Brightness distribution estimation device and brightness distribution estimation program

Abstract

To provide a luminance distribution estimation device and a luminance distribution estimation program capable of estimating a luminance distribution in a measurement point different from an actual measurement point without being affected by a dead angle at the time of photographing.SOLUTION: A luminance distribution estimation device 10 includes: a first acquisition unit 11A that acquires a first luminance distribution showing distribution of luminance obtained by measurement of a first predetermined measurement point, and a first contribution matrix showing the magnitude of influence that daylight gives to the first measurement point; a derivation unit 11B for deriving a light emitting intensity distribution on an incidence surface on which daylight impinges by using the first luminance distribution and the first contribution matrix; a second acquisition unit 11C for acquiring a second contribution matrix showing the magnitude of influence that daylight gives to a second measurement point different from the first measurement point; and an estimation unit 11D for estimating a second luminance distribution showing distribution of luminance in the second measurement point by using a light emitting intensity distribution and the second contribution matrix.SELECTED DRAWING: Figure 3

Description

[Technical Field]

[0001] This invention relates to a luminance distribution estimation device and a luminance distribution estimation program. [Background technology]

[0002] In creating an indoor lighting environment, it is important to appropriately and simply consider the influence of ambient light entering through windows, which contributes significantly to the lighting. In recent years, there has been a method of controlling building lighting and blinds based on an index of the visual environment calculated from the luminance distribution of an area including windows, using imaging devices such as cameras.

[0003] Traditionally, the following technologies have been used to control building lighting:

[0004] Patent Document 1 discloses a lighting control system aimed at enabling lighting control in a lit space with windows or the like that is tailored to the perception of the occupants.

[0005] This lighting control system comprises a lighting fixture for illuminating an indoor lighting space with a window surface that allows light to pass through to the outdoors, and a plurality of imaging means for capturing images of a person's field of view from different directions within the lighting space. Furthermore, this lighting control system includes a luminance distribution measuring means for measuring the luminance distribution within the images captured by each imaging means, and a window surface luminance calculation means for measuring the luminance of the window surface within the images captured by each imaging means. In addition, this lighting control system includes a field of view direction detection means for detecting the direction of a person's field of view within the images captured by the imaging means, and a control means for dimming the lighting fixture based on the detected field of view of the person, the luminance distribution within the images, and the luminance of the window surface.

[0006] However, this technology requires the use of multiple imaging devices. In this case, since the brightness of light sources such as windows varies greatly depending on the viewing angle, it is desirable to install the imaging devices at the eye level of building users (office workers, etc.) in order to use them as a good indicator of the human visual environment. However, the installation locations are limited because they would obstruct users. For example, they would have to be suspended from the ceiling, which is far from the line of sight. Furthermore, the design is poor and it may give users a psychologically oppressive feeling of being monitored. Moreover, installing a device at each user's line of sight is costly.

[0007] As a technology that can be applied to solve this problem, Patent Document 2 discloses a lighting control system aimed at enabling lighting control that provides a comfortable lighting space for people without the need to install multiple cameras in all directions.

[0008] This lighting control system includes a visible image acquisition unit that acquires a visible image, and a viewpoint conversion unit that receives a person's field of view as input and converts the visible image acquired by the visible image acquisition unit into a visible image from the person's viewpoint within the field of view. The lighting control system also includes a luminance distribution calculation unit that calculates the luminance distribution of the field of view based on the visible image from the person's viewpoint, a dimming control unit that controls the dimming of the lighting fixture based on the luminance distribution, and an image storage unit that stores the visible image acquired by the visible image acquisition unit along with the time of capture. Furthermore, the lighting control system includes a scattering characteristic estimation unit that extracts a plurality of visible images with different capture times from the visible image acquired by the visible image acquisition unit and the visible images stored in the image storage unit, and estimates the scattering characteristics for each of a plurality of sub-regions constituting the visible image acquired by the visible image acquisition unit based on the plurality of visible images with different capture times, and the luminance distribution calculation unit corrects the luminance distribution based on the scattering characteristics. [Prior art documents] [Patent Documents]

[0009] [Patent Document 1] Japanese Patent Publication No. 2010-9874 [Patent Document 2] Patent No. 6863475 [Overview of the Initiative] [Problems that the invention aims to solve]

[0010] However, the technology disclosed in Patent Document 2 has the problem that, because it converts a visible image captured at a certain location into a visible image from a human perspective, it is not possible to obtain the brightness distribution for areas that were blind spots during the above-mentioned capture.

[0011] This disclosure is made in view of the above circumstances and aims to provide a luminance distribution estimation device and a luminance distribution estimation program that can estimate the luminance distribution at a measurement point different from the actual measurement point without being affected by blind spots during shooting. [Means for solving the problem]

[0012] The luminance distribution estimation device according to claim 1 of the present invention comprises: a first acquisition unit that acquires a first luminance distribution showing the distribution of luminance obtained by measurement at a predetermined first measurement point, and a first contribution matrix showing the magnitude of the influence of daylight on the first measurement point; a derivation unit that derives a light emission intensity distribution at an incident surface to which daylight is incident using the first luminance distribution and the first contribution matrix; a second acquisition unit that acquires a second contribution matrix showing the magnitude of the influence of daylight on a second measurement point different from the first measurement point; and an estimation unit that estimates a second luminance distribution showing the distribution of luminance at the second measurement point using the light emission intensity distribution and the second contribution matrix.

[0013] According to the luminance distribution estimation device of the present invention as described in claim 1, a first luminance distribution showing the luminance distribution obtained by measurement at a predetermined first measurement point and a first contribution matrix showing the magnitude of the influence of daylight on the first measurement point are obtained, the emission intensity distribution at the incident surface where daylight is incident is derived using the first luminance distribution and the first contribution matrix, a second contribution matrix showing the magnitude of the influence of daylight on a second measurement point different from the first measurement point is obtained, and a second luminance distribution showing the luminance distribution at the second measurement point is estimated using the emission intensity distribution and the second contribution matrix, thereby eliminating the need to use a visible image at the second measurement point, and as a result, the luminance distribution at a measurement point different from the actual measurement point can be estimated without being affected by blind spots during shooting.

[0014] The luminance distribution estimation device according to claim 2 is the luminance distribution estimation device according to claim 1, wherein the first acquisition unit further acquires a third contribution matrix showing the magnitude of the influence on the first measurement point when the dimming rate of the illumination light due to artificial lighting is 100%, and the dimming rate; the derivation unit derives the emission intensity distribution using the first luminance distribution, the first contribution matrix, the third contribution matrix, and the dimming rate; the second acquisition unit further acquires a fourth contribution matrix showing the magnitude of the influence of the illumination light on the second measurement point; and the estimation unit estimates the second luminance distribution using the emission intensity distribution, the second contribution matrix, the fourth contribution matrix, and the dimming rate.

[0015] According to the luminance distribution estimation device of the present invention as described in claim 2, a third contribution matrix showing the magnitude of the influence on the first measurement point when the dimming rate of the illumination light due to artificial lighting is 100%, and the dimming rate are further obtained, and the emission intensity distribution is derived using the first luminance distribution, the first contribution matrix, the third contribution matrix, and the dimming rate, and a fourth contribution matrix showing the magnitude of the influence of the illumination light on the second measurement point is further obtained, and the second luminance distribution is estimated using the emission intensity distribution, the second contribution matrix, the fourth contribution matrix, and the dimming rate, thereby enabling more accurate estimation of the luminance distribution at a measurement point different from the actual measurement point when artificial lighting is present in addition to daylight.

[0016] The luminance distribution estimation program according to the present invention as recited in claim 3 causes a computer to execute a process of obtaining a first luminance distribution indicating a distribution of luminance obtained by measurement at a predetermined first measurement point, and a first contribution matrix indicating the magnitude of the influence of daylight on the first measurement point, deriving a light emission intensity distribution on an incident surface where the daylight is incident using the first luminance distribution and the first contribution matrix, obtaining a second contribution matrix indicating the magnitude of the influence of daylight on a second measurement point different from the first measurement point, and estimating a second luminance distribution indicating a distribution of luminance at the second measurement point using the light emission intensity distribution and the second contribution matrix.

[0017] According to the luminance distribution estimation program according to the present invention as recited in claim 3, a first luminance distribution indicating a distribution of luminance obtained by measurement at a predetermined first measurement point, and a first contribution matrix indicating the magnitude of the influence of daylight on the first measurement point are obtained, a light emission intensity distribution on an incident surface where the daylight is incident is derived using the first luminance distribution and the first contribution matrix, a second contribution matrix indicating the magnitude of the influence of daylight on a second measurement point different from the first measurement point is obtained, and a second luminance distribution indicating a distribution of luminance at the second measurement point is estimated using the light emission intensity distribution and the second contribution matrix. As a result, it is not necessary to use a visible image at the second measurement point, and the luminance distribution at a measurement point different from the actual measurement point can be estimated without being affected by a dead angle at the time of shooting.

Effect of the Invention

[0018] As described above, according to the present invention, the luminance distribution at a measurement point different from the actual measurement point can be estimated without being affected by a dead angle at the time of shooting.

Brief Description of the Drawings

[0019] [Figure 1] It is a block diagram showing an example of the hardware configuration of the luminance distribution estimation device according to the embodiment. [Figure 2]It is a diagram for explaining the contribution matrix according to the embodiment, and is a cross-sectional view showing an example of a combination of the traveling direction of light and measurement points when there are two light sources and two measurement points. [Figure 3] It is a block diagram showing an example of the functional configuration of the luminance distribution estimation device according to the embodiment. [Figure 4] It is a schematic diagram showing an example of the configuration of the building-related information database according to the embodiment. [Figure 5] It is a schematic diagram showing an example of the configuration of the luminance distribution information database according to the embodiment. [Figure 6] It is a flowchart showing an example of the luminance distribution estimation process according to the embodiment. [Figure 7] It is a front view showing an example of the configuration of the initial information input screen according to the embodiment. [Figure 8] It is a diagram for explaining the conventional technology, and is a graph showing an example of the light source position of direct sunlight in the multi-phase method as an example of the discretization of the light source position.

Embodiments of the Invention

[0020] Hereinafter, embodiments for carrying out the present invention will be described in detail with reference to the drawings. In the present embodiment, a case where the present invention is applied to a luminance distribution estimation device that estimates the luminance distribution when a desired position in a room provided in a predetermined building is used as a measurement point will be described.

[0021] First, referring to FIG. 1, the configuration of the luminance distribution estimation device 10 according to the present embodiment will be described. FIG. 1 is a block diagram showing an example of the hardware configuration of the luminance distribution estimation device 10 according to the present embodiment. Examples of the luminance distribution estimation device 10 include information processing devices such as personal computers and server computers.

[0022] As shown in Figure 1, the luminance distribution estimation device 10 according to this embodiment includes a CPU (Central Processing Unit) 11, a memory 12 as a temporary storage area, a non-volatile storage unit 13, an input unit 14 such as a keyboard and mouse, a display unit 15 such as a liquid crystal display, a media read / write device (R / W) 16, and a communication interface (I / F) unit 18. The CPU 11, memory 12, storage unit 13, input unit 14, display unit 15, media read / write device 16, and communication I / F unit 18 are connected to each other via bus B. The media read / write device 16 reads information written on the recording medium 17 and writes information to the recording medium 17.

[0023] The storage unit 13 is implemented by an HDD (Hard Disk Drive), SSD (Solid State Drive), flash memory, etc. The storage unit 13, as a storage medium, stores a luminance distribution estimation program 13A and a physical illumination simulation program 13B. The luminance distribution estimation program 13A is stored in the storage unit 13 when the recording medium 17 on which the program 13A is written is set in the media read / write device 16, and the media read / write device 16 reads the program 13A from the recording medium 17. Similarly, the physical illumination simulation program 13B is stored in the storage unit 13 when the recording medium 17 on which the program 13B is written is set in the media read / write device 16, and the media read / write device 16 reads the program 13B from the recording medium 17. The CPU 11 reads the luminance distribution estimation program 13A and the physical illumination simulation program 13B from the storage unit 13 as appropriate, loads them into memory 12, and sequentially executes the processes of each program.

[0024] In this embodiment, the existing program Radiance is used as the physical lighting simulation program 13B. However, this is not the only possible configuration; the physical lighting simulation program 13B may also be other existing programs with similar functionality or a dedicated program.

[0025] Furthermore, the memory unit 13 stores a building-related information database 13C and a luminance distribution information database 13D. Details of the building-related information database 13C and the luminance distribution information database 13D will be described later.

[0026] Meanwhile, the communication I / F unit 18 is connected to a camera 30 installed in the room whose brightness distribution is to be estimated (hereinafter referred to as the "estimate target room").

[0027] In this embodiment, the imaging device 30 is a surveillance camera that has been previously installed on the ceiling of the room under investigation. This eliminates the need to install a new imaging device in the room under investigation, thus avoiding increased costs and eliminating the need to provide installation space that would be required if a new imaging device were installed. However, it goes without saying that this is not the only possible configuration, and a configuration in which a dedicated imaging device 30 is newly installed in the room under investigation may also be used. Furthermore, in this embodiment, an imaging device 30 that captures color images is used, but this is not the only possible configuration. For example, an imaging device 30 that captures monochrome images may also be used.

[0028] In the luminance distribution estimation device 10 according to this embodiment, the contribution matrix, which indicates the magnitude of the influence of daylight on the measurement point, is obtained by a conventionally known physical illumination simulation program (in this embodiment, physical illumination simulation program 13B). The contribution matrix will now be explained.

[0029] In conventional physical lighting simulation programs such as Radiance, the calculation results for daylight vary depending on the weather and time of day. Therefore, simulations must be performed for each set of conditions, but the multi-phase method exists to speed up these calculations.

[0030] In the multi-phase method, a calculation result matrix (light source position × calculation point) for each calculation point per reference intensity of the discretized light source is created in advance. By multiplying this matrix with the light source intensity vector (light source position) according to the weather and time, the results for the calculation point under specified weather and time conditions are obtained instantaneously. The above calculation result matrix shows the magnitude of the influence of daylight on the measurement point, and this calculation result matrix is ​​called the contribution matrix M.

[0031] There are several variations in how the contribution matrix M is used. For example, when the light sources are sky light and direct sunlight, the photometric quantity at the measurement point can be calculated using the contribution matrix and the emission intensity distribution of the light sources, as shown in equation (1) below. In equation (1), "Direct Daylight Coefficients" is the contribution matrix for direct daylight, and "Sky Daylight Coefficients" is the contribution matrix for sky light. Also, in equation (1), "Sun vecor" is the emission intensity distribution for direct daylight, "Sky vecor" is the emission intensity distribution for sky light, and "sensor values" are the photometric quantities at the measurement point. Furthermore, in equation (1), m is the number of pixels (number of measurement points) in the sensor of the imaging device, and n is the number of elements in the emission intensity distributions of direct daylight and sky light.

[0032]

number

[0033] Figure 8 shows an example of discretization of light source positions, specifically an example of the light source position for direct sunlight in the multi-phase method (Source: “Standard daylight coefficient model for dynamic daylighting simulations”, [online], [Accessed September 18, 2022], Internet). <URL:https: / / www.researchgate.net / publication / 228683789_Standard_daylight_coefficient_model_for_dynamic_daylighting_simulations> ). The actual sun can take any position within the thick frame, but it is discretized, and the values ​​of the calculation points are obtained only at the positions marked with a +, and the calculation results of multiple light source positions (marked with a +) adjacent to the actual position of the sun are weighted and averaged. This averaging process sacrifices spatial resolution (edge ​​strength) but ensures the accuracy of physical quantities. In this specification, the above direct sunlight is also referred to as "direct daylight."

[0034] Figure 2 is a diagram illustrating the contribution matrix M according to this embodiment, and is a cross-sectional view showing an example of a combination of light propagation direction and measurement points when there are two light sources and two measurement points.

[0035] In the luminance distribution estimation device 10 according to this embodiment, the contribution matrix M is used by considering the light source as only the window surface or a window surface having a window device such as a blind.

[0036] For example, in the example shown in Figure 2, we can formulate the following two equations. Note that in the following equations, f ij L is the illuminance that a light source j of standard intensity gives to the measurement point i, j is the emission intensity of light source j, and E i This is the illuminance at measurement point i.

[0037] f 11 ×L1+f 21 ×L2=E1

[0038] f 12 ×L1+f 22×L2 = E2

[0039] As an example, as shown in FIG. 2, the light emitted from a certain light source repeats reflection and finally reaches a certain measurement point, and the illuminance given is f ij and f ij The generalized and matrix-formulated one is defined as the contribution matrix M

[0040] Next, referring to FIG. 3, the functional configuration of the luminance distribution estimation device 10 according to the present embodiment will be described. FIG. 3 is a block diagram showing an example of the functional configuration of the luminance distribution estimation device 10 according to the present embodiment

[0041] As shown in FIG. 3, the luminance distribution estimation device 10 according to the present embodiment includes a first acquisition unit 11A, a derivation unit 11B, a second acquisition unit 11C, and an estimation unit 11D. By the CPU 11 of the luminance distribution estimation device 10 executing the luminance distribution estimation program 13A, it functions as the first acquisition unit 11A, the derivation unit 11B, the second acquisition unit 11C, and the estimation unit 11D

[0042] The first acquisition unit 11A according to the present embodiment acquires a first luminance distribution indicating the distribution of luminance obtained by measurement at a predetermined first measurement point, and a first contribution matrix indicating the magnitude of the influence of daylight on the first measurement point. In the present embodiment, the first luminance distribution is acquired from the imaging device 30. Also, in the present embodiment, the first contribution matrix is acquired using the physical lighting simulation program 13B

[0043] Further, the derivation unit 11B according to the present embodiment uses the acquired first luminance distribution and first contribution matrix to derive the light emission intensity distribution on the incident surface (in the present embodiment, the window surface) where daylight is incident

[0044] In addition, in the derivation unit 11B according to the present embodiment, as an example, the light emission intensity distribution is derived using the following formula (2). "View matrix A" in formula (2) is the first contribution matrix, "light vector" is the light emission intensity distribution, and "sensor vector A" is the first luminance distribution. Also, m in formula (2) is the number of pixels (measurement points) in the sensor of the imaging device 30, and p is the number of elements in the light emission intensity distribution of daylight.

[0045]

Number

[0046] The right side (first luminance distribution) in formula (2) can be obtained by imaging with the imaging device 30. Also, the first contribution matrix on the left side in formula (2) can be obtained by simulation with the prior physical illumination simulation program 13B.

[0047] Thereby, if the number of elements p of the light emission intensity distribution is smaller than the number of measurement points m (if p < m), it becomes theoretically possible to obtain the light emission intensity distribution, which is p unknowns.

[0048] That is, in the luminance distribution estimation device 10 according to the present embodiment, the light emission intensity distribution on the left side in formula (2), that is, the light emission intensity distribution of the light source (window surface) with the highest uncertainty and the greatest influence is set as an unknown, and the photometric quantity (first luminance distribution) of the measurement points where measurement is relatively easy is acquired by the imaging device 30. Then, in the luminance distribution estimation device 10 according to the present embodiment, by acquiring a contribution matrix (first contribution matrix) indicating the magnitude of the influence given by the unit light emission intensity to the measurement point through simulation, the unknown light emission intensity distribution is derived by a conventionally known method such as the least squares method.

[0049] On the other hand, the second acquisition unit 11C according to the present embodiment acquires a second contribution matrix indicating the magnitude of the influence given by daylight to a second measurement point different from the first measurement point. Then, the estimation unit 11D according to the present embodiment estimates a second luminance distribution indicating the distribution of luminance at the second measurement point using the light emission intensity distribution and the second contribution matrix.

[0050] In this embodiment, the estimation unit 11D estimates the second luminance distribution using, as an example, equation (3) shown below. In equation (3), "view matrix B" is the second contribution matrix, "light vector" is the emission intensity distribution derived by equation (2), and "sensor vector B" is the second luminance distribution.

[0051]

number

[0052] In other words, once the emission intensity distribution is derived by the derivation unit 11B, the photometric quantity (second luminance distribution) of any measurement point can be calculated using the contribution matrix (second contribution matrix) of any measurement point according to equation (3). This makes it possible to estimate the photometric quantity of measurement points that are difficult to measure on-site (for example, window surfaces or ceiling surfaces from the line of sight of an office worker).

[0053] As described above, the luminance distribution estimation device 10 according to this embodiment estimates the luminance distribution at any measurement point using equations (2) and (3).

[0054] Next, with reference to Figure 4, the building-related information database 13C according to this embodiment will be described. Figure 4 is a schematic diagram showing an example of the configuration of the building-related information database 13C according to this embodiment. The building-related information database 13C is a database that stores information about buildings that the luminance distribution estimation device 10 according to this embodiment is using to estimate the luminance distribution.

[0055] As shown in Figure 4, the building-related information database 13C according to this embodiment stores information such as the building name, building location information, and 3D CAD (Computer Aided Design) information associated with each building handled by the luminance distribution estimation device 10.

[0056] The above building name is information indicating the name of the corresponding building, and the above building location information is information indicating the construction location of the corresponding building. In this embodiment, the address of the corresponding building is used as the above building location information, but it is not limited to this. The above building location information may also be in the form of applying latitude and longitude information, or it may be in the form of applying the address, or latitude and longitude with altitude added, etc.

[0057] On the other hand, the above 3D CAD information is defined as information that represents a model (hereinafter referred to as the "building-related model") which includes building shape information that shows the shape of the corresponding building and reflectance information that shows the light reflectance of the interior of each room in the building. In addition, the building-related model according to this embodiment also includes identification information for identifying each room in the corresponding building.

[0058] In this embodiment, building-related models are created using predetermined 3D CAD software. In this embodiment, Rhinoceros® is used as the 3D CAD software, but it is not limited to this. For example, other software such as Revit® may be used as the 3D CAD software.

[0059] Next, the luminance distribution information database 13D according to this embodiment will be described with reference to Figure 5. Figure 5 is a schematic diagram showing an example of the configuration of the luminance distribution information database 13D according to this embodiment. The luminance distribution information database 13D is a database for storing information showing the luminance distribution estimated by the luminance distribution estimation device 10 according to this embodiment.

[0060] As shown in Figure 5, the luminance distribution information database 13D according to this embodiment stores information such as the building name, room name, estimated measurement point location, and luminance distribution for each building handled by the luminance distribution estimation device 10.

[0061] The above building name is the same information as the building name in the building-related information database 13C, and the above room name is information indicating the name of the room located in the corresponding building. Furthermore, the above estimated measurement point location is information indicating the location for which the luminance distribution is to be estimated, and the above luminance distribution is information indicating the estimated luminance distribution at the location of the corresponding estimated measurement point.

[0062] In this embodiment, information indicating the estimated measurement point location is applied as information indicating a predetermined position in a three-dimensional coordinate system with a predetermined position in the corresponding building (in this embodiment, the center of gravity of the building) as the origin, but it goes without saying that this is not the only way to do so.

[0063] Next, the operation of the luminance distribution estimation device 10 according to this embodiment will be explained with reference to Figures 6 and 7. When a user gives an instruction input via the input unit 14 to start the execution of the luminance distribution estimation program 13A, the CPU 11 of the luminance distribution estimation device 10 executes the program 13A, thereby executing the luminance distribution estimation process shown in Figure 6. Here, in order to avoid confusion, we will explain the case where the building-related information database 13C has already been constructed and the building name and room name information of the luminance distribution information database 13D have been registered.

[0064] In step 100 of Figure 6, the CPU 11 controls the display unit 15 to display an initial information input screen with a predetermined configuration, and in step 102, the CPU 11 waits until predetermined information is entered.

[0065] Figure 7 shows an example of the initial information input screen according to this embodiment. As shown in Figure 7, the initial information input screen according to this embodiment displays a message prompting the user to input information about the room to be processed (hereinafter referred to as the "target room"). In addition, the initial information input screen according to this embodiment displays input areas 15A for inputting information about the building in which the target room is located, the target room itself, the location of the actual measurement point, and the location of the measurement point to be estimated.

[0066] As an example, when the initial information input screen shown in Figure 7 is displayed on the display unit 15, the user inputs the corresponding information into the corresponding input area 15A via the input unit 14, and then presses the exit button 15B. Accordingly, step 102 becomes a positive determination, and the system proceeds to step 104. The position of the actual measurement point is the position of the measurement point by the imaging device 30, and since this position is fixed, it may be configured to store this position in advance.

[0067] In step 104, the CPU 11 reads 3D CAD information (hereinafter referred to as "building-related information") corresponding to the building entered on the initial information input screen from the building-related information database 13C. In step 106, the CPU 11 uses the building shape information and reflectance information contained in the read building-related information to derive the first contribution matrix at the location of the actual measurement point using the physical lighting simulation program 13B.

[0068] In step 108, the CPU 11 obtains a first luminance distribution from the imaging device 30, and in step 110, the CPU 11 derives the emission intensity distribution by applying the derived first contribution matrix and the obtained first luminance distribution to equation (2).

[0069] In step 112, the CPU 11 uses the building shape information and reflectance information contained in the read-out building-related information to derive a second contribution matrix at the location of any one of the measurement points to be estimated using the physical lighting simulation program 13B. In step 114, the CPU 11 applies the derived second contribution matrix and the luminescence intensity distribution obtained by the processing in step 110 to equation (3) to estimate the second luminance distribution at that measurement point.

[0070] In step 116, the CPU 11 stores (registers) the estimated second luminance distribution in the corresponding memory area of ​​the luminance distribution information database 13D. In step 118, the CPU 11 determines whether the derivation and registration of the second luminance distribution has been completed for all measurement points to be estimated, as entered by the user. If the determination is negative, the process returns to step 112; if the determination is positive, the luminance distribution estimation process is terminated.

[0071] Through the luminance distribution estimation process described above, a luminance distribution information database 13D, as shown in Figure 5 as an example, is constructed. The second luminance distribution registered in the luminance distribution information database 13D is used for analysis, such as calculating the solid angle of the region above a predetermined threshold in the second luminance distribution and deriving indicators such as glare and brightness, or for adjusting indoor lighting or the opening / closing rate of window blinds based on the results of this analysis.

[0072] As described above, according to this embodiment, a first luminance distribution showing the luminance distribution obtained by measurement at a predetermined first measurement point, and a first contribution matrix showing the magnitude of the influence of daylight on the first measurement point are obtained, and the emission intensity distribution at the incident surface where daylight is incident is derived using the first luminance distribution and the first contribution matrix. Furthermore, according to this embodiment, a second contribution matrix showing the magnitude of the influence of daylight on a second measurement point different from the first measurement point is obtained, and a second luminance distribution showing the luminance distribution at the second measurement point is estimated using the emission intensity distribution and the second contribution matrix. As a result, it becomes unnecessary to use a visible image at the second measurement point, and the luminance distribution at a measurement point different from the actual measurement point can be estimated without being affected by blind spots during shooting.

[0073] In the above embodiment, the case where illumination light from artificial lighting installed in the room to be estimated for luminance distribution is not considered was described, but the embodiment is not limited to this, and the illumination light from such artificial lighting may also be considered.

[0074] In this configuration, the first acquisition unit 11A further acquires a third contribution matrix, which indicates the magnitude of the influence on the first measurement point when the dimming rate of the illumination light due to artificial lighting is 100%, and the dimming rate itself. In this configuration, the derivation unit 11B derives the luminescence intensity distribution using the first luminance distribution, the first contribution matrix, the third contribution matrix, and the dimming rate.

[0075] In this configuration, the second acquisition unit 11C further acquires a fourth contribution matrix indicating the magnitude of the influence of the illumination light on the second measurement point, and the estimation unit 11D estimates the second luminance distribution using the emission intensity distribution, the second contribution matrix, the fourth contribution matrix, and the dimming rate. This configuration will be described in detail below.

[0076] When considering the actual operation of the luminance distribution estimation device 10 according to this embodiment in a building, the photometric quantity measured by the imaging device 30 may include components from artificial lighting as well as light sources from windows. In that case, the illuminance from artificial lighting should be subtracted.

[0077] The formula for that case is shown below. In the following formula, the subscripts A and B represent, respectively, w for the window, a for the artificial light, and t for the sum of the window and artificial light. Also, in the following formula, q is the number of elements in the luminescence intensity distribution of the artificial light.

[0078] The second term on the left side of equation (4) below calculates the illuminance due to artificial lighting. The contribution matrix aA corresponds to the third contribution matrix mentioned above, and is the illuminance that one artificial light or one control zone provides to the measurement point when the dimming rate is 100%. This contribution matrix aA can also be obtained by simulation using the physical lighting simulation program 13B, etc., but it is also possible to obtain the contribution matrix aA from measurements taken by the imaging device 30 at night when there is no daylight.

[0079] The dimming rate for each artificial light source or each control zone can be obtained from monitoring data from the central monitoring system. Therefore, by multiplying the contribution matrix aA by the vector of dimming rates for the artificial lights, the illuminance from the artificial lights can be obtained.

[0080]

number

[0081] Furthermore, after obtaining the luminescence intensity distribution of the window using equation (4), in the phase of calculating the photometric quantity at an arbitrary measurement point, by adding the illuminance due to artificial lighting as shown in equation (5) below, the photometric quantity at that arbitrary measurement point, i.e., the second luminance distribution described above, can be derived (estimated). However, in this case, the contribution matrix aB, i.e., the fourth contribution matrix described above, can be obtained by simulation using the physical lighting simulation program 13B, etc., but cannot be obtained from the measured values ​​from the imaging device 30.

[0082]

number

[0083] Furthermore, it goes without saying that the configurations of the various databases applied in the above embodiments are merely examples and are not limited to those exemplified.

[0084] Furthermore, in the above embodiment, for example, the hardware structure of the processing unit that executes the first acquisition unit 11A, the derivation unit 11B, the second acquisition unit 11C, and the estimation unit 11D can be any of the following types of processors. As mentioned above, these types of processors include a CPU, which is a general-purpose processor that executes software (programs) and functions as a processing unit, as well as programmable logic devices (PLDs), such as FPGAs (Field-Programmable Gate Arrays), which are processors whose circuit configuration can be changed after manufacturing, and dedicated electrical circuits, such as ASICs (Application Specific Integrated Circuits), which are processors with circuit configurations specifically designed to execute specific processes.

[0085] The processing unit may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the processing unit may consist of a single processor.

[0086] Examples of configuring a processing unit with a single processor include, firstly, a configuration where one or more CPUs and software are combined to form a single processor, as is common in client and server computers, and this processor functions as the processing unit. Secondly, a configuration using a processor that realizes the functions of the entire system, including the processing unit, on a single IC (Integrated Circuit) chip, as is common in System-on-a-Chip (SoC) systems. Thus, the processing unit is configured, in terms of hardware structure, using one or more of the above types of processors.

[0087] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits, which are combinations of circuit elements such as semiconductor devices. [Explanation of Symbols]

[0088] 10. Brightness distribution estimation device 11 CPU 11A 1st acquisition part 11B Derivation part 11C 2nd acquisition part 11D Estimation section 12 memory 13 Storage section 13A Brightness Distribution Estimation Program 13B Physical Lighting Simulation Program 13C Building-Related Information Database 13D Brightness Distribution Information Database 14 Input section 15 Display 15A Input Area 15B Exit button 16. Media reading / writing device 17 Recording media 18 Communication I / F Section 30 Imaging device

Claims

1. A first acquisition unit that acquires a first luminance distribution showing the luminance distribution obtained by measurement at a predetermined first measurement point, and a first contribution matrix showing the magnitude of the influence of daylight on the first measurement point, A derivation unit that derives the emission intensity distribution at the incident surface into which the daylight is incident using the first luminance distribution and the first contribution matrix, A second acquisition unit acquires a second contribution matrix that shows the magnitude of the influence that the daylight has on a second measurement point different from the first measurement point, An estimation unit that estimates a second luminance distribution showing the luminance distribution at the second measurement point using the luminance intensity distribution and the second contribution matrix, A luminance distribution estimation device equipped with the following features.

2. The first acquisition unit further acquires a third contribution matrix showing the magnitude of the influence on the first measurement point when the dimming rate of the illumination light due to artificial lighting is 100%, and the dimming rate. The derivation unit derives the emission intensity distribution using the first luminance distribution, the first contribution matrix, the third contribution matrix, and the dimming rate. The second acquisition unit further acquires a fourth contribution matrix that shows the magnitude of the influence that the illumination light has on the second measurement point. The estimation unit estimates the second luminance distribution using the emission intensity distribution, the second contribution matrix, the fourth contribution matrix, and the dimming rate. The luminance distribution estimation device according to claim 1.

3. A first luminance distribution is obtained, which shows the luminance distribution obtained by measurement at a predetermined first measurement point, and a first contribution matrix is ​​obtained, which shows the magnitude of the influence of daylight on the first measurement point. Using the first luminance distribution and the first contribution matrix, the emission intensity distribution at the incident surface to which the daylight is incident is derived. A second contribution matrix is ​​obtained that shows the magnitude of the influence that the daylight has on a second measurement point different from the first measurement point. Using the emission intensity distribution and the second contribution matrix, a second luminance distribution showing the luminance distribution at the second measurement point is estimated. A program for estimating brightness distribution to enable a computer to perform the processing.

Images