Observation point determination device and observation point determination method

Abstract

To achieve optimization of an observation point so as to enable observing an observation target surely, while minimizing the number of observation points as much as possible.SOLUTION: An observation point determination device 1 comprises: a lattice surface preparation unit 13 that divides a surface of a structure of a target section to prepare a plurality of lattice surfaces; and a spatial lattice point preparation unit 16 that divides a space within the target section to prepare a plurality of spatial lattice points. The observation point determination device 1 comprises the minimum-number-of points determination unit 15 that determines the minimum number of points of the observation point successful in a reverse estimation estimating the observation target in reverse from an observation result at the observation point on the basis of the number of observation targets and the number of lattice surfaces. The observation point determination device 1 comprises: a direct arrival determination unit 17 that determines for each spatial lattice point whether a linear line connecting an arbitrary point of each lattice surface and the spatial lattice point directly arrives at the spatial lattice point, or not; and an observation point determination unit 19 that performs determination of the observation point on the basis of the minimum number of points of the observation point and a determination result of the direct arrival determination unit 17.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to an observation point determination device and an observation point determination method for determining an observation point for observing an observation target within a target area. [Background technology]

[0002] In the field of radiation measurement, when determining the locations and number of measurement points, locations that are likely to be contaminated by radioactive materials are often selected as measurement points based on empirical or legal standards, etc. However, since it is difficult to evaluate the rationality of the selection of measurement points, in the field of radiation measurement, it is common for the number of measurement points to be excessive or insufficient.

[0003] The difficulty of optimizing the measurement points is not limited to radiation measurement, but also applies to, for example, the installation of security cameras. One of the techniques for optimizing the installation points of security cameras is disclosed in, for example, Patent Document 1.

[0004] Patent Document 1 discloses a technology relating to an optimal placement search device that searches for optimal placement conditions for multiple placement objects to be placed on a predetermined target object. The technology disclosed in Patent Document 1 includes an evaluation means that calculates an evaluation value evaluating all placement conditions of one or more placement objects to be placed on the target object using range information that indicates the range of the target object and placement information that indicates the placement conditions of each of the multiple placement objects to be placed on the target object, and an evaluation means that sets each of the multiple placement objects as a target object and calculates an evaluation value of the target object according to an amount of change between an evaluation value calculated by the evaluation means when the multiple placement objects are placed on the target object and an evaluation value calculated by the evaluation means when the remaining placement objects excluding the target object are placed on the target object. The system includes a contribution degree calculation means for calculating a contribution degree; an update means for performing an update process for updating the placement conditions of each of the plurality of placement targets, the update process being such that the update of the placement conditions of the placement target with the smallest contribution degree, which has the smallest contribution degree, is made to a greater extent than the update of the placement conditions of placement targets other than the placement target with the smallest contribution degree; and an iterative determination means for outputting the placement conditions of each of the plurality of placement targets represented by the placement information as a search result for optimal placement conditions, the placement conditions being obtained by sequentially repeating the calculation of the contribution degree by the contribution degree calculation means, the update of the placement conditions by the update means, and the calculation of the evaluation value by the evaluation means. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] JP 2018-128961 A Summary of the Invention [Problem to be solved by the invention]

[0006] However, the technology disclosed in Patent Document 1 merely searches for optimal placement conditions for multiple placement objects by changing the update of the placement conditions of the placement object with the smallest contribution, which has the smallest contribution, more than the update of the placement conditions of placement objects other than the placement object with the smallest contribution. In other words, the technology disclosed in Patent Document 1 has difficulty in correcting an excess or shortage of the number of multiple placement objects.

[0007] In the field of radiation measurement, if there are too many measurement points in a high-dose area, not only will the measurement take time and effort, but it will also lead to an increase in the amount of radiation exposure, and if there are not enough measurement points, it will hinder the estimation of the radiation source. Therefore, in the field of radiation measurement, it is desirable to minimize the number of measurement points so that the radiation source can be inversely estimated from the radiation measurement results. This also applies to the optimization of the installation points of surveillance cameras. In other words, there is room for improvement in the technology disclosed in Patent Document 1 in terms of optimizing the measurement points related to radiation measurement and the observation points such as the installation points of surveillance cameras.

[0008] The present invention has been made in consideration of the above, and aims to provide an observation point determination device and an observation point determination method that can optimize observation points so as to reliably observe the observation target while minimizing the number of observation points. [Means for solving the problem]

[0009] In order to solve the above problems, the observation point determination device of the present invention is an observation point determination device that determines an observation point for observing an observation target within a target area, and is characterized in that it comprises a lattice surface creation unit that divides the surface of a structure in the target area to create a plurality of lattice surfaces; a spatial grid point creation unit that divides the space within the target area to create a plurality of spatial lattice points; a minimum point number determination unit that determines the minimum number of observation points at which inverse estimation of the observation target from the observation results at the observation points is successful, based on the number of the observation targets and the number of the lattice surfaces; a direct determination unit that determines for each spatial lattice point whether a straight line connecting any point on each lattice surface and the spatial lattice point directly reaches the spatial lattice point; and an observation point determination unit that determines the observation point based on the minimum number of points of the observation point and the determination result of the direct determination unit.

[0010] With this configuration, the observation point determination unit can determine observation points so that the observation target within the target area can be observed thoroughly while minimizing the number of observation points. Therefore, the observation point determination device can optimize the observation points so that the observation target can be observed reliably while minimizing the number of observation points.

[0011] In a further preferred embodiment, the observation point determination unit has a first determination unit that determines the spatial lattice point having the largest number of lattice faces that the straight line directly reaches as the observation point, and a second determination unit that identifies the lattice faces that the straight line does not directly reach for the spatial lattice point determined as the observation point, and determines other spatial lattice points that the straight line from the identified lattice faces reaches directly as the observation point, and the second determination unit continues to determine the observation points until the number of observation points determined by the first determination unit or the second determination unit becomes greater than or equal to the minimum number of points.

[0012] With this aspect, the observation point determination unit can ensure the minimum number of observation points required for successful inverse estimation of the observation target from the observation results, while keeping the number of observation points as small as possible. Therefore, the observation point determination unit can determine observation points so as to reliably prevent an insufficient number of observation points from interfering with the estimation of the observation target, while keeping the number of observation points as small as possible. Therefore, the observation point determination device can further optimize the observation points so as to reliably observe the observation target while keeping the number of observation points as small as possible.

[0013] In a further preferred embodiment, the second determination unit continues determining the observation point until there is no lattice plane on which the straight line does not directly reach the spatial lattice point determined for the observation point.

[0014] With this aspect, since straight lines reach the observation points directly from all lattice planes, the observation point determination unit can determine the observation points so that the observation target in the target area can be observed without blind spots. Therefore, the observation point determination unit can determine the observation points so that the observation target in the target area can be observed more thoroughly while minimizing the number of observation points. Therefore, the observation point determination device can further optimize the observation points so that the observation target can be reliably observed while minimizing the number of observation points.

[0015] In a further preferred embodiment, the number of observation targets is n s where m is the number of lattice planes, p is the minimum number of points, and α is a constant predetermined according to the structure of the target area, then the minimum number of points determination unit determines the minimum number of points using equation (1).

[0016]

number

[0017] With this aspect, the minimum point number determination unit can determine the minimum point number p so as to reliably secure the minimum number of observation points required for successful inverse estimation of the observation target from the observation results. Therefore, the observation point determination unit can determine the observation points so as to minimize the number of observation points while reliably securing the minimum number of observation points required for successful inverse estimation of the observation target from the observation results. Therefore, the observation point determination device can further optimize the observation points so as to reliably observe the observation target while minimizing the number of observation points.

[0018] In a further preferred embodiment, the observation target is a radiation source present in the target area, the observation result is a measurement result of radiation emitted from the radiation source, and the observation point is a measurement point of the radiation.

[0019] With this aspect, the observation point determination device can reliably prevent an excessive number of radiation measurement points, which would result in the labor and effort required for measurement and an increase in the amount of radiation exposure. In addition, the observation point determination device can reliably prevent an insufficient number of radiation measurement points, which would interfere with the estimation of the radiation source. Therefore, the observation point determination device can optimize the radiation measurement points so that the radiation source can be reliably estimated while minimizing the number of radiation measurement points.

[0020] In a further preferred embodiment, the observation target is a monitored object present in the target area, the observation result is an image captured by a surveillance camera monitoring the monitored object, and the observation point is the installation point of the surveillance camera.

[0021] With this aspect, the observation point determination device can reliably prevent the installation of an excessive number of surveillance cameras, which would result in the time and effort required for installation. In addition, the observation point determination device can reliably prevent the installation of an insufficient number of surveillance cameras, which would result in blind spots in the target area and hinder the monitoring of the monitored object. Therefore, the observation point determination device can optimize the installation points of the surveillance cameras so that the monitored object can be reliably monitored while minimizing the number of surveillance cameras installed.

[0022] In addition, the observation point determination method of the present invention is an observation point determination method for determining an observation point for observing an observation object within a target area, and is characterized in that it comprises the steps of: dividing the surface of a structure in the target area to create a plurality of lattice planes; dividing the space within the target area to create a plurality of spatial lattice points; determining the minimum number of observation points at which inverse estimation of the observation object from the observation results at the observation points is successful based on the number of the observation objects and the number of lattice planes; determining for each spatial lattice point whether a straight line connecting any point on each lattice plane and the spatial lattice point directly reaches the spatial lattice point; and determining the observation point based on the minimum number of observation points and the determination result of whether the straight line reaches directly.

[0023] With this configuration, the observation point determination method can determine observation points so that the observation target within the target area can be observed thoroughly while minimizing the number of observation points. Therefore, the observation point determination method can optimize the observation points so that the observation target can be reliably observed while minimizing the number of observation points. Effect of the Invention

[0024] According to the present invention, it is possible to provide an observation point determination device and an observation point determination method that are capable of optimizing observation points so as to reliably observe an observation target while minimizing the number of observation points. [Brief description of the drawings]

[0025] [Figure 1] FIG. 1 is a diagram showing the configuration of an observation point determination device according to an embodiment of the present invention. [Diagram 2] FIG. 1 is a diagram showing the relationship between a source vector, a dose vector, and a matrix. [Diagram 3] FIG. 1 shows an example of a 3D CG model of a target area. [Figure 4] 4A to 4C are diagrams for explaining a lattice surface created by a lattice surface creating unit. [Diagram 5] 6A and 6B are diagrams for explaining the processing content of a direct path determination unit; [Figure 6] 5A to 5C are diagrams for explaining the processing content of an observation point determination unit. [Figure 7] 4 is a flowchart showing an outline of processing performed by an observation point determination device. [Figure 8] 8 is a flowchart showing an outline of a process carried out subsequent to that in FIG. 7; DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0026] Hereinafter, embodiments of the present invention will be described with reference to the drawings. Components with the same reference numerals in each embodiment have the same functions in each embodiment unless otherwise specified, and description thereof will be omitted.

[0027] FIG. 1 is a diagram showing the configuration of an observation point determination device 1 of this embodiment. FIG. 2 is a diagram showing the relationship between a radiation source vector ω, a dose vector y, and a matrix X. FIG. 3 is a diagram showing an example of a 3D CG model of a target area. FIG. 4 is a diagram explaining a lattice plane created by the lattice plane creation unit 13. FIG. 5 is a diagram explaining the processing contents of the direct hit determination unit 17. FIG. 6 is a diagram explaining the processing contents of the observation point determination unit 19.

[0028] The observation point determination device 1 is a device equipped with a system for determining observation points for observing observation targets within a target area. Determining observation points means determining the positions and number of observation points. The target area is the area for which observation points are to be determined. The target area is, for example, a radioactive contaminated area such as a nuclear power plant where a radioactive material leak accident has occurred and its surrounding area. In this case, the observation target is a radiation source present in the target area. The observation results are the measurement results of radiation emitted from the radiation source. The radiation measurement results are, for example, radiation amounts such as spatial dose rates. The observation points are the points where radiation is measured.

[0029] The target area may also be a surveillance area monitored by a surveillance camera or the like to prevent, for example, the theft of parts and the intrusion of suspicious individuals. This surveillance area includes general facilities as well as areas where radioactive materials are stored. In this case, the observation target is a surveillance object that exists in the target area, such as an item containing radioactive material or a suspicious individual. The observation result is an image captured by a surveillance camera monitoring the surveillance object. The observation point is the installation point of the surveillance camera.

[0030] In this embodiment, the inside of a nuclear power plant building with a complex structure is taken as an example of the target area, a radiation source present in the target area is taken as an example of the observation target, the measurement results of radiation emitted from the radiation source are taken as an example of the observation point, and the measurement point of the radiation is taken as an example.

[0031] In the field of radiation measurement, if there are too many measurement points in a high-dose area, not only will the measurement take time and effort, but it will also lead to an increase in the amount of radiation exposure, and if there are not enough measurement points, it will be difficult to estimate the radiation source. Therefore, in the field of radiation measurement, it is desirable to keep the number of measurement points as small as possible so that the radiation source can be inversely estimated from the radiation measurement results. This inverse estimation can be achieved by the following method using sparse modeling.

[0032] That is, in the inverse estimation method, a radiation source vector ω is created which indicates a radiation source assumed to exist in a plurality of regions (also called meshes, grids, or elements) obtained by dividing the target area. The radiation source vector ω is a column vector whose element values ​​are the intensity of radiation emitted from the radiation source set in each region, and whose element number is m, the number of all radiation sources set. Furthermore, in the inverse estimation method, a dose vector y is created which indicates a measured value obtained by measuring the radiation dose at a plurality of measurement points. The dose vector y is a column vector whose element values ​​are the measured values ​​at each measurement point, and whose element number is p, the number of measurement points. Furthermore, in the inverse estimation method, a matrix X (also called a contribution rate matrix X) which indicates the degree to which the radiation emitted from the radiation source indicated by the radiation source vector ω to the measurement point contributes to the measured value is calculated. The matrix X is a p×m matrix which corresponds to the number m of radiation sources indicated by the radiation source vector ω and the number p of measurement points. In the inverse estimation method, it is assumed that the radiation source vector ω, the matrix X, and the dose vector y have a relationship as shown in the following formula (2) as shown in FIG. 2.

[0033]

number

[0034] In the target area, high-intensity radiation sources are often sparsely present, so in this inverse estimation method, the radiation source vector ω is treated as a sparse vector. Then, in this inverse estimation method, the radiation source vector ω is restored using LASSO (Least Absolute Shrinkage and Selection Operator), which searches for a radiation source vector ω that minimizes the objective function D shown in the following equation (3).

[0035]

number

[0036] As a result, the inverse estimation method can accurately estimate the distribution of radiation sources in the target area from a small number of radiation measurement results. However, as described above, if the number of measurement points is insufficient, the inverse estimation will be unsuccessful, which will hinder the estimation of the radiation source. Therefore, the observation point determination device 1 determines the radiation measurement points (observation points) so that the radiation source can be inversely estimated from a small number of radiation measurement results.

[0037] The observation point determination device 1 is configured by a so-called computer system. The observation point determination device 1 includes an input device 2, a communication device 3, a storage device 4, a display device 5, and a calculation processing device 10. The input device 2 is configured by a keyboard or a mouse, etc. The communication device 3 is configured by a communication device that communicates with external devices via a network. The storage device 4 is configured by an SSD or HDD, etc. The storage device 4 stores various data, etc. used in the processing of the calculation processing device 10. The display device 5 is configured by various displays, such as a liquid crystal display, that display the processing results, etc. of the calculation processing device 10. The calculation processing device 10 is configured by a CPU, a ROM, a RAM, etc. The calculation processing device 10 realizes various functions of the observation point determination device 1 by the CPU executing programs stored in the ROM.

[0038] The hardware configuration of the observation point determination device 1 is not particularly limited to the configuration shown in Fig. 1. Some of the functions of the arithmetic processing device 10 may be realized in cooperation with an external computer connected to the communication device 3 via a computer network.

[0039] The calculation processing device 10 includes a target area information acquisition unit 11, a model creation unit 12, a lattice surface creation unit 13, an observation target information acquisition unit 14, a minimum point number determination unit 15, a spatial lattice point creation unit 16, a direct determination unit 17, a determination vector creation unit 18, an observation point determination unit 19, and an output unit 20.

[0040] The target area information acquisition unit 11 acquires information regarding the structure of the target area (hereinafter also referred to as "target area information"). The target area information is, for example, point cloud data or polygon data of the target area. The target area information is generated in advance by 3D scanning or photo scanning the target area. The target area information acquisition unit 11 acquires the target area information from the input device 2 or the communication device 3.

[0041] The model creation unit 12 uses the target area information acquired by the target area information acquisition unit 11 to create a three-dimensional CG model (hereinafter also referred to as a "structural model") representing the structures in the target area, as shown in Figure 3.

[0042] The lattice surface creation unit 13 creates multiple lattice surfaces by dividing the surface of the structure in the target area. Specifically, the lattice surface creation unit 13 creates multiple lattice surfaces by dividing each surface (wall surface, floor surface, ground surface, ceiling surface, surface of the indoor structure, etc.) inside the building represented by the structural model created by the model creation unit 12. FIG. 4 shows an example in which one surface of an indoor structure is divided into multiple triangular lattice surfaces. In this embodiment, it is assumed that a radiation source exists on each lattice surface. The radiation source assumed to exist on each lattice surface corresponds to the radiation source indicated by the radiation source vector ω described above. The lattice surfaces may be radiation source candidate surfaces.

[0043] The observation target information acquisition unit 14 acquires observation target information, which is information related to the observation target. The observation target information includes the number of observation targets. In this embodiment, the number of observation targets corresponds to the number of high-intensity radiation sources present in the target area, and is determined in advance by the user. The observation target information acquisition unit 14 acquires the observation target information from the input device 2 or the communication device 3.

[0044] The minimum point number determination unit 15 determines the minimum number of observation points at which the inverse estimation of the observation target from the observation results at the observation points is successful, based on the number of observation targets and the number of lattice planes. Here, the number of observation targets included in the observation target information acquired by the observation target information acquisition unit 14 is set to n sThe number of lattice planes created by lattice plane creation unit 13 is m, and the minimum number of observation points is p. Minimum point number determination unit 15 determines the minimum number of points p using the following formula (1).

[0045]

number

[0046] In the above formula (1), α is a constant that is predetermined according to the structure of the target area. α may be a numerical value in the range of 2 to 4. In this embodiment, α may be, for example, 3.83. Formula (1) is also called the Candes-Tao condition, and mathematically defines the minimum number of observation points required for successful inverse estimation of an observation target from observation results.

[0047] By determining the minimum number of points p using the above formula (1), minimum point number determination unit 15 can determine the minimum number of points p so as to reliably secure the minimum number of observation points required for successful inverse estimation of an observation target from observation results. Therefore, observation point determination unit 19 can determine observation points so as to minimize the number of observation points while reliably securing the minimum number of observation points required for successful inverse estimation of an observation target from observation results. Therefore, observation point determination device 1 can further optimize the observation points so as to reliably observe the observation target while minimizing the number of observation points.

[0048] The spatial grid point creation unit 16 divides the space in the target area to create multiple spatial grid points. Specifically, the spatial grid point creation unit 16 divides the space in the target area represented by the structural model created by the model creation unit 12 to create multiple spatial grids. The spatial grid point creation unit 16 then sets the intersections of the sides of adjacent spatial grids as spatial grid points. The spatial grids and grid planes do not overlap. The spatial grid points can be candidate points for observation points.

[0049] The direct-feedback determination unit 17 determines for each spatial lattice point whether a straight line connecting an arbitrary point on each lattice plane and a spatial lattice point directly reaches the spatial lattice point (also referred to as "directly reaches"). That is, the direct-feedback determination unit 17 determines for each spatial lattice point whether a straight line connecting an arbitrary point on each lattice plane and a spatial lattice point directly reaches the spatial lattice point without passing through any lattice plane other than the lattice plane. For example, as shown in FIG. 5, the direct-feedback determination unit 17 focuses on one spatial lattice point and determines whether a straight line connecting an arbitrary point on one lattice plane and the spatial lattice point directly reaches the spatial lattice point. Next, the direct-feedback determination unit 17 determines whether a straight line connecting an arbitrary point on another lattice plane and the spatial lattice point directly reaches the spatial lattice point. By repeating such determination, the direct-feedback determination unit 17 determines for all lattice planes whether a straight line connecting the spatial lattice point and the spatial lattice point directly reaches the spatial lattice point. Thereafter, the direct determination unit 17 focuses on other spatial lattice points and determines whether or not a straight line connecting an arbitrary point of each lattice plane and the other spatial lattice point directly reaches the other spatial lattice point. By repeating such determination, the direct determination unit 17 determines whether or not a straight line from each lattice plane directly reaches all spatial lattice points. Note that the arbitrary point of each lattice plane is preferably the center point of each lattice plane, but may be any point other than the center point as long as it is located within each lattice plane.

[0050] The decision vector creation unit 18 creates a decision vector indicating the decision result of the direct determination unit 17 for each spatial lattice point. That is, the decision vector creation unit 18 creates one decision vector for one spatial lattice point. For example, the decision vector creation unit 18 creates a column vector whose element number is the number m of lattice planes, by setting the element value to 1 if the decision result of the direct determination unit 17 is that a straight line from one lattice plane directly reaches the point, and setting the element value to 0 if the decision result is that a straight line from another lattice plane does not directly reach the point. Then, the decision vector creation unit 18 creates decision vectors for all spatial lattice points.

[0051] Observation point determination unit 19 determines an observation point based on the minimum number p of observation points determined by minimum point number determination unit 15 and the judgment result of direct determination unit 17. Specifically, observation point determination unit 19 determines an observation point based on the minimum number p of observation points determined by minimum point number determination unit 15 and the decision vector created by decision vector creation unit 18. Observation point determination unit 19 has a first determination unit 191 and a second determination unit 192.

[0052] The first determination unit 191 determines the spatial lattice point with the largest number of lattice faces that are directly reached by straight lines from each lattice face as the observation point. Specifically, the first determination unit 191 selects the decision vector with the largest number of element values ​​1 from among the multiple decision vectors created by the decision vector creation unit 18, and determines the spatial lattice point of the selected decision vector as the observation point.

[0053] The second determination unit 192 identifies a lattice plane on which the straight line does not directly reach for the spatial lattice point determined as the observation point, and determines another spatial lattice point on which the straight line from the identified lattice plane directly reaches as the next observation point. Specifically, the second determination unit 192 identifies an element with element value 0 in the decision vector selected by the first determination unit 191, and searches for another decision vector with the largest number of elements with element value 1 for the identified element. The second determination unit 192 then determines the spatial lattice point of the other decision vector found as the next observation point.

[0054] The second determination unit 192 continues to determine the observation point until there is no lattice plane on which the straight line does not directly reach the spatial lattice point determined as the observation point, as shown in Fig. 6. Specifically, the second determination unit 192 continues to search for other decision vectors and determine the observation point for each of all elements in the decision vector selected by the first determination unit 191 with an element value of 0, until another decision vector having an element value of 1 is searched for and the spatial lattice point of the other decision vector is determined as the observation point.

[0055] As a result, straight lines reach the observation points directly from all grid planes, so that the observation point determination unit 19 can determine the observation points so that the observation target in the target area can be observed without blind spots. Therefore, the observation point determination unit 19 can determine the observation points so that the observation target in the target area can be observed more thoroughly while minimizing the number of observation points. Therefore, the observation point determination device 1 can further optimize the observation points so that the observation target can be reliably observed while minimizing the number of observation points.

[0056] Furthermore, the second determination unit 192 continues to determine the observation points until the number of observation points determined by the first determination unit 191 or the second determination unit 192 becomes equal to or greater than the minimum number of points p. Specifically, when the number of determined observation points is less than the minimum number of points p, the second determination unit 192 identifies the decision vectors of the spatial lattice points that have already been determined as the observation points in the order in which the observation points were determined, and calculates the product of the identified decision vector and the decision vector of the spatial lattice point that has not yet been determined as the observation point. Then, the second determination unit 192 selects the decision vector of the spatial lattice point that has not yet been determined as the observation point, which minimizes the calculated product, and determines the spatial lattice point of the selected decision vector as the next observation point. Then, the second determination unit 192 continues to calculate this product and determine the observation points until the number of observation points becomes equal to or greater than the minimum number of points p.

[0057] This allows observation point determination unit 19 to ensure that the minimum number of observation points necessary for successful inverse estimation of the observation target from the observation results is secured, while keeping the number of observation points as small as possible. Therefore, observation point determination unit 19 can determine observation points so as to reliably prevent a shortage of observation points that would cause problems in estimating the observation target, while keeping the number of observation points as small as possible. Therefore, observation point determination device 1 can further optimize the observation points so that the observation target can be reliably observed, while keeping the number of observation points as small as possible.

[0058] The output unit 20 outputs information about the observation points determined by the observation point determination unit 19 to the display device 5 or the communication device 3. For example, the output unit 20 may superimpose the observation points determined by the observation point determination unit 19 on a structural model, which is a 3D CG model of the target area created by the model creation unit 12, to create a map that visualizes the distribution of the observation points in the target area. The output unit 20 may then display the created map on the display device 5, or transmit it to an external device via the communication device 3 to display it on the external device.

[0059] Fig. 7 is a flowchart showing an outline of the processing performed by observation point determining device 1. Fig. 8 is a flowchart showing an outline of the processing performed subsequent to Fig. 7.

[0060] In step S1, the observation point determination device 1 acquires target area information, such as point cloud data of the target area.

[0061] In step S2, the observation point determination device 1 creates a structural model of the target area using the acquired target area information.

[0062] In step S3, the observation point determination device 1 divides the surface of the structure in the target area based on the created structural model to create a plurality of lattice planes.

[0063] In step S4, the observation point determination device 1 determines the number m of the created lattice planes and the number n of the predetermined observation targets. s Based on the predetermined constant α, the minimum number p of observation points is determined using the above formula (1).

[0064] In step S5, the observation point determination device 1 divides the space within the target area based on the created structural model to create a plurality of spatial lattice points.

[0065] In step S6, the observation point determination device 1 determines, for each spatial lattice point, whether or not a straight line connecting an arbitrary point on each lattice plane and the spatial lattice point directly reaches that spatial lattice point.

[0066] In step S7, the observation point determination device 1 creates, for each spatial lattice point, a decision vector indicating the decision result as to whether or not a straight line from each lattice plane reaches the spatial lattice point directly.

[0067] In step S8, the observation point determination device 1 selects the decision vector having the largest number of element values ​​1 from the multiple decision vectors that have been created, and determines the spatial lattice point of the selected decision vector as the observation point.

[0068] In step S9, observation point determination device 1 determines whether or not other decision vectors having elements with element value 1 have been searched for all elements in the selected decision vector with element value 0. If such other decision vectors have been searched for all elements in the selected decision vector with element value 0, observation point determination device 1 proceeds to step S13. If such other decision vectors have not been searched for all elements in the selected decision vector with element value 0, observation point determination device 1 proceeds to step S10.

[0069] In step S10, the observation point determination device 1 searches for other decision vectors having elements with element value 1 for the remaining elements in the selected decision vector with element value 0, and determines whether or not such other decision vectors exist. If such other decision vectors exist for the remaining elements in the selected decision vector with element value 0, the observation point determination device 1 proceeds to step S11. If such other decision vectors do not exist for the remaining elements in the selected decision vector with element value 0, the observation point determination device 1 proceeds to step S12.

[0070] In step S11, observation point determination device 1 determines as an observation point the spatial lattice point of another decision vector that has the largest number of elements with element value 1 compared to the remaining elements in the selected decision vector that have element value 0. After that, observation point determination device 1 proceeds to step S9.

[0071] In step S12, observation point determination device 1 selects, from among the decision vectors of spatial lattice points that have not yet been determined as observation points, the decision vector that has the largest number of elements with element value 1, and determines the spatial lattice point of the selected decision vector as the observation point. After that, observation point determination device 1 proceeds to step S9.

[0072] In step S13, observation point determination device 1 determines whether the number of determined observation points is equal to or greater than the minimum number p. If the number of determined observation points is equal to or greater than the minimum number p, observation point determination device 1 terminates the processing shown in Figures 7 and 8. If the number of determined observation points is less than the minimum number p, observation point determination device 1 proceeds to step S14.

[0073] In step S14, the observation point determination device 1 identifies the decision vectors of the spatial lattice points that have already been determined as observation points in the order in which the observation points were determined, and calculates the product of the identified decision vectors and the decision vectors of the spatial lattice points that have not yet been determined as observation points. The calculated product is an inner product.

[0074] In step S15, the observation point determination device 1 selects the judgment vector of the spatial grid point not yet determined as the observation point for which the calculated product is the smallest, and determines the spatial grid point of the selected judgment vector as the observation point. The spatial grid point not yet determined as the observation point for which the calculated product is the smallest is a spatial grid point not yet determined as the observation point for which the number of lines that directly reach the spatial grid point and that directly reach the spatial grid point already determined as the observation point are the smallest. By performing the process of step S15, the observation point determination device 1 can newly determine an observation point having an observation range that does not overlap as much as possible with the observation range of an already determined observation point. This allows the observation point determination device 1 to distribute the observation points so that the observation ranges of each observation point do not overlap as much as possible, and to distribute the observation points as uniformly as possible in the target area. After step S15, the observation point determination device 1 proceeds to step S13.

[0075] As described above, the observation point determination device 1 of this embodiment is an observation point determination device that determines an observation point for observing an observation target within a target area. The observation point determination device 1 includes a lattice surface creation unit 13 that divides the surface of a structure in the target area to create multiple lattice surfaces, and a spatial lattice point creation unit 16 that divides the space within the target area to create multiple spatial lattice points. The observation point determination device 1 includes a minimum point number determination unit 15 that determines the minimum number of observation points at which inverse estimation, which estimates an observation target from an observation result at an observation point, is successful, based on the number of observation targets and the number of lattice surfaces. The observation point determination device 1 includes a direct determination unit 17 that determines, for each spatial lattice point, whether a straight line connecting an arbitrary point on each lattice surface and a spatial lattice point directly reaches the spatial lattice point, and an observation point determination unit 19 that determines an observation point based on the minimum number of observation points and the determination result of the direct determination unit 17.

[0076] This allows observation point determination unit 19 to determine observation points so that the observation target within the target area can be observed thoroughly while keeping the number of observation points as small as possible. Therefore, observation point determination device 1 can optimize the observation points so that the observation target can be observed reliably while keeping the number of observation points as small as possible.

[0077] Furthermore, in observation point determination device 1, the observation target is a radiation source present in the target area, the observation result is the measurement result of radiation emitted from the radiation source, and the observation point is a measurement point of the radiation.

[0078] This allows the observation point determination device 1 to reliably prevent an excessive number of radiation measurement points, which would result in increased measurement time and effort, and an increase in the amount of radiation exposure. In addition, the observation point determination device 1 can reliably prevent an insufficient number of radiation measurement points, which would hinder estimation of the radiation source. Thus, the observation point determination device 1 can optimize the radiation measurement points so that the radiation source can be reliably estimated while minimizing the number of radiation measurement points.

[0079] Furthermore, in observation point determination device 1, the observation target is a monitored object existing in a target area, the observation result is an image captured by a surveillance camera monitoring the monitored object, and the observation point is the installation point of the surveillance camera.

[0080] This allows the observation point determination device 1 to reliably prevent the installation of an excessive number of surveillance cameras, which would result in the time and effort required for installation. In addition, the observation point determination device 1 can reliably prevent a situation in which the number of surveillance cameras installed is insufficient, resulting in blind spots in the target area and hindering the monitoring of the monitored object. Therefore, the observation point determination device 1 can optimize the installation points of the surveillance cameras so that the monitored object can be reliably monitored while minimizing the number of surveillance cameras installed.

[0081] The observation point determination method of this embodiment can be realized by the observation point determination device 1 performing the processes shown in FIGS.

[0082] That is, the observation point determination method of this embodiment is a method for determining an observation point for observing an observation target within a target area. The observation point determination method includes dividing the surface of a structure in the target area to create a plurality of lattice planes (step S3), and dividing the space within the target area to create a plurality of spatial lattice points (step S5). The observation point determination method includes determining the minimum number of observation points at which inverse estimation of the observation target from the observation results at the observation points is successful, based on the number of observation targets and the number of lattice planes (step S4). The observation point determination method includes determining, for each spatial lattice point, whether a straight line connecting an arbitrary point on each lattice plane and a spatial lattice point directly reaches the spatial lattice point (step S6), and determining an observation point based on the minimum number of observation points and the determination result of whether the straight line directly reaches the spatial lattice point (steps S8 to S15).

[0083] As a result, the observation point determination method of this embodiment can determine observation points so that the observation target within the target area can be observed thoroughly while keeping the number of observation points as small as possible. Therefore, the observation point determination method can optimize the observation points so that the observation target can be observed reliably while keeping the number of observation points as small as possible.

[0084] Although the embodiments of the present invention have been described in detail above, the present invention is not limited to the above embodiments, and various modifications can be made without departing from the spirit of the present invention described in the claims. In the present invention, the configuration of one embodiment can be added to the configuration of another embodiment, the configuration of one embodiment can be replaced with the configuration of another embodiment, or a part of the configuration of one embodiment can be deleted. [Explanation of symbols]

[0085] 1...observation point determination device, 2...input device, 3...communication device, 4...storage device, 5...display device, 10...arithmetic processing device, 11...target area information acquisition unit, 12...model creation unit, 13...lattice surface creation unit, 14...observation target information acquisition unit, 15...minimum point number determination unit, 16...spatial lattice point creation unit, 17...direct determination unit, 18...decision vector creation unit, 19...observation point determination unit, 191...first determination unit, 192...second determination unit, 20...output unit

Claims

1. An observation point determination device for determining an observation point for observing an observation target within a target area, a grid surface creation unit that creates a plurality of grid surfaces by dividing a surface of a structure in the target area; a spatial grid point creation unit that creates a plurality of spatial grid points by dividing a space within the target area; a minimum point number determination unit that determines a minimum number of observation points at which an inverse estimation of the observation target from the observation results at the observation points is successful, based on the number of the observation targets and the number of the lattice planes; a direct hit determination unit that determines, for each spatial lattice point, whether or not a straight line connecting an arbitrary point on each lattice plane and the spatial lattice point directly reaches the spatial lattice point; an observation point determination unit that determines the observation points based on the minimum number of the observation points and a determination result of the direct determination unit; An observation point determination device characterized by:

2. The observation point determination unit, a first determination unit that determines the spatial lattice point that has the largest number of lattice faces directly reached by the straight line as the observation point; a second determination unit that identifies the lattice surface on which the straight line does not directly reach with respect to the spatial lattice point determined at the observation point, and determines another spatial lattice point on which the straight line from the identified lattice surface directly reaches as the observation point, The second determination unit continues to determine the observation points until the number of the observation points determined by the first determination unit or the second determination unit becomes equal to or greater than the minimum number of points.

2. The observation point determination device according to claim 1 .

3. The second determination unit continues to determine the observation point until there is no lattice surface on which the straight line does not directly reach the spatial lattice point determined as the observation point.

3. The observation point determination device according to claim 2.

4. The number of observation targets is n ｓ where m is the number of lattice planes, p is the minimum number of points, and α is a constant that is predetermined according to the structure of the target area. The minimum number of points determination unit determines the minimum number of points using the formula (1).

2. The observation point determination device according to claim 1 . [0010]

5. the observation target is a radiation source present in the target area; the observation result is a measurement result of radiation emitted from the radiation source, The observation point is a measurement point of the radiation.

2. The observation point determination device according to claim 1 .

6. The observation target is a monitored object present in the target area, the observation result is an image captured by a surveillance camera monitoring the surveillance object, The observation point is the installation point of the surveillance camera.

2. The observation point determination device according to claim 1 .

7. 1. An observation point determination method for determining an observation point for observing an observation target within a target area, comprising: Dividing a surface of a structure in the target area to generate a plurality of lattice planes; Dividing a space within the area of ​​interest to generate a plurality of spatial grid points; determining a minimum number of observation points at which an inverse estimation of the observation target from the observation results at the observation points is successful, based on the number of the observation targets and the number of the lattice planes; determining, for each spatial lattice point, whether or not a straight line connecting an arbitrary point on each lattice plane and the spatial lattice point directly reaches the spatial lattice point; determining the observation points based on the minimum number of observation points and a determination result of whether the straight line reaches the observation points directly; 2. A method for determining an observation point, comprising:

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