calculated for each polygon of each map object, and a polygon 1101 having a normal vector 1103 whose angle formed with the line-of-sight vector 1100 is greater than 90 degrees is registered in the search table, and The polygon 1102 having the normal vector 1104 with an angle of 90 degrees or less may be removed as the back surface. Here, the above calculation can be easily realized by calculating the inner product of the vectors and determining the positive / negative.

  FIG. 11C and FIG. 11D are examples of hidden surface removal between a plurality of map objects. If the back side polygon 1111 is completely hidden by the near side polygon 1110, it is not registered in the search table, and only the polygon 1112 where at least a part is visible is registered in the search table. Here, when the polygon in front is a convex figure such as a rectangle that does not include a concave portion or a hole, the superposition of the polygons can be easily determined by the following determination process. That is, the rightmost azimuth angle 1121 and left azimuth angle 1122 of the near polygon with respect to the analysis designated position 1120 are calculated in advance, and if necessary, the upper azimuth angle and the lower azimuth angle are calculated. For all constituent points of the back side polygon 1111, the azimuth angle 1124 from the analysis designated position 1120 is obtained, and if these are all included in the arc 1123 of the front side polygon (both up and down, left and right), the back side polygon is completely Do not register in the search table as hidden. If the front polygon includes a recess or a hole, detailed determination processing similar to the subsequent space analysis processing is required, and therefore, it is assumed that it is unconditionally registered in the search table. In addition, when performing a three-dimensional space analysis by physical simulation such as parabolic motion, polygons that do not have a direct line of sight may be subject to analysis, and this is similarly registered in the search table. With the above configuration, map objects that do not affect the spatial analysis can be excluded from the analysis target in a city 3D map or the like in which polygons often have a rectangular shape, and the 3D space analysis process can be speeded up.

  Hereinafter, the three-dimensional space analysis will be described in detail with reference to FIGS.

  FIG. 5 is a diagram showing an example of the three-dimensional space analysis processing flow (205) in the embodiment of the present invention. First, an analysis parameter (an analysis position, an analysis altitude, an analysis direction, etc. generated according to an analysis instruction) is acquired and used for the subsequent analysis. Subsequently, a high-speed graphic search table constructed around the analysis designated position is acquired 501. 502 for all directions of the search table, 503 for all polygons in the direction, and further loop 504 for all cells of the polygon, and select a cell to be analyzed, and a line of sight connecting the cell and the analysis designated position Generate 505 a vector. Using the search table, a loop is performed 506 in order of increasing distance for the polygon existing between the target cell and the analysis designated position (front), and an intersection determination between the front polygon and the line-of-sight vector is performed 507. For the intersection determination, a method described later with reference to FIG. If there is no intersection, the intersection determination is repeated 508 for all the front polygons, and the analysis result is stored 509 in association with the cell, assuming that there is a line of sight when there is no loop (no polygon to be a shield). If there is an intersection, the loop processing is terminated assuming that the cell has no line-of-sight from the designated analysis position, and calculation is started for the next cell 510. The above procedure is repeated for all polygons 511, and further for all directions of the search table 512, thereby realizing a three-dimensional space analysis process.

  Here, when acquiring analysis parameters, it is determined whether the position specified by the user on the screen is a feature or terrain, and if it is terrain, the analysis altitude (human viewpoint or flying object) If the object is a feature, the analysis direction may be specified from the normal vector of the polygon constituting the feature. In particular, for flying objects, the flight altitude may be set in advance, or parameter input may be accepted on the spot. As described above, the processing content of the three-dimensional space analysis is dynamically switched according to the analysis parameter, so that the processing content suitable for the analysis designated position or the peripheral information can be selected without an explicit processing switching instruction. Can be executed. As a result, the operation instruction from the user has simple contents, and a complicated three-dimensional space analysis can be realized with a small number of operation procedures.

  As for analysis instructions, in addition to point input, a range having a spread may be specified by area input by mouse drag, selection input of an existing map figure (point, line, plane, solid), or the like. . In that case, a plurality of analysis designated positions may be equally arranged (or arranged according to a predetermined rule) within the range and managed as a group, and the three-dimensional space analysis may be executed for all analysis designated positions. Complex spatial analysis from lines, planes, solids, etc. can also be easily realized by substituting as a high-speed spatial analysis from a plurality of points and a combined display output of the plurality of analysis results. Thereby, as an example of spatial analysis from a line, a visible range from a road, a railroad, a flying route of a flying object, etc., or a visible range of an infrastructure facility such as an electric wire or a pipeline can be calculated.

  FIG. 12 is a diagram showing an example of hierarchical polygon analysis and cell analysis in an embodiment of the present invention. In the line-of-sight analysis, intersection determination between the line-of-sight vector 1200 from the analysis designated position generated in the flow 505 and the attention map object 1201 is frequently performed (flow 507). In order to increase the processing efficiency, as described above with reference to FIG. 7, the map object, polygon, and cell are used in a hierarchical manner according to the processing level. For example, if it is desired to specify the presence or absence of intersection for a map object in front of the cell of interest by using intersection determination, if each polygon 1202 constituting the map object is used as a representative figure instead of a cell, the relationship of the number of polygons << the number of cells Therefore, it is possible to determine the presence or absence of an intersection at high speed. In addition, when the intersecting polygon 1203 is found, the presence / absence of the intersection can be specified, and the processing for other polygons belonging to the same map object can be terminated. Further, when performing a line-of-sight analysis on a map object from the analysis designated position, for each cell 1204 belonging to each polygon belonging to the map object, when a polygon 1203 intersecting the line-of-sight vector 1200 is found on the near side of the target cell, It can be specified that there is no prospect (flow 507). Here, as an actual intersection determination process, an intersection 1205 between the plane including the polygon 1203 and the line-of-sight vector 1200 is calculated, and it is determined whether the intersection is included in the polygon.

  FIG. 13 is a diagram illustrating an example of a cell analysis method according to an embodiment of the present invention. In the three-dimensional space analysis using cells, ideally, it is necessary to determine the intersection between a triangular prism (three-dimensional polygon) composed of the cell and the analysis designated position and another polygon. However, the determination of the intersection between a three-dimensional polygon and a planar polygon has a heavy processing load, and it is inefficient to execute the processing for all cells. Therefore, the cell is virtually regarded as a point (hereinafter referred to as an analysis point), a line-of-sight vector connecting the analysis point in the cell and the analysis designated position is generated (flow 505), and the line-of-sight vector intersects with another polygon. A three-dimensional space analysis is realized by the determination (flow 507). Here, the following methods can be considered for the arrangement of analysis points in the cell. FIG. 13A shows an example in which spatial analysis such as line-of-sight analysis is performed by paying attention to a representative point (such as the center of gravity) 1301 of the cell 1300. Since processing is simplified by approximating a single cell, high-speed processing is possible even in a three-dimensional space analysis using complicated three-dimensional map data such as an urban area (a large number of cells). However, if the cell is not sufficiently small, the analysis accuracy may be lowered, for example, the processing result may be inconsistent at the cell edge. FIG. 13B is an example in which spatial analysis such as line-of-sight analysis is performed by paying attention to each constituent point 1302 of the cell 1300. When the cell is sufficiently small, the calculation is almost the same as that when the triangular prism is used, and high-precision spatial analysis can be performed by detailed calculation. However, there is a problem that three times the processing is required as compared with the case of one-point approximation. In addition, one cell composing point 1302 may be selected as a representative point 1301 according to a predetermined rule, or analysis points may be randomly arranged in the cell. These may be freely selected by the user according to the needs and usage scenes.

  Hereinafter, the combined output will be described in detail with reference to FIGS.

  FIG. 6 is a diagram showing an example of the combined output processing flow (206) in one embodiment of the present invention. First, a cell analysis result table is acquired 600, and further drawing parameters 601 are acquired. 602 for all the cells, an operation for combining the plurality of analysis results stored in the cell analysis result table based on the drawing parameters is executed 603, the result is stored in the drawing buffer 604, and this is repeated 605 . Finally, if necessary, all elements of the drawing buffer are checked to obtain a maximum value and the like, brightness normalization is performed 606, and generation as synthesized output data is completed 607.

  FIG. 14 is a diagram illustrating an example of a cell drawing method according to an embodiment of the present invention. FIG. 14A shows an example in which a cell is drawn 1400 in a single color by flat shading or the like. A high-speed drawing process is possible, and even a computer (such as a notebook PC) equipped with a graphic board with a low processing capability can realize a system with good response performance to user instructions. One analysis result obtained by the representative point analysis method shown in FIG. 13A can be used as a drawing color, or a plurality of analysis results shown in FIG. good. FIG. 14B shows an example in which a cell is drawn 1401 with gradation by smooth shading or the like. Even in the case where the cell size is large by combining with the component point analysis method shown in FIG. 13B and color designation using the analysis result at each component point, the analysis result is smooth and natural in continuous tone. Drawing is possible. Similar to the cell analysis method described above with reference to FIG. 13, these methods may be freely selected by the user according to needs and usage scenes.

  FIG. 15 is a diagram illustrating an example of drawing parameter setting according to an embodiment of the present invention. Drawing parameters can be set succinctly by using multiple simple interfaces for each individual function. FIG. 15A shows an example of an interface 1500 for setting ON / OFF of display of analysis results. FIG. 15B shows an example of an interface 1501 for setting display ON / OFF for each analysis result group in which a plurality of analysis results are collected. When analysis results from a plurality of points are grouped together and analyzed from lines, surfaces, or solids, the setting operation can be performed in groups. FIG. 15C shows an example of an interface 1502 for setting a color composition calculation method. Various calculation methods such as arithmetic operation (addition SUM) and logical operation (logical sum OR, logical product AND) can be selected and used, and the user can grasp the local situation from various viewpoints by changing the expression method of the analysis result. It becomes possible. For example, the visibility analysis can be realized by specifying the addition SUM calculation for the line-of-sight analysis results from a plurality of points on the road, and the visible region analysis can be realized by specifying the logical OR operation. Further, in the AND operation, only a range that is visible from the entire road can be specified, and useful information for an installation plan of an outdoor signboard or the like can be provided. As a result, it is possible to realize comprehensive landscape evaluation from various viewpoints in a single system or interface. FIG. 15D shows an example of an interface 1503 for setting a color arrangement table. Arbitrary color information can be selected and output, such as grayscale expression and luminance temperature expression. FIG. 15E shows an example of an interface 1504 for setting a spatial analysis method. A spatial analysis method such as a line-of-sight analysis or a spatial simulation can be selected, and related information such as a default color scheme corresponding to each analysis method can be set at the same time. By setting different color schemes for each method in advance, it is possible to provide information with high visibility even in a result of integrating a plurality of types of analysis methods. In this way, a part of the analysis parameters such as the analysis method can be set uniformly with the same procedure or interface as the drawing parameter setting, so that the analysis method can be used in the same manner as drawing ON / OFF of the analysis result and color setting. Can be easily switched, and an intuitive and highly operable system can be realized. In addition to selecting a spatial analysis method, an interface configuration to which an analysis function such as a plug-in format can be added is also possible.

  FIG. 16 is a diagram illustrating an example of the combined output process according to the embodiment of the present invention. According to the procedure described so far, a plurality of analysis results are associated with each cell and registered and managed as the cell analysis result 803. The cell analysis result is combined with the drawing parameter 1600 (flow 603), and the result is drawn into the drawing buffer 1601. (Flow 604). With the above configuration, arbitrary analysis results can be freely selected from a plurality of analysis results and combined on the spot, and the integrated analysis result that immediately reflects the combination result can be synthesized and output on the fly. In addition, it is possible to provide information with high visibility by using the color composition calculation method of these multiple analysis results and drawing parameters such as a color arrangement table suitable for the expression.

  In the following, from FIG. 17 to FIG. 21, a description will be given based on a specific screen image from analysis instruction on the screen to composite output of the analysis result, taking as an example the perspective analysis in the city three-dimensional map space.

  FIG. 17 is a diagram illustrating an example of an analysis instruction on a three-dimensional map according to an embodiment of the present invention. By using the screen 1700 of the output means as a man-machine interface that receives operations and analysis instructions from the user, an intuitive analysis instruction operation 1701 can be performed by a mouse double-click input on the screen. Complex three-dimensional space analysis such as line-of-sight analysis from a specific position or line-of-sight analysis from a specific window on a feature can be easily executed. Specifically, coordinate conversion from the image coordinate system that has received the input of the analysis instruction to the 3D map space coordinate system is executed, and the analysis designated position on the 3D map data is specified. Next, an analysis parameter such as the analysis designated position or its peripheral information is acquired and used for the subsequent three-dimensional space analysis.

  Here, input means other than a pointing device such as a keyboard may be used. For example, information such as an address, a specific feature name, a viewpoint position, and a line-of-sight direction may be key-inputted, and the position may be indirectly specified by converting the information into position information. In addition to receiving a direct instruction operation, the analysis may be performed by specifying the position mechanically through analysis record log information or a script. Further, the plane map interface 1710 can be used as necessary, and the analysis instruction operation can be performed from any interface. This can be realized by sharing the three-dimensional map space used for the three-dimensional space analysis between the interfaces and expressing it in a plane map by orthographic projection or the like.

  FIG. 18 is a diagram illustrating an example of terrain designation analysis according to an embodiment of the present invention. When the analysis designated position by the analysis operation instruction 1701 described above with reference to FIG. 17 is terrain data in the three-dimensional space map data, an analysis parameter corresponding to the attribute of the terrain data is generated to execute the three-dimensional space analysis. For example, the analysis altitude is set to the ground surface altitude + α according to the analysis content, and the analysis parameter is generated by moving the analysis designated position vertically upward. That is, in the case of analysis from the viewpoint of a person, (analysis designated position = ground surface height + average height−position from the top of the head to the eye) may be used. In the case of analysis from a vehicle, an analysis parameter that takes into account the design viewpoint altitude is generated. In the case of analysis from a flying object, a predetermined flight altitude may be used, or parameters may be input and received on the spot. Further, by displaying the terrain symbol information 1800 according to the analysis instruction or the analysis parameter content, the analysis target may be terrain, and the analysis parameter content such as the analysis designated position and the analysis altitude may be presented to the user. . By analyzing and outputting the analysis result on the three-dimensional map data, it is possible to clearly grasp the range 1801 where there is a line of sight from the designated landform position and the range 1802 where there is no line of sight. Also, the same symbol information and analysis result may be output on the planar map interface 1710 to realize multifaceted situation grasp.

  FIG. 19 is a diagram illustrating an example of feature designation analysis according to an embodiment of the present invention. When the analysis designated position according to the analysis operation instruction 1701 described above with reference to FIG. 17 is feature data in the three-dimensional space map data, an analysis parameter corresponding to the attribute of the feature data is generated to execute the three-dimensional space analysis. . For example, a normal vector is acquired for the target polygon of the target feature, and an analysis parameter such as an analysis direction is generated from the normal vector. That is, if the analysis is a line-of-sight analysis from a window on the side of the feature, the processing direction of the three-dimensional space analysis is not limited to 360 degrees in all directions, but limited to a hemispherical direction that is 180 degrees outward from the wall surface. Further, by displaying the feature symbol information 1900 in accordance with the contents of the analysis instruction or analysis parameter, the analysis target is the feature, the analysis designated position and the analysis direction (normal vector direction of the feature side surface), etc. The contents of the analysis parameter may be presented to the user. Here, in order to emphasize the symbol 1900 of the three-dimensional space analysis result that is currently output, other symbols associated with the three-dimensional space analysis for the past implementation may be switched to the non-highlighted symbol information 1903 and displayed. . By combining and outputting the analysis result on the three-dimensional map data, it is possible to clearly grasp the range 1901 where there is a line of sight from the designated feature position and the range 1902 where there is no line of sight.

  FIG. 20 is a diagram illustrating an example of combination analysis by arithmetic operation according to an embodiment of the present invention. According to the present technology, analysis results from different analysis methods or positions such as an analysis result 1801 from the ground (terrain) as shown in FIG. 18 and an analysis result 1901 from a feature as shown in FIG. Since they are integrated and managed in association with cells, they can be used in combination. At that time, by combining and outputting by arithmetic operation (addition SUM) and light / dark color expression, an area 2000 where there is an overlap of a plurality of analysis results (area where there is a line of sight from multiple places) 2000 is a bright color and no overlap A region (region where there is no line of sight from a plurality of locations) 2001 can be expressed as a dark color. Thereby, the visual frequency analysis in landscape analysis can be easily realized by combining and outputting a plurality of line-of-sight analysis results.

  FIG. 21 is a diagram illustrating an example of combination analysis by a logical operation according to an embodiment of the present invention. In FIG. 20, an arithmetic operation is used to combine a plurality of analysis results, but if a logical operation (logical product AND) is used, only a portion where a plurality of analysis results overlap can be expressed as a composite. Accordingly, while using the same analysis result as in FIG. 20, it is possible to clearly distinguish and confirm the region 2100 where the multiple analysis results overlap and the region 2101 where there is no overlap, and easily realize the visible region analysis from a plurality of locations. .

  FIG. 22 is a diagram showing an example of analysis using a virtual figure in one embodiment of the present invention. As shown in FIG. 22A, various applications are possible by constructing a cell including a virtual figure 2202 in addition to normal terrain data 2200 and feature data 2201. For example, in an application example such as an action plan for a flying object flying at a specific altitude, a virtual plane is created at the specific altitude, and line-of-sight analysis from the ground is also performed on the cells on the virtual plane. As shown in FIG. 22B, it is possible to provide support information including the presence / absence of visibility to the ground target (spatial analysis result) 2210. From this, the shortest path connecting the region (such as the center of gravity) where the multiple analysis results overlap and the position of interest may be generated and used as the movement route 2211 or the like. In addition, by using virtual figures such as plane polygons with a specific shape, solid polygons in a specific space, and a spherical surface formed on a distance of a specific radius from a specific position, landscape simulations regarding buildings of arbitrary shapes (viewing frequency) Analysis).

  FIG. 23 is a diagram illustrating an example of a three-dimensional symbol according to an embodiment of the present invention. By using 3D graphics and dynamically switching the symbol shape, orientation, color, etc. according to the content of the analysis instruction or the content of the generated analysis parameter, the symbol can be understood at a glance. For example, since some of the analysis parameters are automatically generated by internal processing, the contents thereof may be particularly shown to the user. In addition, when the analysis target is complicated 3D map data, the user may not know whether or not the instruction can be input as intended in the mouse operation on the 3D map data. It may be shown to the user. FIG. 23A is an example of the symbol 2300 in the line-of-sight analysis from the terrain data, and the analysis altitude may be indicated by the height of the symbol. FIG. 23B is an example of the symbol 2301 in the line-of-sight analysis from the feature data, and the analysis direction may be indicated by the direction of the symbol. FIG. 23C is an example of the symbol 2302 in the line-of-sight analysis from the flying object, and the analysis direction may be indicated by the direction of the symbol. Of course, symbols having a simple configuration that only indicates the contents of analysis instructions (analysis positions) such as text and 2D graphics, or combinations thereof may be used. Further, the symbol may be used not only as a display but also as an operation interface. For example, the drawing position may be moved to the analysis designated position in the three-dimensional map space by an operation such as double-clicking on the symbol in the line-of-sight analysis result, and the drawing line of sight may be moved in the analysis direction to redraw. Thereby, the analysis result can be evaluated and verified from various viewpoints from various viewpoints. With the above configuration, the visibility and operation response of the system can be improved.

  FIG. 24 is a diagram illustrating an example of a three-dimensional space analysis service according to an embodiment of the present invention. The three-dimensional space analysis method described so far has been an example of a single system. However, if this technology is applied, it is also possible to provide information via a network such as a client server or a Web application. For example, an analysis instruction 2410 is transmitted from the client 2401 via the network 2400 to the three-dimensional space analysis function 100 serving as a server. A three-dimensional map database 103 is connected to the server side, a three-dimensional space analysis is executed using the three-dimensional map data, and an analysis result 2411 is returned. Here, it is good also as a structure which distributes a three-dimensional space analysis function to a client side as a program, and uses a three-dimensional map database on a client side. Moreover, it is good also as a structure which distributes a three-dimensional space analysis result not only via a network but via a medium. With the above configuration, a three-dimensional space analysis service can be realized.

The example of a function structure in one Embodiment of this invention. The example of the whole processing flow of the three-dimensional space analysis function in one Embodiment of this invention. The example of the cell construction process flow in one Embodiment of this invention. The example of the search table construction process flow in one Embodiment of this invention. The example of the three-dimensional space analysis processing flow in one Embodiment of this invention. The example of the synthetic | combination output process flow in one Embodiment of this invention. . The example of the data hierarchy management in one Embodiment of this invention. The example of the data management format in one Embodiment of this invention. The example of cell construction in one embodiment of the present invention. The example of the search table construction by the space division method in one Embodiment of this invention. An example of hidden surface removal in polygon registration in one embodiment of the present invention. The example of the hierarchical polygon analysis and cell analysis in one Embodiment of this invention. The example of the cell analysis method in one Embodiment of this invention. The example of the cell drawing method in one Embodiment of this invention. 6 is a drawing parameter setting example according to an embodiment of the present invention. The example of the synthetic | combination output process in one Embodiment of this invention. The example of the analysis instruction | indication on the three-dimensional map in one Embodiment of this invention. The example of the terrain designation | designated analysis in one Embodiment of this invention. The example of the feature specification analysis in one Embodiment of this invention. The example of the combination analysis by the arithmetic operation in one Embodiment of this invention. The example of the combination analysis by the logical operation in one Embodiment of this invention. The example of the analysis using the virtual figure in one Embodiment of this invention. The example of the solid symbol in one Embodiment of this invention. The example of the three-dimensional space analysis service in one Embodiment of this invention.

Explanation of symbols

DESCRIPTION OF SYMBOLS 100 ... Three-dimensional space analysis function, 101 ... Input means, 102 ... Output means, 103 ... Three-dimensional map database, 110 ... Cell construction means, 111 ... Analysis parameter generation means, 112 ... Search table construction means, 113 ... Three-dimensional space analysis means, 114 ... Analysis result management means, 115 ... Drawing parameter management means, 116 ... Synthesis output generation means, 200 ... Cell construction, 201 ... User instruction presence / absence determination, 202 ... Analysis parameter generation, 203 ... Search table construction, 204 ... Solid space analysis 205 ... Drawing parameter setting, 206 ... Composite output generation, 207 ... Screen drawing output, 300 ... Three-dimensional map data reading, 301 ... Analysis target range setting, 302 ... Loop 1 for all map objects, 303 ... Loop 2 for the map object For all polygons, 304 ... equidistant triangle arrangement, 05: Pulling out non-polygon configuration points, 306: Stored correspondence between generated cells and polygons, 307 ... Loop 2 end, 308 ... Loop 1 end, 309 ... Cell analysis result table construction, 400 ... Analysis parameter acquisition, 401 ... Analysis target range 3D map data acquisition, 402 ... Loop 1 for all map objects, 403 ... Loop 2 for all polygons of the map object, 404 ... Loop 3 for all constituent points of the polygon, 405 ... Rightmost / left / upper / lower angle Acquisition, 406 ... Acquisition of shortest distance, 407 ... Loop 3 end, 408 ... Inclusive zone (group) identification, 409 ... Hidden surface deletion determination, 410 ... Distance ascending order table registration, 411 ... Loop 2 end, 412 ... Loop 1 end, 500 ... Analysis parameter acquisition, 501... Search table acquisition, 502... Loop 2 For all polygons in this direction, 504... Loop 3 For all cells of the polygon, 505... Generate a line-of-sight vector connecting the specified position and the cell. 506. Crossing determination of front polygon and line-of-sight vector, 508... Loop 4 end, 509... Cell analysis result storage, 510... Loop 3 end, 511. Drawing parameter acquisition, 602..., Synthetic output calculation, 604... Drawing buffer storage, 605. Loop 1 end, 606 .. luminance normalization, 607 .. composite output data generation, 700. Analysis target scene, 702 ... Scene not to be analyzed, 703 ... Map object, 704 ... Polygon 705 ... cell, 706 ... zone, 800 ... polygon shape, 801 ... polygon cell correspondence, 802 ... cell shape, 803 ... cell analysis result, 900 ... feature data, 901 ... polygon, 902 ... cell, 910 ... spatial analysis Result: 911 ... Spatial analysis result, 912 ... SUM operation composite output, 920 ... SUM operation feature translucent composite output, 921 ... AND operation feature translucent composite output, 922 ... OR operation feature translucent composite output, 1000 3D map data, 1001 ... Analysis target range 3D map data, 1002 ... Analysis designated position, 1003 ... Analysis target range, 1010 ... Search table, 1011 ... Discrete polar coordinate system, 1012 ... Zone, 1020 ... Map object, 1100 ... Gaze vector, 1101 ... Front side polygon, 1102 ... Back side polygon, 1103 ... An angle formed by 90 degrees or more Line vector, 1104 ... Normal vector with an angle of 90 degrees or less, 1110 ... Front polygon, 1111 ... Back side polygon, 1112 ... Partially visible polygon, 1120 ... Analysis specified position, 1121 ... Right azimuth, 1122 ... Left azimuth Angle, 1123 ... Arc, 1124 ... Azimuth angle, 1200 ... Gaze vector, 1201 ... Map object, 1202 ... Polygon, 1203 ... Intersection polygon, 1204 ... Cell, 1205 ... Intersection, 1300 ... Cell, 1301 ... Cell representative point, 1302 ... Cell composing point, 1400 ... cell single color drawing, 1401 ... cell gradation drawing, 1500 ... analysis result display ON / OFF setting interface, 1501 ... analysis result group display ON / OFF setting interface, 1502 ... color composition calculation method setting Interface, 1503 ... Color scheme Bullet setting interface, 1504 ... Spatial analysis method setting interface, 1600 ... Drawing parameter, 1601 ... Drawing buffer, 1700 ... Screen, 1701 ... Analysis instruction operation, 1710 ... Plane map interface, 1800 ... Symbol information for terrain, 1801 ... Outlook A certain range, 1802 ... a range without a line of sight, 1810 ... a plane map interface, 1900 ... a symbol information for a feature, 1901 ... a range with a line of sight, 1902 ... a range without a line of sight, 1903 ... a non-highlighted symbol information, 1910 ... a plane map Interface: 2000 ... Area with multiple analysis result overlap, 2001 ... Area without multiple analysis result overlap, 2010 ... Plane map interface, 2100 ... Area with multiple analysis result overlap, 2101 ... Multiple analysis results Area without overlap, 2110 ... Plane map interface, 2200 ... Terrain data, 2201 ... Feature data, 2202 ... Virtual figure, 2203 ... Analysis specified position, 2210 ... Spatial analysis result, 2211 ... Movement path, 2300 ... From the topography Symbols 2301 ... Symbols from features 2302 ... Symbols from flying objects 2400 ... Network 2401 ... Clients 2410 ... Analysis instructions 2411 ... Analysis results

Claims (7)

Means for dividing each constituent polygon of the three-dimensional map into a plurality of planes to construct a cell and managing it in association with the constituent polygon;
Means for generating an analysis parameter for a three-dimensional space analysis including an analysis designated position based on an analysis instruction from a user;
Means for constructing a search table indexed by identifying the constituent polygons of the three-dimensional map to be analyzed based on the analysis parameters;
Means for performing a three-dimensional space analysis on the cells associated with the constituent polygons included in the search table using the search table;
Means for associating and managing a plurality of results of the three-dimensional space analysis in association with the cell;
Means for managing drawing parameters for combining a plurality of three-dimensional space analysis results;
Synthesizing a plurality of stereo spatial analysis result based on the image drawing parameters, the three-dimensional spatial analysis apparatus characterized by comprising: means for displaying by synthesizing the three-dimensional map. Dividing each constituent polygon of the three-dimensional map into a plurality of planes to construct a cell and managing it in association with the constituent polygon,
Based on the analysis instruction from the user, generate analysis parameters for the 3D space analysis including the analysis specified position,
Based on the analysis parameters, build a search table that is indexed by identifying the constituent polygons of the 3D map to be analyzed,
Performing a three-dimensional space analysis on the cells associated with the constituent polygons included in the search table using the search table;
A plurality of the results of the three-dimensional space analysis are integrated and managed in association with the cell,
Managing drawing parameters for combining a plurality of three-dimensional space analysis results,
A plurality of the three-dimensional space analysis results are synthesized based on the drawing parameters,
A program for causing a computer to execute a three-dimensional space analysis method for combining and displaying the combined output of the analysis result and the three-dimensional map.   3. The program according to claim 2, wherein the symbol information indicating the specified position and the contents of the analysis parameter is combined and displayed on the three-dimensional map. 4. The program according to claim 3 , wherein the corresponding symbol information is switched according to the plurality of three-dimensional space analysis results to be displayed.   The program according to any one of claims 2 to 4, wherein the three-dimensional map includes a virtual figure, and the cell is constructed also for the virtual figure.   Display a three-dimensional map or a two-dimensional map on the display means, accept an analysis instruction from the user via the three-dimensional map or two-dimensional map displayed, and output the three-dimensional space analysis result on the three-dimensional map or two-dimensional map The program according to any one of claims 2 to 5, wherein:   7. The program according to claim 2, wherein the analysis instruction is instructed by inputting point data, line data, surface data, or three-dimensional data, or by specifying existing map data.

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