JP2022049452A - Donation device, donation method, and computer program - Google Patents

Abstract

To make a donation upon detecting a smile in video.SOLUTION: A donation device 100 comprises: an imaging unit 101 that images video; a detection unit 102 that detects the face of a person included in the video; a smile detection unit 103 that detects a smile that appears on the face of the person detected; a donation unit 104 that makes a donation every time a smile is detected; a percentage calculation unit 105 that calculates a percentage of smiles detected; a determination unit 106 that determines the degree of smile; an identification unit 107 that identifies the face of a person included in the video; a limitation unit 108 that limits the execution of donations to a predetermined number of times; a smile information registration unit 109 that registers information related to smiles; and a location identification unit 100 that identifies where a smiling person is.SELECTED DRAWING: Figure 1

Description

The present invention relates to a technique for making a donation when a smile is detected.

Various techniques related to donation services have been proposed. For example, Patent Document 1 discloses that a donation service is provided according to a determination of a transfer state in a road condition.

Patent Document 1 describes a technique for providing a donation service when a transfer state in a road condition is determined. Patent Document 2 describes a technique of detecting a human face based on image data and determining the facial expression of the detected face.

JP-A-2004-13656 JP 2017-119550

As described above, the donation service method according to the prior art is not intended to provide a donation service when a person's smile is detected.

Therefore, one of the purposes of the present invention is to make a donation when it is determined that the face of a person included in the image captured by a predetermined imaging means is a smile.

In order to achieve the above object, the donation device according to one aspect of the present invention detects a person's face included in an image captured by a predetermined imaging means and a smile appearing on the person's face. It has a smile detecting means for making a smile and a donation means for making a donation of a predetermined amount of valuable value each time a smile is detected.

Further, the donation means may make a donation up to a predetermined donation resource.

Further, the predetermined imaging means is installed in a predetermined store or the like, and further has a ratio calculation means for calculating the ratio of smiles detected during a predetermined event held in the predetermined store or the like. However, the donation means may use the sales during the predetermined event as the source of the donation.

Further, the donation means further includes a determination means for determining the degree of the detected smile, and the donation means is the quantity obtained by multiplying the predetermined quantity by a coefficient according to the degree of the smile each time the smile is detected. You may make a donation of valuable value.

Further, it may further have an identification means for individually identifying a person's face included in the video, and a limiting means for limiting the execution of donations by the smile of the same person to a predetermined number of times.

Further, it may further have a smile information registration means for registering information related to the number of times a smile is detected, the detection time, and the detection location.

Further, the donation method according to another aspect of the present invention includes a discrimination step of discriminating a person's face included in an image captured by a predetermined imaging means, and a smile detection step of detecting a smile appearing on the person's face. Each time a smile is detected, a donation step of executing a donation of a predetermined quantity of valuable value may be performed.

Further, the computer program according to another aspect of the present invention includes a discrimination process for discriminating a person's face included in an image captured by a predetermined imaging means, and a smile detection process for detecting a smile appearing on the person's face. , A donation process that executes a predetermined amount of valuable value donation each time a smile is detected may be executed.

The computer program can be provided by downloading via a network such as the Internet, or can be recorded and provided on various computer-readable recording media.

According to the present invention, a donation can be made when a person's smile is detected.

It is a functional block diagram which shows the embodiment of the donation device which concerns on embodiment of this invention. It is a figure which shows the example which the detection part of the donation apparatus which concerns on embodiment of this invention detects a human face. It is a figure for demonstrating the information recorded by the smile information registration part of the donation apparatus which concerns on embodiment of this invention. It is a state transition diagram which shows the embodiment of the donation apparatus which concerns on the state transition example 1 of this invention.

An embodiment of the present invention will be described with reference to FIGS. 1 and 2.
The donation device 100 shown in FIG. 1 is a device that makes a donation when a smile of a person is detected.
The donation device 100 is composed of a storage medium such as a memory, a processor, a communication module, an input / output interface, and the like, and the processor executes a computer program recorded on the storage medium to form a functional block shown in FIG. It has come to be realized. The storage medium is a computer-readable recording medium, such as a storage device such as a RAM (random access memory), a ROM (read only memory), a disk drive, an SSD (solid state drive), and a flash memory. May include. Here, a non-temporary storage device such as a ROM, a disk drive, an SSD, or a flash memory may be included in the donation device 100 as a storage device separate from the memory.

In the present embodiment, as a premise, a plurality of client terminals provided with the donation device 100 may exist, or they may exist in a distant place or a close place, and the client terminals may communicate with each other. Further, there is a server terminal provided with the donation device 100, and the donation device 100 may be used by a plurality of or one user accessing the server terminal.

● Functional configuration

The donation device 100 has an imaging unit 101, a detection unit 102, a smile detection unit 103, a donation unit 104, a ratio calculation unit 105, a determination unit 106, an identification unit 107, a restriction unit 108, and a smile information registration unit, depending on the hardware configuration described above. 109, a location specifying unit 110 is provided.

The imaging unit 101 images a restaurant, a place where a sport is watched, or the like in order to discriminate the faces of a plurality of people at a restaurant or a place where the game is watched. The method of imaging is, for example, imaging with a visible light camera. As the camera used in the image pickup method, various cameras such as a camera that outputs in gray scale and a thermography camera can be adopted as long as it can identify a human face.
When the image pickup unit 101 captures an image of a restaurant or the like, it suffices if the customer's face can be imaged, and the inside or outside of the restaurant or the like may be photographed. Further, a plurality of visible light cameras or the like, which are image pickup units 101, may be installed inside or outside the restaurant or the like.
The image pickup by the image pickup unit 101 may be activated only during the business hours of the restaurant or the like, or may be activated outside the business hours of the restaurant or the like.

The detection unit 102 detects a human face included in the image captured by the image pickup unit 101. As shown in FIG. 2, the detection unit 102 can detect a human face. In that case, as shown in FIG. 2, a square frame may be displayed around the detected face.
As a method for detecting a human face by the detection unit 102, various methods such as a Haar-like feature classifier or a method for detecting a human face based on big data having human face data may be used.

The detection unit 102 may detect not only the front of the human face but also the profile of the person, the face seen from above, and the face seen from below as the human face. Further, the detection unit 102 may detect a plurality of human faces included in the image captured by the image pickup unit 101.

The smile detection unit 103 detects a smile appearing on a person's face detected by the detection unit 102. For example, as shown in FIG. 2, the face of the person on the left side of FIG. 2 is detected by the detection unit 102, but is not detected by the smile detection unit 103 because it is not a smile. On the other hand, the face of the person on the right side of FIG. 2 is detected by the detection unit 102, and because it is a smile, it is detected by the smile detection unit 103. Further, as a technique for realizing the smile detection unit 103, it is conceivable to use various techniques such as a face recognition technique by AI, but it is sufficient if the smile can be detected.

When the detection unit 102 detects a plurality of human faces, the smile detection unit 103 detects whether or not the faces of the plurality of people are smiling.

The smile detection unit 103 records the time when the face of the person detected by the detection unit 102 is a smile. For example, when the smile of Mr. A in the store is detected, the smile detection unit 103 records that the detected time is 12:03. Various methods can be considered for recording, such as using the system date of a computer provided with the smile detection unit 103, but the method is not limited as long as the time when the smile is detected can be recorded.

The smile detection unit 103 may detect not only a smile but also other facial expressions such as anger, sadness, and surprise. In that case, the imaging unit 101, the detection unit 102, the donation unit 104, the ratio calculation unit 105, the determination unit 106, the identification unit 107, the restriction unit 108, the smile information registration unit 109, and the location identification unit 110 are various instead of smiling faces. May be applied to the facial expression of. For example, when a smile is detected in a state where many facial expressions such as sadness and anger are detected in a predetermined store, the donation amount may be increased more than usual. That is, in this embodiment, the donation amount per smile is 1 yen, but in a situation where many facial expressions such as sadness and anger are detected, the donation amount per smile may be 5 yen or the like.
Further, the donation device 100 may have the results of the detected facial expressions in a predetermined database or the like in addition to the detection of various facial expressions described above. For example, the smile information registration unit 109 may register not only a smile but also a detection result of a facial expression other than a smile such as anger, sadness, and surprise.

The donation unit 104 makes a donation of a predetermined amount of valuable value each time the smile detection unit 103 detects a smile. As shown in FIG. 2, the donation unit 104 can make a donation of, for example, 1 yen when the smile detection unit 103 detects that the face of the right person is a smile. From now on, it is assumed that the amount of donation per smile is 1 yen. On the other hand, as shown in FIG. 2, since the face of the person on the left is not a smile, the donation by the donation department 104 is not executed. That is, in the case of FIG. 2, since one smile is detected, the donation unit 104 makes a donation of 1 yen.

The donation unit 104 can make a donation up to a predetermined donation resource. For example, if the donation source is set to 1000 yen and a smile is detected 1000 times, the donation amount reaches 1000 yen, which is the upper limit of donation.

The donation unit 104 can use the sales of a predetermined event as a donation resource. For example, if the daily sales of a predetermined event are 10,000 yen, it can be used as a donation resource. That is, until the smile is detected 10,000 times, the donation of 1 yen is executed every time the smile is detected, and from the 11th time onward, the donation is not executed even if the smile is detected.
The donation unit 104 is not limited to the above example, and may be able to set a change in the donation rate for one smile from the 11th time.

Each time the donation unit 104 detects a smile, the donation unit 104 makes a donation of the value of the quantity obtained by multiplying the predetermined quantity, which is the donation amount per smile, by a coefficient according to the degree of the smile. Since it is assumed that the predetermined quantity, which is the amount of donation per smile, is 1 yen, the value of the value obtained by multiplying 1 yen by a coefficient according to the degree of smile is executed. For example, if the degree of smile is simply evaluated on a scale of 10 and multiplied by a ratio that is a coefficient according to the stage, if the degree of smile is 8 on a scale of 10, 1 x 0.8 = 0.8. It becomes a circle. Therefore, if the degree of smile is 8 on a scale of 10, a donation of 0.8 yen will be made by the donation department 104. If the degree of smile is 2 in 10 steps, 1 × 0.2 = 0.2 yen, and a donation of 0.2 yen is executed by the donation department 104.

The predetermined event may be various events such as an event for making a donation.
Although it is assumed that the donation amount per smile is 1 yen, the donation amount can be set to a desired amount.
In the above, the degree of smile is evaluated on a scale of 10, and the coefficient is multiplied accordingly. However, the value of the quantity obtained by multiplying the desired coefficient according to the desired degree is not limited to the 10 grade. You can make a donation.
The donation unit 104 may determine the degree of smile in consideration of the degree of smile determined by the determination unit 106.

The ratio calculation unit 105 calculates the ratio of smiles detected during a predetermined event held in a predetermined store. For example, the ratio calculation unit 105 can calculate the ratio of the time when the smile is detected to the total time of the image captured by the image pickup unit 101. When the total time of the captured image is 2 hours and the time when the smile is detected is 45 minutes, it can be calculated that it is 3.75%. Further, for example, the ratio calculation unit 105 can calculate the ratio of the smile detected by the smile detection unit 103 to the human face detected by the detection unit 102. When the face of the person detected by the detection unit 102 is 1000 times and the face of the person who was smiling is 250 times, it is calculated that the ratio of smiles is 2.5%. Can be done.
The method for calculating the smile ratio is not limited to the above, and various methods may be used.

The determination unit 106 determines the degree of smile detected by the smile detection unit 103. For example, when the donation unit 104 described above makes a donation of a quantity of valuable value obtained by multiplying the degree of smile by a coefficient corresponding to the degree of smile, the determination unit 106 detects the smile detection unit 103. The degree of smile is judged on a scale of 10. The smile in the first stage is a smile, the smile in the tenth stage is a full smile, and the smiles in the second to ninth stages may be appropriately set so that the degree of smile gradually increases.

It should be noted that various methods such as determining the degree of smile on a person's face based on big data having human face data and determining the smile by face recognition technology by AI can be considered, but the degree of smile is determined. It doesn't matter how you do it.
The degree of smile determined by the determination unit 106 is not limited to the 10 levels as described above, and various degrees may be set.

The identification unit 107 individually identifies a person's face included in the image captured by the image pickup unit 101. For example, when the image captured by the imaging unit 101 includes 10 people, each of the 10 people is individually identified. That is, when the inside of a predetermined store is photographed, each person in the store can be individually identified.

The smile detection unit 103 may detect a smile on an individual person identified by the identification unit 107. As a result, the restriction unit 108, which will be described later, can limit the execution of donations by the smile of the same person to a predetermined number of times by the smile detection unit 103. Further, since the smile can be detected for each person, the number of times each person smiles during a predetermined event can be calculated.

The determination unit 106 can determine the degree of smile for each person recognized by the identification unit 107. For example, when the degree of smile is evaluated on a scale of 10, it can be determined that the smile of Mr. A in a predetermined store is 8 and the smile of Mr. Otsu in the same store is 5. Further, since the degree of smile for each person can be determined, the degree of the highest smile recorded by each person during a predetermined event can be determined.

Various techniques for identifying faces by the identification unit 107 can be considered, such as using a face recognition technique, but it suffices if a person's face can be individually identified.

The restriction unit 108 limits the execution of donations by the same person's smile to a predetermined number of times. For example, when a smile included in an image captured by an image pickup unit 101 is detected in a store such as a restaurant, the identification unit 107 identifies that Mr. A and Mr. Otsu are in the store. Then, when the restriction unit 108 limits the execution of donations by the same person's smile to 10 times, when the smile detection unit 103 detects a smile for each of Mr. A and Mr. B, the donation unit 104 makes a donation. You can limit the execution of to 10 times for each of Mr. A and Mr. Otsu, that is, up to 10 yen.

The restriction unit 108 can be set to limit the execution of donations to individual people in the store to a predetermined number of times. For example, if there are Mr. A and Mr. Otsu in a store such as a restaurant, when a smile is detected by the smile detection unit 103, the donation unit 104 will donate up to 10 times. When a smile is detected by the smile detection unit 103, the donation by the donation unit 104 can be set up to 20 times.

In the above-mentioned example, only Mr. A and Mr. Otsu are given as an example, but the number of times may be limited not only by Mr. A and Mr. Otsu but also by a plurality of individual persons by the limiting unit 108.

The smile information registration unit 109 registers information related to the number of times a smile is detected, the detection time, and the detection location. For example, as shown in FIG. 3, the number of smiles detected during a predetermined event in the store is 200 times, and the detection time is 12:03 for the first time and 12 for the second time for each of the number of smiles. You can register at 10 minutes and so on. Further, the detection location may be the location of the store, or may be registered by further dividing the inside of the store. For example, when there are a table seat 1, a table seat 2, and a table seat 3, a smile is detected at the table seat 2 at 12:03 for the first time after specifying the place by the place specifying unit 110 described later. It is possible to register that the smile was detected at the table seat 3 at 12:10 the second time. As for the detection location, as shown in Fig. 3, a predetermined store name can be registered, such as inside a 〇〇 store, while the address of a predetermined store, such as 〇〇 city, 〇〇 prefecture, 〇〇, etc. You can register by any means such as latitude / longitude, IP address, etc.

The example shown in FIG. 3 is an example, and it suffices if information related to the number of detections, the detection time, and the detection location can be registered.
The number of detections may be registered as the total number of detections.

The location specifying unit 110 can specify where the person identified by the identification unit 107 is. For example, when there are a table seat 1, a table seat 2, and a table seat 3 in the store, it can be specified that Mr. A is in the table seat 1 and Mr. B is in the table seat 3.

In addition, although the above shows an example of specifying the location of Mr. A and Mr. B, the location can be specified for a plurality of individual people in the store.
The location specifying unit 110 may specify the location of a person detected by the detection unit 102.

<Example 1>

The processing method of the donation device 100 according to the present embodiment will be described with reference to the flowchart of FIG.

(Step S201) The imaging unit 101 images the inside of a store such as a restaurant or a place where a sport is watched in order to discriminate the faces of a plurality of people. If the image pickup unit 101 is photographing the inside of the store, the process proceeds to step S202.

(Step S202) The detection unit 102 detects a human face included in the image captured by the image pickup unit 101. The detection unit 102 detects a human face while the image pickup unit is taking a picture in step S201.
When the detection unit 102 detects the face of a person included in the image captured by the image pickup unit 101, the detection unit 102 may move to step S211 and specify the location of the detected person by the location identification unit 110.

(Step S203) When the detection unit 102 detects a smile of a person included in the image captured by the image pickup unit 101, the process proceeds to step S206, and the smile detection unit 103 detects the smile.
On the other hand, when the detection unit 102 does not detect the smile of the person included in the image captured by the image pickup unit 101, the process proceeds to step S204.

(Step S204) If the smile is not detected in step S203, the identification unit 107 identifies each person. The identification unit 107 individually identifies a person's face detected by the detection unit 102. When the identification unit 107 identifies an individual person, the process proceeds to step S205, and the restriction unit 108 limits the execution of donations by the same person's smile to a predetermined number of times.
In addition, individual identification may be performed by the identification unit 107 before or after step S206 described later.

(Step S205) In step S202, when the face of a person included in the image captured by the image pickup unit 101 is detected, the person moves to step S204 to identify the face of the person, and then the smile of the same person is determined by the restriction unit 108. Donations may be limited to a given number of times. In this case, even if the identification unit 107 does not identify the individual person, if the number of people is small, the location identification unit 110 can identify the individual person by specifying the location. As a result, the number of donations can be limited by the restriction unit 108 based on the location information.

When the restriction is performed by the restriction unit 108, the number of times is set to be limited by the restriction unit 108 when the process proceeds to step S213 and the donation is executed by the donation unit 104. For example, if the restriction unit 108 limits the execution of donations by the same person's smile to 10 times, the donation unit 104 can make a donation 10 times when the smile detection unit 103 detects a smile. Limited to times. In other words, the maximum amount of donations made by the same person is 10 yen.

The number of times limited by the above-mentioned limiting unit 108 is an example, and the user of the donation device 100 may appropriately set it.

(Step S206) The smile detection unit 103 detects a smile appearing on a person's face detected by the detection unit 102.
When the smile detection unit 103 detects a smile, the process proceeds to step S212, and information related to the number of smiles detected by the smile information registration unit 109, the detection time, and the detection location may be registered.

(Step S207) If the smile detection unit 103 succeeds in detecting the smile, the process proceeds to step S208.
On the other hand, if the smile detection unit 103 fails to detect the smile, the process is terminated and the process from step S201 is started again.
When the process is completed, the user of the donation device 100 may end the process without starting the process from step S201 again when the predetermined time has elapsed.

(Step S208) In this step, step S209, step S210, and step S211 may be freely selected and executed. Further, a plurality of processes may be selected and executed from step S209, step S210, and step S211.
(Step S209) The determination unit 106 determines the degree of smile detected by the smile detection unit 103. When the determination unit 106 determines the degree of smile, the process proceeds to step S213, and the donation unit 104 executes the donation. For example, when the determination unit 106 evaluates a smile on a 10-point scale, when Mr. A's smile is 8, the donation unit 104 receives the information and multiplies the ratio according to the stage to make a donation. To. That is, in the case of this embodiment, 1 × 0.8 = 0.8 yen, and a donation of 0.8 yen is executed.

In the above, the donation amount is 1 yen and the degree of smile by the determination unit 106 is set to 10 levels, but the donation is not limited to this and various values may be set.

(Step S210) The ratio calculation unit 105 calculates the ratio of smiles detected by the smile detection unit 103. Examples are as described above. When the ratio of smiles is calculated by the ratio calculation unit 105, the process may proceed to step S213 and the donation by the donation unit 104 may be executed. In this case, if the donation source of the predetermined event is 10,000 yen and the ratio of smiles by the ratio calculation unit 105 is 2.5%, the donation unit 104 will have 10,000 x 0.25 = 2500 yen. You may make a donation.

(Step S211) The location specifying unit 110 identifies where the person detected by the detection unit 102 or the individual identified by the identification unit 107 is.
For example, when there are a table seat 1, a table seat 2, and a table seat 3 and a person's face is detected at the table seat 1, the place specifying unit 110 identifies the person's place as the table seat 1. do. Further, when Mr. A identified by the identification unit 107 is detected at the table seat 3, the location of Mr. A is specified as the table seat 3.

When the location specifying unit 110 identifies where the person detected by the detection unit 102 or the individual identified by the identification unit 107 is, the process proceeds to step S212, and the smile information registration unit 109 registers the smile information.

The location specifying unit 110 is not limited to the above, and may specify the location of a person detected by the smile detecting unit 103.

(Step S212) The smile information registration unit 109 registers information related to the number of times a smile is detected, the detection time, and the detection location. Examples are as described above. When registration is performed by the smile information registration unit 109, the process may proceed to step S213 and the donation by the donation unit 104 may be executed. In this case, the donation unit 104 may make a donation in consideration of the registered number of times the smile is detected, the detection time, and the detection place. For example, if the detection time is between 12:00 and 13:00 and the number of times the smile is detected is 1000, a donation of 1000 yen can be made. Alternatively, when the number of smiles detected between 13:00 and 14:00 is targeted and the number of smiles detected between 13:00 and 14:00 is 500, a donation of 500 yen can be made. Further, for example, when the detection location is considered by the location specifying unit 110, when there are table seat 1, table seat 2, and table seat 3, the table seat 1 smiles 20 times and the table seat 2 smiles 40 times. It is assumed that the table seat 3 smiles 30 times. At this time, when making a donation for the table seat 1, a donation of 20 yen can be made.

The method of considering the number of detections, the detection time, and the detection location when the donation is executed by the donation unit 104 is not limited to the above.

(Step S213) The donation unit 104 makes a donation of a predetermined amount of valuable value each time the smile detection unit 103 detects a smile. Examples are as described above. In this case, the result of the limiting unit 108 can be used.

The donation unit 104 can make a donation up to a predetermined donation resource. Examples are as described above. In this case, the results obtained by the ratio calculation unit 105 and the smile information registration unit 109 can be used. For example, if the upper limit of donation resources is 10,000 yen and the ratio calculation unit 105 calculates the smile ratio to be 50%, a donation of 5,000 yen may be made.

Each time the donation unit 104 detects a smile, the donation unit 104 makes a donation of the value of the quantity obtained by multiplying the predetermined quantity, which is the donation amount per smile, by a coefficient according to the degree of the smile. In this case, the result of the determination unit 106 can be used. Examples are as described above.

In the present embodiment, the amount of donation by the donation unit 104 is set to 1 yen, but the amount is not limited to 1 yen and various amounts may be set.

The predetermined event may be an ordinary event or an extraordinary event. Further, the predetermined store may include any place, not limited to the inside of the store.

The above donations may include basic income, social security, wealth redistribution systems, wealth sharing, value sharing, and the like.

<Effect of this embodiment>
According to this embodiment, when a predetermined event is held in a store or the like, a donation can be made every time a smile occurs, so that a customer who uses the store can make a donation every time he / she smiles, and the store side can make a donation. Can provide quality service to get customers to make donations with a smile. As a result, it becomes possible to contribute to the SDGs.

<Supplementary information about this embodiment>
Although the present invention has been described above based on the embodiments, the present invention is not limited to the above-described embodiments, and it goes without saying that various modifications and applications are possible within the scope of the gist of the present invention. be.

100 Donation device 101 Imaging unit 102 Detection unit 103 Smile detection unit 104 Donation unit 105 Ratio calculation unit 106 Judgment unit 107 Identification unit 108 Restriction unit 109 Smile information registration unit 110 Location identification unit

Japanese Unexamined Patent Publication No. 2004-13656 Japanese Unexamined Patent Publication No. 2019-3536

Claims (8)

A discriminating means for discriminating a human face included in an image captured by a predetermined imaging means, and
A smile detecting means for detecting a smile appearing on a person's face,
Each time a smile is detected, it has a donation means, which makes a donation of a given amount of valuable value.
Donation device. The donation means makes donations up to the prescribed donation resources.
The donation device according to claim 1. The predetermined imaging means is installed in a predetermined store, and the predetermined imaging means is installed in a predetermined store.
Further having a ratio calculation means for calculating the ratio of smiles detected during a predetermined event held in the predetermined store.
The donation means uses the sales of the predetermined event as the source of the donation.
The donation device according to claim 1 or 2. Further having a determination means for determining the degree of the detected smile,
Each time the donation means detects a smile, the donation of the value of the quantity obtained by multiplying the predetermined quantity by a coefficient according to the degree of the smile is executed.
The donation device according to any one of claims 1 to 3. An identification means for individually identifying a person's face included in the image,
Further has a limiting means for limiting the execution of donations by the same person's smile to a predetermined number of times.
The donation device according to any one of claims 1 to 4. It further has a smile information registration means for registering information related to the number of times a smile is detected, the detection time, and the detection location.
The donation device according to any one of claims 1 to 5. A discrimination step for discriminating a human face included in an image captured by a predetermined imaging means, and a discrimination step.
The smile detection step that detects the smile that appears on the person's face,
Each time a smile is detected, a donation step, which makes a donation of a given amount of valuable value, is carried out,
A donation method characterized by that. Discrimination processing for discriminating a person's face included in an image captured by a predetermined imaging means, and
The smile detection process that detects the smile that appears on the person's face,
Every time a smile is detected, a donation process that executes a donation of a predetermined amount of valuable value is executed.
A computer program that features that.

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