Estimating system and estimating method

Abstract

The present disclosure addresses the problem of identifying information relating to lighting fixtures in a reference image. An estimating system (1) according to the present disclosure comprises an input unit (31), an extracting unit (211), and an identifying unit (212). The input unit (31) accepts input of a reference image. The extracting unit (211) estimates and extracts, from the reference image accepted by the input unit (31), a fixture feature, which is a feature of the lighting fixtures disposed in a space in the reference image. The identifying unit (212) identifies fixture information, which is information relating to the lighting fixtures, from the fixture feature extracted by the extracting unit (211). The fixture feature includes at least one of the illumination range of light from each lighting fixture, the color temperature of the light, the number of lighting fixtures arranged in the space, and the position of the lighting fixtures in the space.

Description

Estimation System and Estimation Method

[0001] The present disclosure relates to an estimation system and an estimation method. More specifically, the present disclosure relates to an estimation system and an estimation method including an input unit that receives an input of a reference image.

[0002] Patent Document 1 describes a method of lighting simulation using the Internet.

[0003] In the lighting simulation method described in Patent Document 1, for example, there is a problem that it is difficult to specify information (for example, product number) regarding a lighting fixture in an image (reference image) found on SNS.

[0004] Japanese Patent Application Laid-Open No. 2002-334119

[0005] An object of the present disclosure is to provide an estimation system and an estimation method capable of specifying information regarding a lighting fixture in a reference image.

[0006] An estimation system according to one aspect of the present disclosure includes an input unit, an extraction unit, and a specification unit. The input unit receives an input of a reference image. The extraction unit estimates and extracts a fixture feature amount, which is a feature amount of a lighting fixture arranged in a space in the reference image, from the reference image received by the input unit. The specification unit specifies fixture information, which is information regarding the lighting fixture, from the fixture feature amount extracted by the extraction unit. The fixture feature amount includes at least one of an irradiation range of light from the lighting fixture, a color temperature of the light, the number of the lighting fixtures arranged in the space, and a position of the lighting fixture in the space.

[0007] An estimation method according to one aspect of the present disclosure comprises an input step, an extraction step, and a identification step. In the input step, a reference image is received as input. In the extraction step, fixture features, which are characteristic quantities of lighting fixtures arranged in the space within the reference image, are estimated and extracted from the reference image received in the input step. In the identification step, fixture information, which is information about the lighting fixtures, is identified from the fixture features extracted in the extraction step. The fixture features include at least one of the following: the irradiation range of light from the lighting fixture, the color temperature of the light, the number of lighting fixtures arranged in the space, and the position of the lighting fixtures in the space.

[0008] Figure 1 is a block diagram of the estimation system according to the embodiment. Figure 2 is a schematic diagram showing a reference image displayed on an information terminal used in the estimation system. Figure 3 is a schematic diagram showing an example of output from an information terminal used in the estimation system. Figure 4 is a flowchart of the estimation method executed by the estimation system. Figure 5 is a schematic diagram showing a facility image displayed on an information terminal used in the estimation system according to the first modified embodiment. Figure 6 is a schematic diagram showing a proposed image displayed on an information terminal used in the estimation system. Figure 7 is a block diagram of the control unit in the estimation system according to the second modified embodiment. Figure 8 is a block diagram of the control unit in the estimation system according to the third modified embodiment. Figure 9 is a block diagram of the control unit in the estimation system according to the fourth modified embodiment.

[0009] The estimation system and estimation method according to the embodiments will be described below with reference to the drawings. The drawings referenced in the following embodiments are schematic diagrams, and the size and thickness of the components shown in the drawings do not necessarily reflect the actual dimensions, nor do the size ratios and thickness ratios between components necessarily reflect the actual dimensional ratios.

[0010] (Embodiment) (1) Overview First, an overview of the estimation system 1 according to the embodiment will be described with reference to Figures 1 to 3.

[0011] As shown in Figure 2, the estimation system 1 according to this embodiment is a system that estimates fixture features, which are characteristic quantities of lighting fixtures 100 located in space SP1 within reference image Im1, and identifies fixture information In1 (see Figure 3), which is information about the lighting fixtures 100, from the estimated fixture features.

[0012] As shown in Figure 1, the estimation system 1 according to the embodiment comprises an input unit 31, an extraction unit 211, and a identification unit 212. The input unit 31 receives a reference image Im1 (see Figure 2) as input. The extraction unit 211 estimates fixture features, which are characteristic quantities of lighting fixtures 100 (see Figure 2) arranged in space SP1 (see Figure 2) within the reference image Im1, from the reference image Im1 received by the input unit 31, and extracts the estimated fixture features. The identification unit 212 identifies fixture information In1 (see Figure 3), which is information about the lighting fixtures 100, from the fixture features extracted by the extraction unit 211. The fixture features include at least one of the following: the irradiation range of light from the lighting fixtures 100, the color temperature of the light from the lighting fixtures 100, the number of lighting fixtures 100 arranged in space SP1, and the position of the lighting fixtures 100 in space SP1.

[0013] In the estimation system 1 according to this embodiment, the extraction unit 211 estimates and extracts fixture features, which are characteristic quantities of the lighting fixture 100, from the reference image Im1 received by the input unit 31, and the identification unit 212 identifies fixture information In1, which is information about the lighting fixture 100, from the fixture features extracted by the extraction unit 211. In other words, according to the estimation system 1 according to this embodiment, it is possible to identify information about the lighting fixture 100 (fixture information In1) within the reference image Im1.

[0014] (2) Details Next, each component of the estimation system 1 according to the embodiment will be described with reference to Figures 1 to 3.

[0015] As described above, the estimation system 1 according to the embodiment is a system that estimates the fixture features of a lighting fixture 100 located in space SP1 within a reference image Im1, and identifies fixture information In1 of the lighting fixture 100 from the estimated fixture features.

[0016] As shown in Figure 1, the estimation system 1 according to this embodiment comprises a server device 2 and an information terminal 3. The information terminal 3 is, for example, a smartphone, tablet device, or personal computer owned by the user. In this embodiment, as an example, the information terminal 3 is a tablet device (see Figures 2 and 3).

[0017] (2.1) Server device Server device 2 can be implemented, for example, by a computer system having one or more processors and one or more memories. That is, it functions as a server device 2 by one or more processors executing a program recorded in one or more memories of the computer system. The program is here pre-recorded in the memory of the computer system, but it may also be provided via a telecommunication line such as the Internet, or it may be provided recorded on a non-temporary recording medium such as a memory card.

[0018] As shown in Figure 1, the server device 2 comprises a control unit 21, a storage unit 22, and a communication unit 23.

[0019] (2.1.1) Control Unit The control unit 21 performs overall control of the server device 2. The control unit 21 is electrically connected to the storage unit 22 and the communication unit 23. The control unit 21 controls the storage unit 22 to store information in the storage unit 22 and to read information from the storage unit 22. The control unit 21 also controls the communication unit 23 to communicate with the information terminal 3. The control unit 21 includes an extraction unit 211 and a specification unit 212 (see Figure 1).

[0020] The extraction unit 211 estimates the fixture features, which are the feature quantities of the lighting fixtures 100 (see Figure 2) arranged in space SP1 (see Figure 2) within the reference image Im1 (see Figure 2), from the reference image Im1 (see Figure 2) received by the input unit 31 of the information terminal 3 described later, and extracts the estimated fixture features. In the example in Figure 2, multiple lighting fixtures 100 are arranged in space SP1. More specifically, the multiple lighting fixtures 100 include a first lighting fixture 100A, a second lighting fixture 100B, and a third lighting fixture 100C. The first lighting fixture 100A is, for example, a spotlight mounted on the wall surface of space SP1. The second lighting fixture 100B is, for example, a pendant light suspended from the ceiling surface of space SP1. The third lighting fixture 100C is, for example, a downlight mounted on the ceiling surface of space SP1. Furthermore, the fixture features include at least one of the following: the illumination range of the light emitted from the luminaire 100, the color temperature of the light emitted from the luminaire 100, the number of luminaires 100s arranged in space SP1 within reference image Im1, and the position of the luminaire 100 in space SP1 within reference image Im1. In this embodiment, as an example, the fixture features include all of the following: the illumination range of the light emitted from the luminaire 100, the color temperature of the light emitted from the luminaire 100, the number of luminaires 100s arranged in space SP1 within reference image Im1, and the position of the luminaire 100 in space SP1 within reference image Im1.

[0021] The identification unit 212 identifies fixture information In1 (see Figure 3), which is information about the lighting fixture 100, from the fixture feature quantities extracted by the extraction unit 211. The fixture information In1 includes, for example, type information, which is information about the type of lighting fixture 100. Specifically, the type information includes, for example, the name of the lighting fixture 100 and at least one of the part number of the lighting fixture 100. In this embodiment, as an example, the type information includes both the name of the lighting fixture 100 and the part number of the lighting fixture 100.

[0022] More specifically, the identification unit 212 identifies the type information as instrument information In1 based on the instrument features extracted by the extraction unit 211 and the instrument features stored in the storage unit 22, which will be described later. Specifically, the identification unit 212 compares the instrument features extracted by the extraction unit 211 with the instrument features stored in the storage unit 22, reads the type information from the storage unit 22 that is associated with the instrument feature that is most similar to the instrument feature extracted by the extraction unit 211 among the multiple instrument features stored in the storage unit 22, and identifies it as instrument information In1.

[0023] (2.1.2) Memory Unit The memory unit 22 includes, for example, ROM (Read Only Memory), RAM (Random Access Memory), EEPROM (Electrically Erasable Programmable Read Only Memory), etc. The memory unit 22 stores type information, which is information about the type of lighting fixture 100, and fixture characteristics of the lighting fixture 100, linked together.

[0024] (2.1.3) Communication Unit The communication unit 23 includes a communication interface for communicating with the information terminal 3. The communication unit 23 communicates with the communication unit 34 of the information terminal 3, which will be described later, via a network such as the Internet. By communicating with the communication unit 34, the communication unit 23 receives (acquires) the reference image Im1 received by the input unit 31 of the information terminal 3. The communication unit 23 also transmits the device information In1 identified by the identification unit 212 by communicating with the communication unit 34. The information terminal 3 displays the device information In1 received by the communication unit 34 on the display unit 30. This makes it possible to notify the user of the device information In1 identified based on the reference image Im1.

[0025] (2.2) Information Terminal As described above, the information terminal 3 is, for example, a tablet terminal owned by the user. The information terminal 3 can be realized by, for example, a computer system having one or more processors and one or more memories. That is, the information terminal 3 functions by one or more processors executing a program recorded in one or more memories of the computer system. The program is here pre-recorded in the memory of the computer system, but it may also be provided via a telecommunication line such as the Internet, or it may be recorded and provided on a non-temporary recording medium such as a memory card.

[0026] As shown in Figure 1, the information terminal 3 comprises an input unit 31, an output unit 32, a control unit 33, a communication unit 34, and a storage unit 35.

[0027] (2.2.1) Input Unit The input unit 31 receives input of a reference image Im1. The reference image Im1 is, for example, an image of interior design found on SNS (Social Networking Service) or in a physical store. More specifically, the reference image Im1 is an image of a space SP1 in which multiple lighting fixtures 100 are installed, as shown in Figure 2. The space SP1 is, for example, a living room. In this embodiment, since the information terminal 3 is a tablet terminal, the input unit 31 is configured by the touch panel of the tablet terminal.

[0028] (2.2.2) Output Unit The output unit 32 outputs the fixture information In1 identified by the identification unit 212. In this embodiment, the control unit 33 displays the fixture information In1 identified by the identification unit 212 on the display unit 30 of the information terminal 3 (see Figure 3). In the example of Figure 3, the fixture information In1 is data of image Im2 that includes the name and part number of the first lighting fixture 100A, which is a spotlight, the name and part number of the second lighting fixture 100B, which is a pendant light, and the name and part number of the third lighting fixture 100C, which is a downlight. In this way, the control unit 33 can present the fixture information In1 to the user by displaying it on the display unit 30 of the information terminal 3.

[0029] (2.2.3) Control Unit The control unit 33 performs overall control of the information terminal 3. The control unit 33 is electrically connected to the input unit 31, the output unit 32, the communication unit 34, and the storage unit 35. The control unit 33 acquires the reference image Im1 received by the input unit 31 from the input unit 31. The control unit 33 controls the output unit 32 to output (display) the device information In1 to the output unit 32 (display unit 30). The control unit 33 controls the communication unit 34 to communicate with the communication unit 23 of the server device 2. The control unit 33 controls the storage unit 35 to store information in the storage unit 35 and to read information from the storage unit 35.

[0030] (2.2.4) Communication Unit The communication unit 34 includes a communication interface for communicating with the server device 2. The communication unit 34 communicates with the communication unit 23 of the server device 2, for example, via a network such as the Internet. By communicating with the communication unit 23, the communication unit 34 receives the device information In1 identified by the identification unit 212. The communication unit 34 also transmits the reference image Im1 received by the input unit 31 by communicating with the communication unit 23.

[0031] (2.2.5) Storage Unit The storage unit 35 includes, for example, memory such as ROM, RAM, and EEPROM. The storage unit 35 stores, for example, the device information In1 sent from the server device 2. The storage unit 35 may also store the device information In1 in association with the reference image Im1 received by the input unit 31.

[0032] (3) Estimation Method Next, the estimation method according to the embodiment will be described with reference to Figure 4. The estimation method according to the embodiment is performed, for example, by the estimation system 1 according to the embodiment. However, the entity that performs the estimation method is not limited to the estimation system 1.

[0033] The estimation method according to the embodiment, as shown in Figure 4, comprises an input step ST1, an extraction step ST2, and a identification step ST3. In the input step ST1, a reference image Im1 (see Figure 2) is received as input. In the extraction step ST2, from the reference image Im1 received in the input step ST1, fixture features, which are characteristic quantities of the lighting fixtures 100 arranged in space SP1 within the reference image Im1, are estimated, and the estimated fixture features are extracted. In the identification step ST3, fixture information In1 (see Figure 3), which is information about the lighting fixtures 100, is identified from the fixture features extracted in the extraction step ST2. The fixture features include at least one of the following: the irradiation range of the light emitted from the lighting fixtures 100, the color temperature of the light emitted from the lighting fixtures 100, the number of lighting fixtures 100 arranged in space SP1, and the position of the lighting fixtures 100 in space SP1.

[0034] In the estimation method according to this embodiment, in the extraction step ST2, the input unit 31 extracts fixture features, which are characteristic quantities of the lighting fixture 100, from the reference image Im1 received by the input unit 31, and in the identification step ST3, fixture information In1, which is information about the lighting fixture 100, is identified from the fixture features extracted in the extraction step ST2. In other words, according to the estimation method according to this embodiment, it is possible to identify information about the lighting fixture 100 in the reference image Im1.

[0035] Figure 4 is a flowchart showing the estimation method performed by the estimation system 1 according to the embodiment. The estimation method includes steps ST1 to ST4 shown in Figure 4. Note that the flowchart shown in Figure 4 is an example, and one or more steps other than steps ST1 to ST4 shown in Figure 4 may be included. Also, the output step ST4 may be omitted. The estimation method according to the embodiment will be described in detail below.

[0036] First, the estimation system 1 executes the input step ST1. More specifically, in the input step ST1, the input unit 31 of the estimation system 1 receives the input of a reference image Im1 (see Figure 2). The data of the reference image Im1 received by the input unit 31 is transmitted from the information terminal 3 to the server device 2 through communication between the server device 2 and the information terminal 3.

[0037] Next, the estimation system 1 executes the extraction step ST2. More specifically, in the extraction step ST2, the extraction unit 211 of the estimation system 1 estimates the fixture features, which are the feature quantities of the lighting fixtures 100 located in the space SP1 within the reference image Im1, from the reference image Im1 received by the input unit 31, and extracts the estimated fixture features.

[0038] Furthermore, the estimation system 1 executes the identification step ST3. More specifically, in the identification step ST3, the identification unit 212 of the estimation system 1 identifies the fixture information In1, which is information about the lighting fixture 100, from the fixture features extracted by the extraction unit 211. Specifically, in the identification step ST3, the identification unit 212 compares the fixture features extracted by the extraction unit 211 with the fixture features stored in the storage unit 22, reads the type information associated with the fixture feature with the highest similarity among the multiple fixture features stored in the storage unit 22, and identifies it as fixture information In1.

[0039] Then, the estimation system 1 executes the output step ST4. More specifically, in the output step ST4, the output unit 32 of the estimation system 1 outputs the equipment information In1 identified by the identification unit 212. Specifically, the display unit 30, which is the output unit 32, displays the image Im2 (equipment information In1) shown in Figure 3.

[0040] (4) Effects In the estimation system 1 according to the embodiment, the extraction unit 211 extracts fixture feature quantities, which are feature quantities of the lighting fixture 100, from the reference image Im1 received by the input unit 31, and the identification unit 212 identifies fixture information In1, which is information about the lighting fixture 100, from the fixture feature quantities extracted by the extraction unit 211. In other words, according to the estimation system 1 according to the embodiment, it is possible to identify information about the lighting fixture 100 in the reference image Im1. Furthermore, as in this embodiment, by displaying the fixture information In1 identified by the identification unit 212 on the display unit 30 of the information terminal 3, it is possible to present the fixture information In1 to the user.

[0041] In the estimation system 1 according to the embodiment, by simply comparing the appliance feature amount extracted by the extraction unit 211 with the appliance feature amount stored in the storage unit 22, it becomes possible to specify the type information as the appliance information In1.

[0042] (5) Modified Example The above-described embodiment is merely one of various embodiments of the present disclosure. The above-described embodiment can be variously modified according to the design and the like as long as the object of the present disclosure can be achieved. Further, the same function as that of the estimation system 1 according to the above-described embodiment may be embodied by the above-described estimation method, (computer) program, or non-temporary recording medium recording the program.

[0043] Hereinafter, modified examples of the above-described embodiment will be listed. The modified examples described below can be applied in appropriate combinations.

[0044] (5.1) Modified Example 1 Hereinafter, the estimation system 1 according to Modified Example 1 will be described. Regarding the estimation system 1 according to Modified Example 1, the same components as those of the estimation system 1 according to the above-described embodiment will be denoted by the same reference numerals and the description thereof will be omitted.

[0045] In the estimation system 1 according to Modified Example 1, the input unit 31 is configured to receive the input of the facility image Im3 (see FIG. 5) in addition to the reference image Im1. The facility image Im3 is an image of the target facility FA1. The target facility FA1 is, for example, a housing facility such as each dwelling unit of a detached house or an apartment house, or a non-housing facility such as an office, a store, a school, or a care facility. In Modified Example 1, as an example, the target facility FA1 is each dwelling unit or each room of an apartment house. That is, the input unit 31 further receives the input of the facility image Im3 which is an image of the target facility FA1.

[0046] Further, as shown in FIG. 6, the estimation system 1 according to Modified Example 1 further includes an output unit 32 that outputs a proposed image Im4. The proposed image Im4 is an image in which the lighting fixture 100 corresponding to the appliance information In1 specified by the specifying unit 212 is superimposed on the facility image Im3. In the example of FIG. 6, the proposed image Im4 is an image in which the spotlight as the first lighting fixture 100A, the pendant light as the second lighting fixture 100B, and the downlight as the third lighting fixture 100C are superimposed on the facility image Im3.

[0047] According to the estimation system 1 according to the first modification example, it is possible to output a proposed image Im4 in which the lighting fixture 100 corresponding to the fixture information In1 is superimposed on the facility image Im3. As a result, it is possible to visually give the user an image of the target facility FA1 by the lighting fixture 100 similar to the lighting fixture 100 arranged in the space SP1 in the reference image Im1.

[0048] Here, the input unit 31 may be configured to receive an input for correcting the proposed image Im4 (see FIG. 6) output from the output unit 32 (display unit 30). As an example, it is possible to change, delete, add, or change the position of the type of the lighting fixture 100 included in the proposed image Im4 according to the correction input received by the input unit 31. Thereby, it is possible to correct the proposed image Im4 presented by the information terminal 3 of the estimation system 1 according to the user's preference.

[0049] (5.2) Second modification example Next, the estimation system 1 according to the second modification example will be described with reference to FIG. 7. Regarding the estimation system 1 according to the second modification example, the same components as those of the estimation system 1 according to the above-described embodiment are denoted by the same reference numerals and the description thereof is omitted.

[0050] In the estimation system 1 according to the second modification example, the server device 2 includes a control unit 21A, a storage unit 22, and a communication unit 23. The control unit 21A includes an extraction unit 211, a specification unit 212, and a generation unit 213.

[0051] The generation unit 213 generates the fixture feature amount of each lighting fixture 100 from the catalog information of the lighting fixture 100. As described above, the fixture feature amount includes at least one of the irradiation range of the light emitted from the lighting fixture 100, the color temperature of the light emitted from the lighting fixture 100, the number of lighting fixtures 100 arranged in the space SP1 in the reference image Im1, and the position of the lighting fixture 100 in the space SP1 in the reference image Im1.

[0052] Furthermore, the memory unit 22 stores the device feature quantities generated by the generation unit 213 in association with the device information In1. As described above, the device information In1 includes, for example, the name and model number of the lighting fixture 100.

[0053] Then, the identification unit 212 identifies the fixture information In1 based on the fixture features extracted by the extraction unit 211 and the fixture features stored in the storage unit 22. More specifically, the identification unit 212 compares the fixture features extracted by the extraction unit 211 with the fixture features stored in the storage unit 22, and reads out the fixture information In1 of the lighting fixture 100 corresponding to the fixture feature with the highest similarity among the multiple fixture features stored in the storage unit 22 from the storage unit 22.

[0054] According to the estimation system 1 in modified example 2, since the equipment information In1 is identified based on catalog information, it becomes possible to identify the equipment information In1 with higher accuracy.

[0055] (5.3) Modification 3 Hereinafter, the estimation system 1 according to Modification 3 will be described with reference to Figure 8. With respect to the estimation system 1 according to Modification 3, components similar to those of the estimation system 1 according to the above embodiment will be denoted by the same reference numerals and their description will be omitted.

[0056] In the estimation system 1 according to modified example 3, the server device 2 comprises a control unit 21B, a storage unit 22, and a communication unit 23. The control unit 21B also includes an extraction unit 211, a specific unit 212, and a furniture extraction unit 214.

[0057] Unlike the extraction unit 211, the furniture extraction unit 214 estimates and extracts furniture feature quantities, which are the feature quantities of furniture located in space SP1 within the reference image Im1 received by the input unit 31. The furniture located in space SP1 includes, for example, desks, chairs, sofas, and shelves. The furniture feature quantities include, for example, at least one of the shape and material of the desk, chair, sofa, and shelf.

[0058] Furthermore, the memory unit 22 stores furniture information and furniture features, which are information related to furniture. The furniture information includes, for example, the names and model numbers of furniture such as desks, chairs, sofas, and shelves.

[0059] Then, the identification unit 212 identifies furniture information based on the furniture features extracted by the furniture extraction unit 214 and the furniture features stored in the storage unit 22. More specifically, the identification unit 212 compares the furniture features extracted by the furniture extraction unit 214 with the furniture features stored in the storage unit 22, and reads out the furniture information from the storage unit 22 for the furniture corresponding to the furniture feature with the highest similarity among the multiple furniture features stored in the storage unit 22.

[0060] According to the estimation system 1 related to the modified example 3, it is possible to identify not only the equipment information In1 but also the furniture information.

[0061] In the modified example 3, the extraction unit 211 and the furniture extraction unit 214 are provided separately, but the extraction unit 211 may also function as the furniture extraction unit 214. That is, the extraction unit 211 may be configured to extract both the appliance features and the furniture features.

[0062] (5.4) Modification 4 Hereinafter, the estimation system 1 according to Modification 4 will be described with reference to Figure 9. With respect to the estimation system 1 according to Modification 4, components similar to those of the estimation system 1 according to the above embodiment will be denoted by the same reference numerals and their description will be omitted.

[0063] In the estimation system 1 according to modified example 4, the server device 2 comprises a control unit 21C, a storage unit 22, and a communication unit 23. The control unit 21C also includes an extraction unit 211, a specification unit 212, and an internal extraction unit 215.

[0064] Unlike the extraction unit 211, the interior extraction unit 215 estimates and extracts interior feature quantities, which are the feature quantities of the interior of space SP1 within the reference image Im1 received by the input unit 31. The interior of space SP1 includes, for example, wallpaper and flooring. If the interior of space SP1 is wallpaper, the interior feature quantities include, for example, at least one of the wallpaper pattern and the wallpaper color. If the interior of space SP1 is flooring, the interior feature quantities include, for example, at least one of the flooring material and the flooring shape.

[0065] Furthermore, the memory unit 22 stores interior information and interior feature quantities, which are information related to the interior. The interior information includes, for example, the names and product numbers of interior materials such as wallpaper and flooring.

[0066] Then, the identification unit 212 identifies the interior information based on the interior feature quantities extracted by the interior extraction unit 215 and the interior feature quantities stored in the storage unit 22. More specifically, the identification unit 212 compares the interior feature quantities extracted by the interior extraction unit 215 with the interior feature quantities stored in the storage unit 22, and reads the interior information from the storage unit 22 that corresponds to the interior feature quantity with the highest similarity among the multiple interior feature quantities stored in the storage unit 22.

[0067] According to the estimation system 1 in modified example 4, it is possible to identify not only the fixture information In1 but also the interior information.

[0068] In the modified example 4, the extraction unit 211 and the interior extraction unit 215 are provided separately, but the extraction unit 211 may also function as the interior extraction unit 215. That is, the extraction unit 211 may be configured to extract both the instrument features and the interior features.

[0069] (5.5) Modification 5 In the above embodiment, the storage unit 22 stores type information, which is information about the type of lighting fixture 100, and fixture feature quantities linked together. In contrast, the storage unit 22 may store feature information, which is information about the characteristics of the lighting fixture 100, and fixture feature quantities linked together. The feature information includes, for example, the fixture type of the lighting fixture 100, the output characteristics of the lighting fixture 100, and the color temperature of the light emitted from the lighting fixture 100. The fixture type of the lighting fixture 100 includes, for example, a name indicating the type of lighting fixture 100 (e.g., spotlight, downlight, pendant light). The output characteristics of the lighting fixture 100 include, for example, the light distribution characteristics of the light emitted from the lighting fixture 100, and the power consumption of the lighting fixture 100.

[0070] Then, the identification unit 212 identifies characteristic information as fixture information In1 based on the fixture feature quantities extracted by the extraction unit 211 and the fixture feature quantities stored in the storage unit 22. More specifically, the identification unit 212 compares the fixture feature quantities extracted by the extraction unit 211 with the fixture feature quantities stored in the storage unit 22, and reads out the fixture information In1 (characteristic information) of the lighting fixture 100 corresponding to the fixture feature quantity with the highest similarity among the multiple fixture feature quantities stored in the storage unit 22 from the storage unit 22.

[0071] According to the estimation system 1 of modified example 5, it is possible to identify information regarding the lighting fixture 100 in the reference image Im1, similar to the estimation system 1 of the above embodiment.

[0072] (5.6) Modification 6 In the above embodiment, the input unit 31 is configured to receive input of a reference image Im1. In contrast, the input unit 31 may be configured to receive input of floor plan information, which is information relating to the floor plan of the target facility FA1, in addition to input of the reference image Im1. That is, the input unit 31 further receives input of floor plan information, which is information relating to the floor plan of the target facility FA1.

[0073] Then, the identification unit 212 further identifies combinations of lighting fixtures 100 according to the floor plan information received by the input unit 31. More specifically, the identification unit 212 identifies at least one of the type (fixture type) and number of lighting fixtures 100 suitable for the target facility FA1, according to the floor plan information received by the input unit 31.

[0074] According to the estimation system 1 in modified example 6, it is also possible to identify combinations of lighting fixtures 100.

[0075] (5.7) Modification 7 In the above embodiment, the input unit 31 is configured to receive input of a reference image Im1. In contrast, the input unit 31 may be configured to receive input of budget information in addition to input of a reference image Im1. The budget information is information relating to the cost of installing the lighting fixture 100 at the target facility FA1. That is, the input unit 31 further receives input of budget information which is information relating to the cost of installing the lighting fixture 100 at the target facility FA1.

[0076] The memory unit 22 stores multiple pieces of equipment information In1 and multiple pieces of budget information in association with each other. Here, the multiple pieces of equipment information In1 and the multiple pieces of budget information may be linked on a one-to-one basis, or they may be linked on a one-to-many basis.

[0077] Then, the identification unit 212 selects (identifies) one or more pieces of equipment information In1 from among the multiple pieces of equipment information In1 stored in the storage unit 22, according to the budget information received by the input unit 31.

[0078] According to the estimation system 1 of modified example 7, it is possible to identify one or more pieces of equipment information In1 corresponding to the budget information received by the input unit 31.

[0079] (5.8) Modification 8 In the above-described embodiment, the input unit 31 is configured to receive input of reference image Im1. In contrast, the input unit 31 may be configured to receive input of text relating to the lighting fixture 100 in addition to input of reference image Im1. That is, in Modification 8, the input unit 31 further receives input of text relating to the lighting fixture 100.

[0080] In the modified example 8, the extraction unit 211 estimates and extracts instrument features from the reference image Im1 and text received by the input unit 31. The text is, for example, a document describing the reference image Im1 found on social media or in a magazine. This makes it possible to improve the estimation accuracy of the extraction unit 211 compared to estimating instrument features based solely on the reference image Im1.

[0081] (5.9) Other variations The following are other variations.

[0082] The entity that executes the estimation system 1 or estimation method in this disclosure includes a computer system. The computer system mainly consists of a processor and memory as hardware. The processor executes a program recorded in the memory of the computer system, thereby realizing the function of the entity that executes the estimation system 1 or estimation method in this disclosure. The program may be pre-recorded in the memory of the computer system, provided via a telecommunications line, or provided on a non-temporary recording medium such as a memory card, optical disk, or hard disk drive that can be read by the computer system. The processor of the computer system consists of one or more electronic circuits including semiconductor integrated circuits (ICs) or large-scale integrated circuits (LSIs). The integrated circuits such as ICs or LSIs referred to here are named differently depending on the degree of integration, and include integrated circuits called system LSIs, VLSIs (Very Large Scale Integrations), or ULSIs (Ultra Large Scale Integrations). Furthermore, FPGAs (Field-Programmable Gate Arrays) that are programmed after the manufacture of the LSI, or logic devices that allow for the reconfiguration of junction relationships or circuit compartments within the LSI, can also be used as processors. Multiple electronic circuits may be integrated onto a single chip or distributed across multiple chips. Multiple chips may be integrated onto a single device or distributed across multiple devices. The computer system referred to here includes a microcontroller having one or more processors and one or more memories. Therefore, the microcontroller also consists of one or more electronic circuits, including semiconductor integrated circuits or large-scale integrated circuits.

[0083] Furthermore, it is not essential for the estimation system 1 to have multiple functions integrated into a single enclosure; the components of the estimation system 1 may be distributed across multiple enclosures. Moreover, at least some of the functions of the estimation system 1, for example, the functions of the control unit 21 of the server device 2, may be implemented by the cloud (cloud computing) or the like.

[0084] Conversely, in the above-described embodiment, at least some of the functions of the estimation system 1, which are distributed across multiple devices, may be consolidated into a single enclosure. For example, some of the functions of the estimation system 1, which are distributed across a server device 2 and an information terminal 3, may be consolidated into a single enclosure.

[0085] In the above-described embodiment, the estimation system 1 is equipped with an output unit 32, but the estimation system 1 does not need to be equipped with an output unit 32. In other words, the output unit 32 may be omitted.

[0086] At least some of the functions of server device 2 may be implemented in the cloud.

[0087] In the above-described embodiment, the output unit 32 is the display unit 30 of the information terminal 3, and displays the equipment information In1 on the display unit 30. In contrast, the output unit 32 may output the equipment information In1 to another system or device different from the estimation system 1, for example. In addition to the equipment information In1, the output unit 32 may also output equipment feature quantities.

[0088] In the embodiment described above, the identification unit 212 compares the device feature quantities extracted by the extraction unit 211 with the device feature quantities stored in the storage unit 22, and selects the device information In1 corresponding to the device feature quantity with the highest similarity among the multiple device feature quantities stored in the storage unit 22. Alternatively, the identification unit 212 may compare the device feature quantities extracted by the extraction unit 211 with the device feature quantities stored in the storage unit 22, and select multiple device information In1 corresponding to multiple device feature quantities in descending order of similarity among the multiple device feature quantities stored in the storage unit 22.

[0089] In the above-described embodiment, the reference image Im1 received by the input unit 31 is a still image. In contrast, for example, in the case of a lighting fixture where the light fluctuates, it is preferable that the reference image be a moving image.

[0090] In the above-described embodiment, the fixture features include at least one of the following: the illumination range of the light emitted from the luminaire 100, the color temperature of the light emitted from the luminaire 100, the number of luminaires 100 arranged in space SP1 within reference image Im1, and the position of the luminaire 100 in space SP1 within reference image Im1. The fixture features may further include the light distribution pattern of the luminaire 100, light distribution data, the brightness of the light emitted from the luminaire 100, and so on.

[0091] (Aspects) The following aspects are disclosed in this specification.

[0092] The estimation system (1) according to the first embodiment comprises an input unit (31), an extraction unit (211), and a specification unit (212). The input unit (31) receives a reference image (Im1) as input. The extraction unit (211) estimates and extracts fixture features, which are feature quantities of lighting fixtures (100) arranged in the space (SP1) within the reference image (Im1), from the reference image (Im1) received by the input unit (31). The specification unit (212) identifies fixture information (In1), which is information about the lighting fixtures (100), from the fixture features extracted by the extraction unit (211). The fixture features include at least one of the following: the irradiation range of light from the lighting fixtures (100), the color temperature of the light, the number of lighting fixtures (100) arranged in the space (SP1), and the position of the lighting fixtures (100) in the space (SP1).

[0093] According to this embodiment, it becomes possible to identify information regarding the lighting fixture (100) in the reference image (Im1).

[0094] The estimation system (1) according to the second embodiment further comprises a memory unit (22) in the first embodiment. The memory unit (22) stores type information, which is information relating to the type of lighting fixture (100), and fixture features in association. The identification unit (212) identifies the type information as fixture information (In1) based on the fixture features extracted by the extraction unit (211) and the fixture features stored in the memory unit (22).

[0095] According to this embodiment, it becomes possible to identify instrument information (In1) based on the instrument features extracted by the extraction unit (211) and the instrument features stored in the storage unit (22).

[0096] The estimation system (1) according to the third embodiment further comprises a memory unit (22) in the first embodiment. The memory unit (22) stores characteristic information, which includes the fixture type of the lighting fixture (100), the output characteristics of the lighting fixture (100), and the color temperature of the light from the lighting fixture (100), in association with fixture features. The identification unit (212) identifies the characteristic information as fixture information (In1) based on the fixture features extracted by the extraction unit (211) and the fixture features stored in the memory unit (22).

[0097] According to this embodiment, it becomes possible to identify instrument information (In1) based on the instrument features extracted by the extraction unit (211) and the instrument features stored in the storage unit (22).

[0098] In the estimation system (1) according to the fourth embodiment, in any one of the first to third embodiments, the input unit (31) further receives input of floor plan information, which is information relating to the floor plan of the target facility (FA1). The identification unit (212) further identifies combinations of lighting fixtures (100) according to the floor plan information received by the input unit (31).

[0099] According to this embodiment, it is also possible to specify the combination of lighting fixtures (100).

[0100] In the estimation system (1) according to the fifth embodiment, in any one of the first to fourth embodiments, the input unit (31) further accepts input of budget information, which is information regarding the cost of installing lighting fixtures (100) at the target facility (FA1). The estimation system (1) further includes a storage unit (22) that stores multiple fixture information (In1) and multiple budget information in association with each other. The identification unit (212) identifies the fixture information (In1) corresponding to the budget information received by the input unit (31) from among the multiple fixture information (In1) stored in the storage unit (22).

[0101] According to this embodiment, it becomes possible to identify equipment information (In1) corresponding to the budget information received by the input unit (31).

[0102] In the estimation system (1) according to the sixth embodiment, in any one of the first to fifth embodiments, the input unit (31) further accepts text input relating to the lighting fixture (100). The extraction unit (211) estimates and extracts fixture features from the reference image (Im1) and the text received by the input unit (31).

[0103] According to this embodiment, it is possible to improve the estimation accuracy of the extraction unit (211) compared to the case where the instrument features are estimated based only on the reference image (Im1).

[0104] In the estimation system (1) according to the seventh embodiment, in any one of the first to sixth embodiments, the input unit (31) further accepts an input of a facility image (Im3), which is an image of the target facility (FA1). The estimation system (1) further comprises an output unit (32). The output unit (32) outputs a proposed image (Im4) in which lighting fixtures (100) corresponding to the fixture information (In1) identified by the identification unit (212) are superimposed on the facility image (Im3).

[0105] According to this embodiment, it is possible to output a proposed image (Im4) in which a lighting fixture (100) corresponding to the fixture information (In1) identified by the specific unit (212) is superimposed on a facility image (Im3).

[0106] The estimation system (1) according to the eighth embodiment further comprises a generation unit (213) and a storage unit (22) in any one of the first to seventh embodiments. The generation unit (213) generates fixture features from catalog information of the lighting fixture (100). The storage unit (22) stores the fixture features generated by the generation unit (213) and the fixture information (In1) in association. The identification unit (212) identifies the fixture information (In1) based on the fixture features estimated by the extraction unit (211) and the fixture features stored in the storage unit (22).

[0107] According to this embodiment, since the fixture information (In1) is identified based on the catalog information of the lighting fixture (100), it becomes possible to identify the fixture information (In1) with higher accuracy.

[0108] The estimation system (1) according to the ninth embodiment further comprises a furniture extraction unit (214) and a storage unit (22) in any one of the first to eighth embodiments. Unlike the extraction unit (211), the furniture extraction unit (214) estimates and extracts furniture features, which are the feature quantities of furniture placed in the space (SP1) within the reference image (Im1). The storage unit (22) stores furniture information, which is information about furniture, and furniture features, linked together. The identification unit (212) identifies the furniture information based on the furniture features extracted by the furniture extraction unit (214) and the furniture features stored in the storage unit (22).

[0109] According to this embodiment, in addition to equipment information (In1), furniture information can also be identified.

[0110] The estimation system (1) according to the tenth embodiment further comprises an interior extraction unit (215) and a storage unit (22) in any one of the first to ninth embodiments. Unlike the extraction unit (211), the interior extraction unit (215) estimates and extracts interior feature quantities, which are the feature quantities of the interior of the space (SP1) in the reference image (Im1). The storage unit (22) stores interior information, which is information about the interior, and interior feature quantities linked together. The identification unit (212) identifies the interior information based on the interior feature quantities extracted by the interior extraction unit (215) and the interior feature quantities stored in the storage unit (22).

[0111] According to this embodiment, in addition to fixture information (In1), interior information can also be specified.

[0112] The estimation method according to the eleventh embodiment comprises an input step (ST1), an extraction step (ST2), and a identification step (ST3). In the input step (ST1), a reference image (Im1) is received as input. In the extraction step (ST2), fixture features, which are characteristic quantities of lighting fixtures (100) arranged in the space (SP1) within the reference image (Im1), are estimated and extracted from the reference image (Im1) received in the input step (ST1). In the identification step (ST3), fixture information (In1), which is information about the lighting fixture (100), is identified from the fixture features extracted in the extraction step (ST2). The fixture features include at least one of the following: the irradiation range of light from the lighting fixture (100), the color temperature of the light, the number of lighting fixtures (100) arranged in the space (SP1), and the position of the lighting fixture (100) in the space (SP1).

[0113] According to this embodiment, it becomes possible to identify information regarding the lighting fixture (100) in the reference image (Im1).

[0114] The configurations relating to the second to tenth aspects are not essential to the estimation system (1) and can be omitted as appropriate.

[0115] 1 Estimation System 22 Memory Unit 31 Input Unit 32 Output Unit 100 Lighting Fixture 211 Extraction Unit 212 Identification Unit 213 Generation Unit 214 Furniture Extraction Unit 215 Interior Extraction Unit FA1 Target Facility Im1 Reference Image Im3 Facility Image Im4 Proposed Image In1 Fixture Information SP1 Space ST1 Input Step ST2 Extraction Step ST3 Identification Step

Claims

1. An estimation system comprising: an input unit for receiving a reference image; an extraction unit for estimating and extracting fixture feature quantities, which are characteristic quantities of lighting fixtures arranged in the space within the reference image, from the reference image received by the input unit; and an identification unit for identifying fixture information, which is information relating to the lighting fixtures, from the fixture feature quantities extracted by the extraction unit, wherein the fixture feature quantities include at least one of the following: the irradiation range of light from the lighting fixtures, the color temperature of the light, the number of lighting fixtures arranged in the space, and the position of the lighting fixtures in the space.

2. The estimation system according to claim 1, further comprising a storage unit that stores type information, which is information relating to the type of lighting fixture, and fixture feature quantities in association, wherein the identification unit identifies the type information as fixture information based on the fixture feature quantities extracted by the extraction unit and the fixture feature quantities stored in the storage unit.

3. The estimation system according to claim 1, further comprising a storage unit that stores characteristic information, which includes the type of lighting fixture, the output characteristics of the lighting fixture, and the color temperature of the light from the lighting fixture, in association with the fixture characteristic quantity, wherein the identification unit identifies the characteristic information as fixture information based on the fixture characteristic quantity extracted by the extraction unit and the fixture characteristic quantity stored in the storage unit.

4. The estimation system according to any one of claims 1 to 3, wherein the input unit further receives input of floor plan information, which is information relating to the floor plan of the target facility, and the identification unit further identifies a combination of lighting fixtures corresponding to the floor plan information received by the input unit.

5. The estimation system according to any one of claims 1 to 4, wherein the input unit further receives budget information which is information relating to the cost of installing the lighting fixtures at the target facility, and further comprises a storage unit which stores a plurality of fixture information and a plurality of budget information linked together, and the identification unit identifies the fixture information corresponding to the budget information received by the input unit from among the plurality of fixture information stored in the storage unit.

6. The estimation system according to any one of claims 1 to 5, wherein the input unit further accepts text input relating to the lighting fixture, and the extraction unit estimates and extracts the fixture features from the reference image and text received by the input unit.

7. The estimation system according to any one of claims 1 to 6, wherein the input unit further receives an input of a facility image which is an image of a target facility, and outputs a proposed image in which the lighting fixtures corresponding to the fixture information identified by the identification unit are superimposed on the facility image.

8. The estimation system according to any one of claims 1 to 7, further comprising: a generation unit that generates fixture feature quantities from catalog information of the lighting fixture; and a storage unit that associates and stores the fixture feature quantities generated by the generation unit with the fixture information, wherein the identification unit identifies the fixture information based on the fixture feature quantities extracted by the extraction unit and the fixture feature quantities stored in the storage unit.

9. An estimation system according to any one of claims 1 to 8, further comprising: a furniture extraction unit which estimates and extracts furniture feature quantities which are characteristic quantities of furniture arranged in the space within the reference image, and a storage unit which stores furniture information which is information about the furniture and the furniture feature quantities linked together, wherein the identification unit identifies the furniture information based on the furniture feature quantities extracted by the furniture extraction unit and the furniture feature quantities stored in the storage unit.

10. An estimation system according to any one of claims 1 to 9, further comprising: an interior extraction unit which estimates and extracts interior feature quantities which are characteristic quantities of the interior of the space in the reference image, unlike the extraction unit; and a storage unit which stores interior information which is information relating to the interior and the interior feature quantities linked together, wherein the identification unit identifies the interior information based on the interior feature quantities extracted by the interior extraction unit and the interior feature quantities stored in the storage unit.

11. An estimation method comprising: an input step of receiving a reference image; an extraction step of estimating and extracting fixture features, which are characteristic quantities of lighting fixtures arranged in the space within the reference image, from the reference image received in the input step; and an identification step of identifying fixture information, which is information relating to the lighting fixtures, from the fixture features extracted in the extraction step, wherein the fixture features include at least one of the following: the irradiation range of light from the lighting fixtures, the color temperature of the light, the number of lighting fixtures arranged in the space, and the position of the lighting fixtures in the space.

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