Projection device, projection method, and program

Abstract

To provide a projection device, a projection method, and a program to change the appearance of a dish.SOLUTION: A projection device 1 includes a subject dish identification unit 22 that identifies a subject's dish, a sample dish identification unit 23 that identifies a sample dish corresponding to the subject's dish, a projection image generation unit 24 that generates a projection image on the basis of an image of the sample dish, and a projection control unit 25 that projects the projection image generated by the projection image generation unit 24 by superimposing it on the surface of the subject's dish.SELECTED DRAWING: Figure 3

Description

[Technical field]

[0001] The present invention relates to a projection device, a projection method, and a program. [Background technology]

[0002] There is known a projection mapping technique that uses a projector to project an image by aligning it with a real object. Patent Document 1 discloses a technique that projects an image of a selected dish onto an empty plate. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2018-185414 A Summary of the Invention [Problem to be solved by the invention]

[0004] For example, elderly people with weak teeth or chewing power, or people suffering from illnesses, and other people with dietary restrictions may have to eat bland dishes or liquid foods. Bland dishes and liquid foods are less tasty because they have little color, which can reduce satisfaction with the food and make it difficult to enjoy the meal.

[0005] Also, when a person with dietary restrictions eats a meal with able-bodied people, they may have to eat different food than the able-bodied people. In such cases, the person with dietary restrictions may not be able to enjoy the meal as much because the food is not the same as the able-bodied people.

[0006] In Patent Document 1, a projector projects an image of food onto an empty plate, and does not project an image of the food that will actually be eaten.

[0007] The present invention has been made in consideration of such problems, and an object of the present invention is to provide a projection device, a projection method, and a program that change the appearance of a dish. [Means for solving the problem]

[0008] A projection device according to one aspect of the present invention is characterized in that it comprises a subject dish identification unit that identifies a subject's dish, a sample dish identification unit that identifies a sample dish corresponding to the subject's dish, a projection image generation unit that generates a projection image based on an image of the sample dish, and a projection control unit that projects the projection image generated by the projection image generation unit by superimposing it on the surface of the subject's dish.

[0009] A projection method according to one aspect of the present invention is a projection method for projecting a projection image onto the position of a subject's food, and is characterized by including a subject dish identification step for identifying the subject's food, a sample dish identification step for identifying a sample dish corresponding to the subject's food, a projection image generation step for generating a projection image based on an image of the sample dish, and a projection control step for superimposing and projecting the projection image generated by the projection image generation step onto the surface of the subject's food.

[0010] A program according to one aspect of the present invention is characterized in that, in a program executable by a computer capable of exchanging information with an input / output device, it includes a subject dish identification step of identifying a dish for the subject, a sample dish identification step of identifying a sample dish corresponding to the subject's dish, a projection image generation step of generating a projection image based on an image of the sample dish, and a projection control step of projecting the projection image generated by the projection image generation step and superimposing it onto the surface of the subject's dish. Effect of the Invention

[0011] According to the present invention, the appearance of the food eaten by a subject can be changed. [Brief description of the drawings]

[0012] [Figure 1]FIG. 1 is a diagram showing an external configuration of a projection device before an image is projected, and an example of its use. [Diagram 2] FIG. 2 is a diagram showing the external configuration of the projection device after image projection and an example of its use. [Diagram 3] FIG. 3 is a block diagram showing the internal configuration of the projection device. [Figure 4] FIG. 4 is a flowchart illustrating the operation of the projection device. [Diagram 5] FIG. 5 is a diagram showing ramen as an example of a subject's dish. [Figure 6] FIG. 6 is a block diagram showing the internal configuration of a projection device in another example of the projection process. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0013] [One embodiment] FIG. 1 is a diagram showing the external configuration of a projection device 1 before an image is projected, and an example of its use.

[0014] In this example, Diner A is a healthy person and Diner B is an ill person. Diners A and B are about to have a meal together, and the dish X offered to Diner A is ramen. The dish Y offered to Diner B is porridge, a liquid food.

[0015] 1, the projection device 1 is installed on the ceiling. The projection device 1 has an imaging unit 11 and a projection unit 12. The imaging unit 11 images an area including a diner A and ramen, which is dish X served to the diner A, and a diner B and porridge, which is dish Y served to the diner B.

[0016] The projection device 1 projects the image captured by the image capture unit 11 via the projection unit 12 by a projection process described later. For example, as shown in Fig. 2, the projection device 1 projects an image of ramen noodles (hereinafter, appropriately referred to as ramen noodles X) provided to diner A onto porridge (hereinafter, appropriately referred to as porridge Y) which is dish Y provided to diner B so that diner B can recognize that he or she is eating the same ramen as diner A. For example, the projection of the image of ramen noodles X provided to diner A onto porridge Y provided to diner B is achieved by positioning and color matching using a well-known projection mapping technique.

[0017] Here, alignment means correcting the image to be projected and aligning it with the shape of the real object onto which the image is projected. Also, color matching means correcting the image to be projected and matching the colors so that the image overlaps with the colors of the real object onto which the image is projected to make the desired colors appear. Note that the image to be projected and projected via the projection unit 12 after being corrected is called the projected image.

[0018] For example, a sensor (not shown) possessed by the projection device 1 measures the distance to the surface of the porridge Y and the shape and color of the object, and a projection image of ramen X corrected based on the distance and the shape and color of the object is projected onto the surface of the porridge Y.

[0019] A dish onto which a projection image is projected by a projection process described later, such as porridge Y, is referred to as a target person's dish, as appropriate. A person onto whose dish a projection image is projected, such as diner B, is referred to as a target person, as appropriate. A dish that is a sample of a projection image projected onto the target person's dish by a projection process described later, such as ramen X, is referred to as a sample dish, as appropriate. A person who accompanies the target person to a meal, such as diner A, is referred to as a companion, as appropriate.

[0020] 1 is merely an example, and various structures are possible for the projection device 1. For example, the image capturing unit 11 may be disposed separately from the projection device 1, and information from the projection device 1 may be acquired through wireless communication such as Bluetooth (registered trademark) or Wi-Fi (registered trademark) or through wired communication.

[0021] (Internal configuration of projection device 1) 3 is a block diagram showing the internal configuration of the projection device 1. The projection device 1 includes an image capturing unit 11, a projection unit 12, an operation unit 13, a control unit 14, and a storage unit 15.

[0022] The photographing unit 11 is, for example, a video camera that photographs the food placed on the dining table and the diners, generates image information including the food and the diners, and supplies the image information to the control unit 14.

[0023] The projection unit 12 is, for example, a projector, and is configured to include three liquid crystal light valves, a projection lens, a light valve driving unit, etc. The projection unit 12 receives an image signal from the control unit 14, and projects and displays a projection image at the position of the diner's food in response to this image signal. That is, the projection unit 12 displays the projection image by superimposing it on the surface of the target person's food.

[0024] The operation unit 13 is, for example, a button, a touch panel, or the like, and receives information input by operation of a user (including a person eating with a meal and other people), and supplies the information to the control unit 14.

[0025] The control unit 14 is composed of a CPU (Central Processing Unit), a storage section (such as a ROM (Read Only Memory), a RAM (Random Access Memory), or a non-volatile memory), and other elements including hardware. The control unit 14 controls the entire projection device 1 by executing a control application program (not shown) stored in the memory unit 15, and also functions as an image recognition unit 21, a target dish identification unit 22, a sample dish identification unit 23, a projection image generation unit 24 and a projection control unit 25, and executes the projection process.

[0026] The image recognition unit 21 recognizes the diners, the dishes, and the ingredients contained in the dishes based on the images captured by the imaging unit 11.

[0027] The target person's dish identification unit 22 identifies the target person's dish from among the dishes recognized by the image recognition unit 21. In this example, the sample dish identification unit 23 identifies the dish of the companion who will eat with the target person from among the dishes recognized by the image recognition unit 21 as the sample dish corresponding to the target person's dish.

[0028] The projection image generator 24 generates a projection image based on the sample dish image.

[0029] The projection control unit 25 projects the projection image generated by the projection image generation unit 24 via the projection unit 12 so as to be superimposed on the surface of the target person's food identified by the target person's food identification unit 22.

[0030] The storage unit 15 includes, for example, a Read Only Memory (ROM), a Random Access Memory (RAM), and a non-volatile memory. The storage unit 15 stores the above-mentioned control application program, various data required for executing the program, and information generated by processing.

[0031] (Projection process of projection device 1) Next, the projection process of the projection device 1 in the example of FIGS. 1 and 2 will be described with reference to the flowchart of FIG.

[0032] As shown in Fig. 1, two dishes X and Y are set on a dining table, and two diners A and B are about to take the dishes (start eating). In step S1, the imaging unit 11 of the projection device 1 starts imaging the dishes X and Y set on the dining table and the diners A and B.

[0033] In step S2, the subject dish identifying unit 22 identifies the subject dish. In the example of FIG. 1, diner B is the subject, and porridge Y, which is a dish provided to diner B as the subject, is the subject dish. Specifically, the user (diners A, B, and other users) registers in advance in the storage unit 15, via the operation unit 13, that diner B is the subject, and that diner B will be sitting in the position on the right side in the figure. From the image captured by the imaging unit 11, the subject dish identifying unit 22 identifies porridge Y, which is a dish placed within a predetermined distance from the chair on the right side in the figure where diner B, the subject, is sitting, as the subject dish. The subject dish identifying unit 22 may identify the dish placed closest among the dishes placed within a predetermined distance from the subject as the subject dish.

[0034] Next, in step S3, the sample dish identifying unit 23 identifies the sample dish. In the example of FIG. 1, the dish of the companion accompanying the target person, diner B, is identified as the sample dish. Specifically, the user registers in advance in the storage unit 15, via the operation unit 13, that ramen X, which is the dish to be provided to diner A, is the sample dish and that the companion diner A will be sitting in the position on the left side of the figure. From the image captured by the imaging unit 11, the sample dish identifying unit 23 identifies ramen X, which is the dish placed within a predetermined distance from the chair on the left side of the figure where diner A is sitting, as the sample dish. The sample dish identifying unit 23 may identify the dish placed closest to the companion among the dishes placed within a predetermined distance.

[0035] In step S4, the projection image generating unit 24 generates a projection image based on the image of the sample dish. Then, in step S5, the projection control unit 25 projects the projection image generated by the projection image generating unit 24 via the projection unit 12 so as to be superimposed on the surface of the target person's dish identified by the target person's dish identifying unit 22.

[0036] Specifically, for example, when the image recognition unit 21 recognizes that the subject's dish and the sample dish are in different categories and the color of the subject's dish is less than a predetermined standard, the projection image generation unit 24 generates an image of the sample dish as a projection image. Then, the projection control unit 25 projects the image of the sample dish generated by the projection image generation unit 24 via the projection unit 12, superimposed on the surface of the subject's dish. Here, the color of the dish is the number of types of colors that the dish has, and is obtained from the pixel value of the dish image. The image recognition unit 21 may calculate a variance value for the pixel values ​​of the color components contained in the image of the subject's dish, and recognize that the color is less than a predetermined standard when the calculated variance value is smaller than a predetermined value. In addition, the category of the dish is a classification of the dish, for example, the name of the dish such as ramen. The image recognition unit 21 may input the image of the subject's dish to an inference model that can infer the category of the dish stored in the storage unit 15, and recognize the inference result as the category of the dish.

[0037] The image recognition unit 21 may use a method such as well-known template matching or edge extraction to recognize the food category and color. Also, the user can set the food category via the operation unit 13.

[0038] In the example of FIG. 1, the image recognition unit 21 recognizes that the porridge Y, which is the target person's dish, and the ramen X, which is the sample dish, are in different dish categories. The image recognition unit 21 also recognizes that the color of the porridge Y, which is the target person's dish, is less than a predetermined standard. The projection image generation unit 24 generates an image of the ramen X, which is the sample dish, as a projection image. Then, the projection control unit 25 projects the projection image, which is the image of the ramen X, superimposed on the surface of the porridge Y, which is the target person's dish, via the projection unit 12, as shown in FIG. 2. As a result, the diner B can recognize that the same ramen as the diner A has been served, even though the porridge Y has been served.

[0039] Thereafter, for example, when the image recognition unit 21 recognizes that the target person's food has run out or when the user instructs the end of the processing via the operation unit 13, the processing of the projection device 1 ends.

[0040] (Another example of projection processing)

[0041] <Match some colors> The projection onto the subject's dish is not limited to the examples described in steps S4 and S5 of Fig. 4. For example, if there is a predetermined difference between the image of the sample dish recognized by the image recognition unit 21 and the image of the subject's dish, the projection image generation unit 24 generates a projection image that matches the portion of the subject's dish with the predetermined difference to the portion of the sample dish with the predetermined difference. The projection control unit 25 can then project the projection image by superimposing it on the surface of the subject's dish.

[0042] Here, the projected image may be just an image of the part of the subject's dish that has a predetermined difference, or may be an image of the entire dish including the part of the subject's dish that has a predetermined difference.

[0043] As a specific example, the image recognition unit 21 recognizes that the subject's dish and the sample dish are both ramen, which is the same dish category, and that the difference in pixel value between the soup portion of the image of the ramen of the subject's dish shown in Figure 5 and the soup portion of the image of the ramen of the sample dish is greater than a predetermined value.

[0044] The image recognition unit 21 may input an image of the subject dish and an image of a sample dish into an inference model capable of inferring the ingredients of a dish stored in the memory unit 15, and recognize the type of ingredients and their position on the image from the inference results.

[0045] The image recognition unit 21 judges whether the ingredients in the image of the subject's dish and the image of the sample dish match. If the ingredients match, the image recognition unit 21 judges whether the difference in color components of pixel values ​​at the position of the ingredients in the image of the subject's dish and the image of the sample dish is greater than a predetermined value. If the difference in pixel values ​​is greater than the predetermined value, the image recognition unit 21 recognizes that there is a predetermined difference between the image of the sample dish and the image of the subject's dish.

[0046] The storage unit 15 stores in advance the predetermined values ​​used by the image recognition unit 21 . The predetermined value may be determined as follows. First, the projection image generating unit 24 generates two images with the same pixel values, and projects them using the projection control unit 25 to present them to the subject, changing the color of one of them slightly. The projection image generating unit 24 may use the positions of the ingredients in the cooking image recognized by the image recognizing unit 21 to change the pixel values ​​included in the range of some of the ingredients. The subject operates the operation unit 13 when he or she senses a difference between the two projected images. The image recognition unit 21 stores in the storage unit 15 the difference in pixel values ​​between the two images being projected at the time when the difference is input via the operation unit 13 as a predetermined value. The image recognition unit 21 may read out the predetermined value stored in the storage unit 15 and use it when determining whether or not the difference in color components of pixel values ​​is greater than the predetermined value.

[0047] The projection image generating unit 24 may use an image of ramen as the two images to be projected. That is, the projection image generating unit 24 may recognize the soup portion in the image of ramen and change the pixel value of the soup portion.

[0048] When the image recognition unit 21 recognizes that there is a predetermined difference between the image of the sample dish and the image of the subject's dish, the projection image generation unit 24 generates a projection image based on the image of the sample dish and the image of the subject's dish. For example, the projection image generation unit 24 generates a projection image in which the color of the soup in the ramen of the subject's dish is the same as the pixel values ​​of the image of the soup in the sample dish by making the pixel values ​​of the image of the soup in the sample dish the same. Then, the projection control unit 25 projects the projection image so that it is superimposed on the surface of the ramen of the subject's dish.

[0049] Here, the projection image may be only an image of the soup part of the ramen of the subject's dish, or may be an image of the entire ramen including the soup part of the ramen of the subject's dish. In other words, the projection image generating unit 24 may generate a projection image including at least a part of the ingredients of the subject's dish. In addition, the projection image generating unit 24 may generate a projection image by changing the pixel values ​​of the image of the ingredient part of the subject's dish to within a predetermined range based on the pixel values ​​of the image of the ingredient part of the sample dish.

[0050] In the above, the difference in color between the sample dish and the subject dish has been explained as an example, but it is not limited to the difference in color. For example, the projection image can be projected based on the difference in size of ingredients such as the roast pork in Figure 5.

[0051] <Specify color> For example, in addition to comparing with the sample dish, the projection image generating unit 24 recognizes the voice of the subject using a well-known voice recognition technology, extracts keywords that indicate the subject's evaluation of the dish, and generates a projection image according to the keywords. The projection image generating unit 24 may extract information on the ingredients of the dish in addition to an evaluation of the taste of the dish as the evaluation. The projection control unit 25 can display the generated projection image by superimposing it on the surface of the subject's dish. In this case, as shown in FIG. 6, the projection device 1 is further provided with a voice input unit 16, such as a microphone, for inputting the voice of the target person.

[0052] As a specific example, the subject's dish is ramen, and the subject's voice is input from the voice input unit 16. When the keywords "soup" which is information about ingredients and "too thin" which is an evaluation of the taste are extracted from the subject's voice saying "the soup is too thin", the projection image generation unit 24 changes the pixel values ​​of the soup part of the image of the ramen of the subject's dish to a specified value, thereby generating an image in which the color of the soup part of the ramen of the subject's dish is darkened. The projection control unit 25 projects the generated image by superimposing it on the surface of the subject's dish.

[0053] For example, if the subject's dish is ramen, images of ramen with different soup colors can be stored as sample dish images in the storage unit 15. When the projection image generating unit 24 extracts the keyword "too light," the projection control unit 25 can quickly project a projection image of a soup that is one level darker in color. In this case, a taste intensity level is associated with each of the images of the sample dishes stored in the storage unit 15. The taste intensity level is an index indicating general taste intensity, such as "light," "normal," and "strong." In this way, when the projection image generating unit 24 extracts the keyword "too light," the projection control unit 25 can project a projection image based on the image of the sample dish associated with the "strong" intensity level. Therefore, even if it is difficult to distinguish the intensity of the taste from the sample image, it is possible to project a projection image of a dish with an appropriate taste based on the subject's taste evaluation. [Other Examples] (Other examples of how to identify the target dish) In the projection process described with reference to Figure 4, the user registers in advance the position where the target person will be sitting, and the target person food identification unit 22 identifies the food placed close to the position of the registered target person as the target person food, but the method of identifying the target person food is not limited to this method.

[0054] For example, the subject's food identification unit 22 can estimate the age of a diner from the face image of the diner captured by the image capture unit 11 using a known face recognition technique, identify a diner older than a predetermined age as the subject, and identify the food placed near the subject as the subject's food. The subject's food identification unit 22 can also identify a diner with a pale complexion as a diner who is not in good health, for example, from the face image of the diner captured by the image capture unit 11, and identify the food near the subject as the subject's food. The subject's food identification unit 22 can also identify a diner who consumes food slower than a predetermined standard as the subject from the video of the diner's face captured by the image capture unit 11. As a specific example, the image recognition unit 21 measures the number of times the diner chews per certain time, that is, the chewing speed, from the face image of the diner captured by the image capture unit 11. The subject's food identification unit 22 can identify a diner whose chewing speed is slower than a predetermined standard as the subject.

[0055] The user can appropriately set how close a dish is placed to the target person to be considered as the target person's dish. In addition, when multiple dishes are provided to the target person, the target person's dish identification unit 22 can identify one dish as the target person's dish, or multiple dishes as the target person's dishes.

[0056] (Another example of how to identify a sample dish) In the projection process described with reference to Figure 4, the user registers in advance the positions where diners other than the target person will sit, and the sample dish identification unit 23 identifies the dish placed close to the registered position as the sample dish, but the method of identifying the sample dish is not limited to this method.

[0057] For example, the user can photograph a dish that he or she wishes to use as a sample dish in advance using the photographing unit 11 and register the photographed image as an image of the sample dish in the storage unit 15, and the sample dish identification unit 23 can use that image as an image of the sample dish. Also, the user can register an image of a dish downloaded from the Internet in advance in the storage unit 15 as an image of the sample dish, and the sample dish identification unit 23 can use that image as an image of the sample dish.

[0058] The image recognition unit 21 may recognize a person who is closest to the target person within a first distance as a companion. Also, a companion and a projection device 1a (not shown) may be present at a position different from the projection device 1 that projects onto the target person. The projection device 1 and the projection device 1a may have the same configuration, and may communicate with each other via a communication unit (not shown). Also, the image recognition unit 21 may recognize a person who is closest to the projection device 1a within a second distance, or a person at a predetermined position as a companion.

[0059] The sample dish identifying unit 23 may identify the dish that is closest to the accompanying person within a third distance as the sample dish. The sample dish identification unit 23 may identify a dish in the same category as the identified target dish as the sample dish. The sample dish identification unit 23 may identify, as the sample dish, a dish that is closest to the accompanying person within a third distance and that is in the same category as the identified target person dish.

[0060] The projection image generating unit 24 may use an image of a dish downloaded from the Internet as the sample dish image.

[0061] Also, the number of people dining is not limited to two, but may be one, three or more.

[0062] (Arbitrary settings for projection processing) The user can also appropriately decide whether to execute the projection process described above. For example, in the example of Fig. 1, if the subject, diner B, does not have much appetite, the user can select via the operation unit 13 not to execute the projection process, so that the subject can eat dish Y as porridge. In addition, if there are multiple subject dishes, the user can select via the operation unit 13 to execute the projection process for one subject dish and not to execute the projection process for another subject dish.

[0063] (Projection area) In the projection process described with reference to Fig. 4, the projection device 1 projects the projection image onto the subject's dish placed on the table, but it can also project onto the part of the subject's dish that the subject has taken with a spoon, fork, or chopsticks. For example, when the subject takes ramen soup with a spoon, a sensor (not shown) of the projection device 1 detects the movement of the soup and projects a projection image of the soup onto the part of the spoon where the soup has accumulated, following the movement of the spoon, so that the color of the soup in the spoon is recognized as the same as the color of the soup in the sample dish.

[0064] (Use of AR glasses, head-mounted displays, etc.) Although an example has been described using the projection device 1, it is also possible to use AR (Augmented Reality) glasses, a head-mounted display, etc. to display a projected image superimposed on the target person's food.

[0065] (Projection according to eating state) The projection image can be changed as the meal progresses. For example, the projection image can be generated based on a comparison between the sample dish and the subject's dish at first, and then modified based on the subject's voice. That is, the projection image generating unit 24 may generate the projection image based on the sample dish and the subject's dish, may generate the projection image based on the subject's voice, or may switch the method of generating the projection image at a predetermined timing. The projection image generating unit 24 may also update the projection image based on a change in the appearance of the dish.

[0066] (Certification of target dishes, etc.) Various recognitions of the subject, the subject's dish, the sample dish, the dish category, and the different parts of the subject's dish and the sample dish can be realized using existing image processing and machine learning processing.

[0067] (Meaning of projected image) In the above, we have explained an example of a projected image that makes the subject eat more. However, in order to more reliably restrict food intake, the projected image can also be an image that is perceived as not appetizing.

[0068] [Supplementary explanation of the embodiment]

[0069] The above-mentioned embodiments each show a preferred specific example of the present invention. The numerical values, components, the arrangement positions and connection forms of the components, the processing order in the flow charts, and the like shown in the following embodiments are merely examples and are not intended to limit the present invention. Also, each figure is not necessarily a strict illustration.

[0070] The above-mentioned series of processes can be executed by hardware or software. When the series of processes are executed by software, the programs constituting the software are installed from a program recording medium into a computer incorporated in dedicated hardware, or into, for example, a general-purpose personal computer capable of executing various functions by installing various programs.

[0071] In addition, the program executed by the computer may be a program in which processing is performed chronologically in the order described in this specification, or it may be a program in which processing is performed in parallel or at the required timing, such as when called. [Summary of the invention]

[0072] (1) The above-described projection device 1 is A target person's food identification unit 22 that identifies the target person's food; A sample dish identification unit 23 that identifies a sample dish corresponding to the subject's dish; a projection image generating unit (24) for generating a projection image based on the image of the sample dish; a projection control unit 25 that superimposes and projects the projection image generated by the projection image generation unit 24 onto the surface of the subject's food; Equipped with.

[0073] With this configuration, the projection device 1 can change the appearance of the food that the subject eats by projecting a projection image.

[0074] (2) The system further includes an image recognition unit 21 that recognizes images of the subject's dish and images of sample dishes, When there is a predetermined difference between the image of the sample dish recognized by the image recognition unit 21 and the image of the subject's dish, the projection image generation unit 24 generates a projection image that matches at least the part of the subject's dish with the predetermined difference to the part of the sample dish with the predetermined difference.

[0075] With this configuration, the projection device 1 can make the appearance of a portion of the target person's dish closer to the appearance of the sample dish by projecting a projection image.

[0076] (3) Further, a voice input unit 16 for inputting the voice of the subject is provided, The projection image generating unit 24 extracts keywords indicating the subject's evaluation of the dish from the subject's voice input from the voice input unit 16, and generates a projection image according to the evaluation.

[0077] With this configuration, the projection device 1 generates a projection image in response to the subject's vocal evaluation, and by projecting the projection image, the appearance of the food the subject is eating can be changed to suit the subject's preferences.

[0078] This disclosure includes matters that contribute to the realization of the SDGs "Good health and well-being for all" and contribute to value creation through healthcare products and services. [Explanation of symbols]

[0079] 1 Projection device 11. Photography Department 12 Projection section 13 Control section 14 Control section 15 Storage section 16 Audio input section 21 Image Recognition Unit 22 Target Food Specification Section 23 Sample Cooking Section 24 Projection image generation unit 25 Projection control unit

Claims

1. A target person's cuisine identification unit that identifies the target person's cuisine; A sample dish identification unit that identifies a sample dish corresponding to the target person's dish; a projection image generating unit that generates a projection image based on the image of the sample dish; a projection control unit that projects the projection image generated by the projection image generation unit so as to be superimposed on the food of the subject; A projection device comprising:

2. An image recognition unit that recognizes an image of the subject's dish and an image of the sample dish, When a predetermined difference exists between the image of the sample dish recognized by the image recognition unit and the image of the subject's dish, the projection image generation unit generates a projection image in which at least a portion of the subject's dish having the predetermined difference is matched to a portion of the sample dish having the predetermined difference.

2. The projection device according to claim 1 .

3. A voice input unit for inputting the voice of the subject is further provided, The projection image generation unit extracts the subject's evaluation of the dish from the voice of the subject inputted from the voice input unit, and generates a projection image according to the evaluation.

3. A projection device according to claim 1 or 2.

4. A subject cuisine identification step of identifying the subject's cuisine; A sample dish identification step of identifying a sample dish corresponding to the subject's dish; a projection image generating step of generating a projection image based on the image of the sample dish; a projection control step of superimposing the projection image generated by the projection image generation step on the food of the subject; 23. A projection method comprising:

5. In a program executable by a computer capable of transmitting and receiving information to and from an input / output device, A subject cuisine identification step of identifying the subject's cuisine; A sample dish identification step of identifying a sample dish corresponding to the subject's dish; a projection image generating step of generating a projection image based on the image of the sample dish; a projection control step of superimposing the projection image generated by the projection image generation step on the food of the subject; Characterized in that it comprises A program that causes a computer to carry out processing.

Images