JP7068156B2 - Information processing equipment and programs - Google Patents

Description

The present invention relates to an information processing apparatus and a program.

A device that executes an emotion estimation process for estimating an emotion of a occupant based on a face image of a occupant of a vehicle has been known (see, for example, Patent Document 1).
[Prior Art Document]
[Patent Document]
[Patent Document 1] Japanese Unexamined Patent Publication No. 2018-106530

It is desirable to provide a technique that can contribute to improving the estimation accuracy of emotion estimation processing based on facial images.

According to the first aspect of the present invention, an information processing apparatus is provided. The information processing device may include a status acquisition unit that acquires the status of one moving object. The information processing device is an emotion estimation unit that estimates the emotions of the occupant by executing emotion estimation processing based on the image of the occupant of the moving object captured by the imaging unit mounted on the moving body. It may be provided with an emotion estimation unit that executes emotion estimation processing according to the physical condition.

The information processing device stores emotional tendency information indicating the emotional tendency of the passenger for each situation of the one moving body when the passenger is on board the one moving body. The emotion estimation unit may include an emotion estimation unit, and the emotion estimation unit may execute an emotion estimation process using the emotional tendency of the passenger corresponding to the situation of the moving body. The emotional tendency information storage unit may store emotional tendency information corresponding to each of the plurality of passengers of the one moving body, and the emotional estimation unit may refer to the emotional tendency information corresponding to the passengers. Then, the emotional tendency of the passenger corresponding to the situation of the moving object may be specified.

The emotional tendency information may include the emotional tendency of the passenger corresponding to the situation regarding the moving speed of the moving body. The emotional tendency information may correspond to a situation in which the moving speed of the one moving body is faster than a predetermined speed and an emotional tendency indicating that the passenger is likely to have fear, and the emotion estimation unit may be used. Compared with the case where the emotion of the passenger is estimated without using the emotional tendency information when the moving speed of the one moving body is faster than the predetermined speed, is the emotion of fear of the passenger. The emotions of the above passengers may be estimated so that the degree of the above becomes stronger.

The emotional tendency information may include the emotional tendency of the passenger corresponding to the situation regarding the number of passengers of the one moving object. The emotional tendency information may correspond to a situation in which a plurality of passengers are on board the one moving body and an emotional tendency indicating that the passengers are likely to have joy, and the emotion estimation unit may be used. , The degree of emotion of joy of the passenger as compared with the case of estimating the emotion of the passenger without using the emotional tendency information when a plurality of passengers are on board the one moving body. The emotions of the above passengers may be estimated so that The emotional tendency information may correspond to a situation in which a plurality of passengers are on board the one moving object and an emotional tendency indicating that the passengers are likely to have sadness, and the emotion estimation unit may be used. , When a plurality of passengers are on board the one moving object, the degree of the emotional feelings of the passengers is compared with the case where the emotions of the passengers are estimated without using the emotional tendency information. The emotions of the above passengers may be estimated so that

The one moving object may be an automobile, and the emotional tendency information may include the emotional tendency of the passenger corresponding to the situation regarding the road on which the one moving object is traveling. The emotional tendency information may correlate the situation where the road on which the one moving object is traveling is a highway with the emotional tendency indicating that the passenger is likely to have excitement, and the emotional estimation unit may be used. Compared with the case where the emotion of the passenger is estimated without using the emotional tendency information when the moving body is traveling on the highway, the degree of emotion of the passenger's excitement is higher. The emotions of the passenger may be estimated so as to be stronger. The emotional tendency information may correspond to the situation where the road on which the one moving body is traveling is a highway and the emotional tendency indicating that the passenger is likely to have tension, and the emotional estimation unit may be used. Compared with the case where the emotion of the passenger is estimated without using the emotional tendency information when the moving body is traveling on the highway, the degree of emotion of the passenger's emotion is higher. The emotions of the passenger may be estimated so as to be stronger.

The information processing apparatus may include a data storage unit for storing emotion estimation data for estimating the emotion of the passenger of the one mobile body for each situation of the mobile body, and the emotion estimation unit may include the emotion estimation unit. Emotion estimation processing using emotion estimation data corresponding to the situation of one moving body may be executed. The data storage unit may store an emotion estimation algorithm for estimating the emotion of the passenger of the one moving body for each situation of the moving body, and the emotion estimation unit may store the situation of the one moving body. The emotions of the passenger may be estimated by executing the emotion estimation process based on the image of the passenger captured by the imaging unit using the emotion estimation algorithm corresponding to the above. The data storage unit may store an image of the passenger's neutral facial expression for estimating the emotion of the passenger of the one moving body for each situation of the moving body, and the emotion estimation unit may store the image of the neutral facial expression of the passenger. The emotion of the passenger may be estimated by comparing the image of the passenger captured by the image pickup unit with the image of the neutral facial expression of the passenger corresponding to the situation of the moving body.

According to the second aspect of the present invention, a program for making a computer function as the information processing apparatus is provided.

The outline of the above invention does not list all the necessary features of the present invention. A subcombination of these feature groups can also be an invention.

An example of the vehicle 100 according to the present embodiment is schematically shown. An example of the configuration of the vehicle 100 is shown schematically. An example of the functional configuration of the information processing apparatus 200 is schematically shown. An example of the processing flow by the information processing apparatus 200 is schematically shown. An example of the processing flow by the information processing apparatus 200 is schematically shown. An example of the functional configuration of the information management server 300 is shown schematically. An example of the hardware configuration of the computer 1200 that functions as the information processing apparatus 200 is schematically shown.

Hereinafter, the present invention will be described through embodiments of the invention, but the following embodiments do not limit the invention to which the claims are made. Also, not all combinations of features described in the embodiments are essential to the means of solving the invention.

FIG. 1 schematically shows an example of a vehicle 100 according to this embodiment. The vehicle 100 may be an example of a moving body that carries and moves a plurality of passengers. The vehicle 100 may include an information processing device 200. The information processing device 200 has an emotion estimation processing function for estimating the emotions of the passengers of the vehicle 100.

In the present embodiment, when the person who is on the vehicle 100 is not distinguished, it is described as a passenger, and when the person who is driving and the person who is not driving are distinguished, the former is referred to as the driver 52 and the latter is referred to as the passenger 54. Describe. When the vehicle 100 is an autonomous driving vehicle, the driver 52 may be a person sitting in the driver's seat. The passenger 54 may be a person sitting in the passenger seat. The passenger 54 may be a person sitting in the back seat.

The information processing apparatus 200 may be capable of executing an emotion estimation process for estimating the emotions of the passenger using the image of the passenger. The information processing device 200 acquires an image of a passenger captured by an image pickup unit included in the vehicle 100. The image pickup unit may have one camera 110 capable of capturing the entire interior of the vehicle 100. The information processing apparatus 200 may acquire an image of the driver 52 and an image of the passenger 54 from the camera 110.

The image pickup unit may have a plurality of cameras 110. The information processing apparatus 200 may acquire the image of the driver 52 and the image of the passenger 54 captured by each of the plurality of cameras 110 from the plurality of cameras 110. The image pickup unit includes, for example, a camera 110 capable of capturing an image of a driver's seat and a passenger seat, and a camera 110 capable of imaging a rear seat. The imaging unit may include a camera 110 capable of imaging the driver's seat and a camera 110 capable of imaging the passenger seat. The image pickup unit may have a plurality of cameras 110 capable of photographing each of the plurality of passengers 54 in the rear seats.

The information processing apparatus 200 stores, for example, an image of a passenger's neutral facial expression in advance. The neutral facial expression may be a so-called plain facial expression. The original facial expression of the passenger is, for example, a facial expression when the passenger is not aware of anything. The information processing apparatus 200 may estimate the emotions of the occupant by comparing the facial image of the occupant captured by the camera 110 with the image of the neutral facial expression.

The information processing apparatus 200 stores, for example, an image of the passenger's neutral facial expression captured by the camera 110 as an initial setting. The information processing device 200 may receive and store an image of the passenger's neutral facial expression from another device. The information processing device 200 receives, for example, an image of the passenger's neutral expression from a mobile communication terminal such as a smartphone owned by the passenger via short-range wireless communication such as Bluetooth (registered trademark). Further, the information processing apparatus 200 receives, for example, an image of the passenger's neutral expression from a management server that manages the image of the passenger's neutral expression via a mobile communication network or the like. The information processing device 200 may store a plurality of images having a neutral facial expression for one passenger.

The information processing apparatus 200 may estimate the emotion of the passenger by using the image of the neutral facial expression of the passenger instead of using the image of the neutral facial expression of the passenger. The general-purpose neutral facial expression image may be an average neutral facial expression image of a large number of people. Images of general-purpose neutral facial expressions may be prepared for each attribute such as gender, age, and race.

The information processing apparatus 200 stores, for example, the correspondence data in which the difference from the neutral facial expression and the human emotion pattern are associated with each other in advance. The associative data, for example, associates the raised angle of the mouth with a neutral facial expression and the positive emotion, and associates the lowered angle of the mouth with the negative emotion with respect to the neutral facial expression. The association data may further associate the degree of difference with the neutral facial expression and the degree of emotion. For example, the associative data associates a neutral facial expression with a higher degree as the corner of the mouth rises. The information processing apparatus 200 uses the image of the passenger captured by the camera 110, the image of the neutral facial expression, and the associated data to identify one of the emotional patterns and the degree of emotion for boarding. It is the estimation result of the person's emotions.

As a pattern of human emotions, for example, it is based on a ring model of Russell, which expresses human emotions on the two axes of activity (Arousal) and arousal (Valence), and expresses the degree of emotions by the distance from the origin. Emotional patterns can be adopted. Also, for example, human emotions are classified into eight basic emotions (joy, trust, fear, surprise, sadness, disgust, anger, expectation) and applied emotions by combining two adjacent emotions. Emotional patterns based on the emotional circle of can be adopted. Not limited to these, the information processing apparatus 200 according to the present embodiment may adopt any emotional pattern.

The information processing apparatus 200 does not use an image of a neutral facial expression, but stores a facial image when the passenger has each of a plurality of types of emotions, and then the boarding image captured by the camera 110. The emotion of the occupant may be estimated by comparing the facial image of the person with a plurality of stored facial images. For example, the information processing apparatus 200 identifies a face image most similar to the passenger's face image captured by the camera 110 among a plurality of stored face images, and the type of emotion corresponding to the specified face image. Is the estimation result of the type of emotion of the passenger. Further, the information processing apparatus 200 determines the degree of similarity between the face image of the occupant captured by the camera 110 and the face image most similar to the face image as the estimation result of the degree of emotion of the occupant. good.

The information processing apparatus 200 may estimate the emotion of the occupant based on the fluctuation of the occupant's face image or the like, instead of using the image stored in advance. Various techniques are known as an emotion estimation technique for estimating the emotion of the person from the face image of the person, and any technique among the various techniques can be adopted.

The passengers of the vehicle 100 may have different emotional tendencies depending on the situation of the vehicle 100. For example, there are people who feel scared when the speed is high, but when such a person gets on the vehicle 100, it can be said that there is a high possibility that they will have a feeling of fear in the situation where the speed of the vehicle 100 is high. Also, for example, there are people who are happy to be with other people, but when such a person gets on the vehicle 100, there is a high possibility that they will have a feeling of joy if there are other passengers. I can say. Also, for example, there are people who like to be alone, but when such a person gets on the vehicle 100, it is highly likely that they will feel sad if there are other passengers.

The information processing apparatus 200 according to the present embodiment executes an emotion estimation process according to the situation of the vehicle 100 when estimating the emotions of the passenger. The information processing device 200 stores, for example, emotional tendency information indicating the emotional tendency of the occupant for each situation of the vehicle 100, and the emotion estimation process using the emotional tendency of the occupant corresponding to the situation of the vehicle 100. To execute.

For example, the information processing apparatus 200 estimates the emotions of the passengers so that the degree of fear becomes stronger when the emotions of the passengers who feel scared when the speed is high are estimated as compared with the case where the emotional tendency information is not used. do. The information processing apparatus 200 estimates the emotions of the occupant as in the case where the emotional tendency information is not used, and then makes a correction to increase the degree of fear. Further, for example, the information processing apparatus 200 executes the emotion estimation process after setting the parameters so that the degree of fear becomes stronger. As a result, the probability that the emotion estimation result shows the actual emotion of the passenger can be increased, which can contribute to the improvement of the emotion estimation accuracy.

The information processing apparatus 200 may acquire emotional tendency information by any method. For example, the information processing apparatus 200 acquires emotional tendency information input by the passenger himself / herself. Further, for example, the information processing apparatus 200 may generate emotional tendency information from the emotion estimation result of the passenger. For example, the information processing apparatus 200 identifies the tendency of the occupant's emotion in each of the plurality of situations of the vehicle 100 by collecting and analyzing the situation of the vehicle 100 and the emotion estimation result of the occupant in the situation. And generate emotional tendency information using specific results.

The information processing device 200 may share the generated emotional tendency information with another vehicle 100 or the like. For example, the information processing apparatus 200 acquires the identification information of the passenger who has boarded the vehicle 100, and stores the emotional tendency information generated for the passenger and the identification information in association with each other. Then, the information processing apparatus 200 transmits the identification information and the emotional tendency information stored in association with each other to the information management server 300 via the network 10.

The passenger identification information is, for example, a user ID assigned by the information management server 300. The identification information that can identify the passenger may be any information as long as the passenger can be identified, such as a mobile phone number owned by the passenger.

The network 10 may be any network. For example, the network 10 may include a mobile communication system such as a 3G (3rd Generation) communication system, an LTE (Long Term Evolution) communication system, and a 5G (5th Generation) communication system. The network 10 may include the Internet, a public wireless LAN (Local Area Network), an arbitrary dedicated network, and the like.

The information management server 300 registers identification information and emotional tendency information collected from a plurality of information processing devices 200. For example, when the information management server 300 receives a request including the identification information and the emotional tendency information corresponding to the identification information is registered, the information management server 300 sends the emotional tendency information to the sender of the request. Send.

The source of the request is, for example, the information processing device 200 of the vehicle 100. For example, when a occupant boarded a vehicle 100 equipped with the information processing apparatus 200, the information processing apparatus 200 acquires the identification information of the occupant and sends a request including the identification information to the information management server 300. It transmits and receives emotional tendency information from the information management server 300. Thereby, the information processing apparatus 200 can estimate the emotion of the occupant by using the emotional tendency information generated by the information processing apparatus 200 of the other vehicle 100. The source of the request may be any device as long as it is a device that executes emotion estimation processing based on a person's face image.

FIG. 2 schematically shows an example of the configuration of the vehicle 100. The various configurations shown in FIG. 2 may be a part of the navigation system included in the vehicle 100.

The vehicle 100 includes a camera 110. FIG. 2 illustrates a case where the vehicle 100 includes a camera 110 capable of capturing all of the driver's seat 162, the passenger seat 164, and the rear seat 166. As shown by the angle of view 112 exemplified in FIG. 2, according to the camera 110, the passengers of the driver's seat 162, the passenger's seat 164, and the rear seat 166 can be imaged. The arrangement of the camera 110 in FIG. 2 is an example, and the camera 110 may be arranged at any place as long as all of the driver's seat 162, the passenger's seat 164, and the rear seat 166 can be imaged. The vehicle 100 may include a plurality of cameras 110 that capture images of the driver's seat 162, the passenger seat 164, and the rear seat 166, respectively.

The vehicle 100 includes a microphone 122. FIG. 2 illustrates a case where the vehicle 100 includes a microphone 122 corresponding to all of the driver's seat 162, the passenger seat 164, and the rear seat 166. The arrangement of the microphone 122 in FIG. 2 is an example, and the microphone 122 may be arranged at any place as long as the voices of all the passengers in the driver's seat 162, the passenger seat 164 and the rear seat 166 can be picked up. The vehicle 100 may include a plurality of microphones 122. The plurality of microphones 122 include, for example, a microphone 122 for the driver's seat 162, a microphone 122 for the passenger seat 164, and a microphone 122 for the rear seat 166.

The vehicle 100 includes a speaker 124. FIG. 2 illustrates a case where the vehicle 100 is provided with speakers 124 corresponding to all of the driver's seat 162, the passenger's seat 164, and the rear seat 166. The arrangement of the speaker 124 in FIG. 2 is an example, and the speaker 124 may be arranged at an arbitrary place. The vehicle 100 may include a plurality of speakers 124.

The vehicle 100 includes a display 130. The arrangement of the display 130 in FIG. 2 is an example, and the display 130 may be arranged at any place as long as it can be viewed mainly from the driver's seat 162 and the passenger's seat 164. The display 130 may be a touch panel display. The vehicle 100 may include a plurality of displays 130. For example, the vehicle 100 includes a display 130 for the driver's seat 162 and the passenger seat 164, and a display 130 for the rear seat 166.

The vehicle 100 includes a wireless communication antenna 142. The wireless communication antenna 142 may be an antenna for communicating with a device on the network 10. The vehicle 100 communicates with a device on the network 10 by means of, for example, a wireless communication antenna 142 via a wireless base station, a wireless router, or the like in a mobile communication system. The wireless communication antenna 142 may be an antenna for performing vehicle-to-vehicle communication, road-to-vehicle communication, and the like, and the vehicle 100 communicates with a device on the network 10 via vehicle-to-vehicle communication, road-to-vehicle communication, and the like. You may.

The vehicle 100 includes a GPS (Global Positioning System) antenna 144. The GPS antenna 144 receives radio waves for position measurement from GPS satellites. The vehicle 100 may determine the current location of the vehicle 100 by using the radio wave for position measurement received by the GPS antenna 144. The vehicle 100 may further position the current location of the vehicle 100 by combining positioning by self-contained navigation. The vehicle 100 may position the current location of the vehicle 100 using any known positioning technique.

The vehicle 100 may include a sensor (not shown) capable of detecting the biological information of the passenger of the vehicle 100. The sensor is arranged in, for example, a handle 150, a driver's seat 162, a passenger seat 164, a rear seat 166, and the like, and detects biological information such as a occupant's heartbeat, pulse, sweating, blood pressure, and body temperature. The vehicle 100 may include a short-range wireless communication unit that communicates and connects with a wearable device worn by the occupant, and receives the occupant's biometric information detected by the wearable device from the wearable device. May be good. The short-range wireless communication unit communicates with the wearable device by means of, for example, Bluetooth or the like.

The information processing apparatus 200 may be provided with the above-mentioned various configurations. The information processing device 200 may be integrated with the navigation system included in the vehicle 100, or may be a separate body.

FIG. 3 schematically shows an example of the functional configuration of the information processing apparatus 200. The information processing device 200 includes an image acquisition unit 202, a voice acquisition unit 204, a sensor information acquisition unit 206, an emotion estimation unit 210, a situation acquisition unit 220, an emotional tendency information storage unit 230, an emotional tendency information generation unit 232, and an identification information acquisition unit. It includes 234, emotional tendency information transmission unit 236, emotional tendency information acquisition unit 238, data storage unit 240, and data acquisition unit 242. It is not always essential that the information processing apparatus 200 has all of these configurations.

The image acquisition unit 202 acquires an image of the passenger of the vehicle 100. The image acquisition unit 202 acquires an image of the passenger captured by the image pickup unit of the vehicle 100. The image acquisition unit 202 may continuously acquire the image of the passenger captured by the 100 image pickup units.

The voice acquisition unit 204 acquires the voice of the passenger of the vehicle 100. The voice acquisition unit 204 acquires the occupant's voice input from the microphone 122 of the vehicle 100. The voice acquisition unit 204 may continuously acquire the voice of the occupant from the microphone 122 of the vehicle 100.

The sensor information acquisition unit 206 acquires the biometric information of the occupant of the vehicle 100 detected by the sensor. The sensor information acquisition unit 206 is a living body such as a passenger's heartbeat, pulse, sweating, blood pressure, and body temperature detected by sensors arranged on, for example, a handle 150, a driver's seat 162, a passenger seat 164, and a rear seat 166. Information is acquired from the sensor. Further, the sensor information acquisition unit 206 acquires biological information such as the occupant's heartbeat, pulse, sweating, blood pressure, and body temperature detected by the wearable device worn by the occupant from the wearable device. ..

The emotion estimation unit 210 executes an emotion estimation process to estimate the type and degree of emotions of the passenger. The emotion estimation unit 210 may execute an emotion estimation process using the passenger's face image acquired by the image acquisition unit 202.

Further, the emotion estimation unit 210 may be able to execute the emotion estimation process using the passenger's voice acquired by the voice acquisition unit 204. The emotion estimation unit 210 executes, for example, an emotion estimation process based on the feature amount of the voice itself. Examples of the feature amount of the voice itself include the loudness, tone, spectrum, fundamental frequency, and the like of the voice. The emotion estimation unit 210 may execute an emotion estimation process based on a character string as a result of voice recognition of voice. Further, the emotion estimation unit 210 may execute an emotion estimation process based on both the feature amount of the voice itself and the character string as a result of voice recognition of the voice. When the vehicle 100 is provided with a plurality of microphones that pick up the voices of the plurality of passengers, the emotion estimation unit 210 may identify the speaker by the difference between the microphones. When the voices of a plurality of passengers are picked up by one microphone, the emotion estimation unit 210 may identify the speaker by using a known speaker identification function. As a known speaker identification function, a method using a feature amount of voice, a method of determining from the acquisition direction of voice, and the like are known. Various techniques are known as an emotion estimation technique for estimating the emotion of the person from the voice of the person, and the emotion estimation unit 210 may adopt any technique among the various techniques.

Further, the emotion estimation unit 210 may be able to execute an emotion estimation process using a plurality of types of biological information acquired by the sensor information acquisition unit 206. The emotion estimation unit 210 executes an emotion estimation process using, for example, the occupant's heartbeat, pulse, sweating, blood pressure, body temperature, and the like. Various techniques are known as an emotion estimation technique for estimating a person's emotions from a person's heartbeat, pulse, sweating, blood pressure, body temperature, etc., and the information processing apparatus 200 is any of the various techniques. Technology can be adopted.

The status acquisition unit 220 acquires the status of the vehicle 100. The status acquisition unit 220 acquires, for example, the traveling status of the vehicle 100. The status acquisition unit 220 acquires, for example, the traveling status of the vehicle 100 managed by the navigation system of the vehicle 100 from the navigation system. The navigation system of the vehicle 100 is based on the position information of the vehicle 100, the road data around the vehicle 100, the speed and acceleration of the vehicle 100, the steering operation state, the brake operation state, and the like. May be determined.

The traveling condition of the vehicle 100 may include the condition of the vehicle 100, the condition of the road on which the vehicle 100 is traveling, and the like. The state of the vehicle 100 includes, for example, information about the traveling speed of the vehicle 100. Information on the traveling speed of the vehicle 100 includes, for example, that the vehicle 100 is traveling at a normal speed, that the vehicle 100 is accelerating, that the vehicle 100 is suddenly accelerated, that the vehicle 100 is suddenly stopped, and the like. include.

The condition of the road on which the vehicle 100 is traveling includes, for example, the shape of the road on which the vehicle 100 is traveling. Examples of the shape of the road include straight lines, curves, and slopes. The curve may be subdivided into a loose curve, a normal curve, a sharp curve, and the like depending on the degree of the curve. Slopes may be divided into uphills and downhills, and are subdivided into gentle uphills, normal uphills, steep uphills, gentle downhills, normal downhills, steep downhills, etc. depending on the degree of the slope. It may be converted.

Further, the status acquisition unit 220 acquires, for example, the internal status of the vehicle 100. The situation acquisition unit 220 acquires the internal status of the vehicle 100, for example, by the image acquired by the image acquisition unit 202. The status acquisition unit 220 acquires, for example, the number of passengers in the vehicle 100. Further, the situation acquisition unit 220 acquires information on a person who is on the vehicle 100 by identifying the passenger of the vehicle 100 and identifying an individual.

The emotional tendency information storage unit 230 stores the emotional tendency information of the passenger. The emotional tendency information storage unit 230 may store emotional tendency information corresponding to each of the plurality of passengers. The emotional tendency information storage unit 230 stores, for example, the emotional tendency information of a person who regularly uses the vehicle 100. For example, the emotional tendency information storage unit 230 stores the emotional tendency information of the owner of the vehicle 100 and the person living with the owner. The emotional tendency information storage unit 230 may store emotional tendency information of a person who may board the vehicle 100 in addition to the person who regularly uses the vehicle 100.

The emotional tendency information may include the emotional tendency of the occupant corresponding to the situation regarding the moving speed of the vehicle 100. The emotional tendency information associates, for example, a situation in which the traveling speed of the vehicle 100 is faster than a predetermined speed with an emotional tendency indicating that the passenger is likely to have fear.

The emotional tendency information may include, for example, a passenger's emotional tendency corresponding to a situation regarding the number of passengers in the vehicle 100. The emotional tendency information associates, for example, a situation in which a plurality of passengers are on board the vehicle 100 with an emotional tendency indicating that the passengers are likely to have joy. Further, the emotional tendency information associates, for example, a situation in which a plurality of passengers are on board the vehicle 100 with an emotional tendency indicating that the passengers tend to have sadness.

The emotional tendency information may include the emotional tendency of the occupant corresponding to the situation regarding the road on which the vehicle 100 is traveling. The emotional tendency information associates, for example, a situation where the road on which the vehicle 100 is traveling is a highway with an emotional tendency indicating that the passenger is likely to have excitement. Further, the emotional tendency information associates, for example, a situation where the road on which the vehicle 100 is traveling is an expressway with an emotional tendency indicating that the passenger is likely to have tension.

The emotional tendency information storage unit 230 may store emotional tendency information indicating the emotional tendency of each of the plurality of passengers, as illustrated in Table 1 below, when driving and when riding together.

The emotion estimation unit 210 executes the emotion estimation process according to the situation of the vehicle 100 acquired by the situation acquisition unit 220. For example, the emotion estimation unit 210 refers to the emotional tendency information corresponding to the passenger, and executes the emotion estimation process using the emotional tendency of the passenger corresponding to the situation acquired by the situation acquisition unit 220. When the passenger is the driver 52, the emotion estimation unit 210 may execute an emotion estimation process using emotion tendency information indicating each emotional tendency when the passenger drives. Further, when the passenger is a passenger 54, the emotion estimation unit 210 may execute an emotion estimation process using emotion tendency information indicating each emotional tendency when the passenger is on board.

For example, when there are three passengers, the emotion estimation unit 210 reads out the emotional tendency information of each of the three passengers from the emotional tendency information storage unit 230. Table 2 below shows an example of the read emotional tendency information.

The emotion estimation unit 210, for example, when the moving speed of the vehicle 100 is faster than a predetermined speed, as compared with the case of estimating the emotion of the driver without using the emotion tendency information, the emotion of the driver's excitement. Estimate the driver's emotions so that the degree of Further, the emotion estimation unit 210 estimates the emotion of the passenger A without using the emotion tendency information when the moving speed of the vehicle 100 is faster than a predetermined speed, for example, as compared with the case where the passenger A estimates the emotion of the passenger A. Estimate the emotions of passenger A so that the degree of fear of the passenger becomes stronger.

Since the emotion estimation unit 210 has a plurality of passengers on board the vehicle 100, the degree of emotions of the driver's sorrow is higher than that in the case of estimating the emotions of the driver without using the emotion tendency information. The driver's emotions may be estimated to be stronger. Further, since the emotion estimation unit 210 has a plurality of passengers on board the vehicle 100, the joy of the passenger B is compared with the case where the emotion of the passenger B is estimated without using the emotion tendency information. The driver's emotions may be estimated so that the degree of emotions becomes stronger.

For example, when the vehicle 100 is traveling on a highway, the emotion estimation unit 210 determines the degree of emotion of the driver's excitement as compared with the case where the driver's emotion is estimated without using the emotion tendency information. Estimate the driver's emotions to be stronger. Further, the emotion estimation unit 210 estimates the emotions of the passenger A and the passenger B without using the emotion tendency information, for example, when the vehicle 100 is traveling on the highway. The driver's emotions are estimated so that the degree of excitement of A and passenger B becomes stronger.

As described above, the emotion estimation unit 210 refers to the emotion tendency information corresponding to the passenger, and executes the emotion estimation process using the emotion tendency of the passenger corresponding to the situation of the vehicle 100 to execute each situation. Since the estimation result that reflects the emotional information that the passenger can easily hold can be derived, it can contribute to the improvement of the estimation accuracy.

The emotional tendency information generation unit 232 generates emotional tendency information. The emotional tendency information generation unit 232 generates emotional tendency information from, for example, the situation acquired by the situation acquisition unit 220 and the estimation result of the passenger's emotions estimated by the emotion estimation unit 210 without using the emotional tendency information. .. The emotional tendency information generation unit 232 identifies the tendency of the occupant's emotion in each of the plurality of situations of the vehicle 100 by collecting and analyzing the situation of the vehicle 100 and the emotion estimation result of the occupant in the situation. Then, the emotional tendency information may be generated using the specific result. The emotional tendency information generation unit 232 stores the generated emotional tendency information in the emotional tendency information storage unit 230.

The identification information acquisition unit 234 acquires the identification information of the passenger of the vehicle 100. The identification information acquisition unit 234 identifies a person by applying the person recognition technique to the face image of the passenger acquired by the image acquisition unit 202, and acquires the identification information of the specified person. Further, the identification information acquisition unit 234 identifies a person by applying the speaker recognition technique to the voice of the passenger acquired by the voice acquisition unit 204, and acquires the identification information of the identified person. The identification information acquisition unit 234 may receive the identification information of the passenger from the mobile communication terminal owned by the passenger via short-range wireless communication. The emotional tendency information generation unit 232 may store the emotional tendency information of the passenger in the emotional tendency information storage unit 230 in association with the passenger identification information acquired by the identification information acquisition unit 234.

The emotional tendency information transmission unit 236 transmits the emotional tendency information to which the identification information is associated, which is stored in the emotional tendency information storage unit 230, to the information management server 300. The emotional tendency information transmission unit 236 may transmit the emotional tendency information to the information management server 300 via the network 10.

The emotional tendency information acquisition unit 238 acquires emotional tendency information from the information management server 300. The emotional tendency information acquisition unit 238 transmits, for example, a request including the identification information of the passenger of the vehicle 100 acquired by the identification information acquisition unit 234 to the information management server 300, and the information management server 300 transmits the identification included in the request. Emotional tendency information corresponding to the information may be received. The emotional tendency information acquisition unit 238 may store the emotional tendency information received from the information management server 300 in the emotional tendency information storage unit 230.

The data storage unit 240 stores emotion estimation data for estimating emotions of the passengers of the vehicle 100. The data storage unit 240 may store emotion estimation data for each situation of the vehicle 100. The emotion estimation data may be data generated so that when the vehicle 100 is in a certain situation, the types of emotions that the passenger of the vehicle 100 can easily hold can be easily derived as the estimation result. Further, the emotion estimation data may be data generated so that the degree of emotion of the type of emotion that the passenger is likely to hold when the vehicle 100 is present is a strong degree.

The data storage unit 240 stores, for example, emotion estimation data for each traveling speed of the vehicle 100. Further, the data storage unit 240 stores, for example, emotion estimation data for each number of passengers in the vehicle 100. Further, the data storage unit 240 stores, for example, emotion estimation data for each of automatic driving and manual driving. The data storage unit 240 is not limited to these, and may store emotion estimation data according to various situations.

The emotion estimation unit 210 may execute an emotion estimation process using the emotion estimation data corresponding to the situation acquired by the situation acquisition unit 220. As a result, it is possible to derive an emotion estimation result that reflects the emotional tendency of the occupant according to the situation of the vehicle 100.

The emotion estimation data is, for example, an emotion estimation algorithm. The emotion estimation unit 210 may execute an emotion estimation algorithm using an emotion estimation algorithm corresponding to the situation acquired by the situation acquisition unit 220. The data storage unit 240 may store the emotion estimation algorithm for each situation of the vehicle 100. The data storage unit 240 stores, for example, an emotion estimation algorithm in which the type of emotion that the occupant tends to hold when the vehicle 100 is in a certain situation is easily derived as an estimation result, in association with the situation. Further, the data storage unit 240 associates, for example, an emotion estimation algorithm generated so that the degree of emotion of the type of emotion that the passenger is likely to hold is strong when the vehicle 100 is in a certain situation. And store.

The data storage unit 240 stores, for example, an emotion estimation algorithm for each traveling speed of the vehicle 100. As a specific example, the data storage unit 240 associates an emotion estimation algorithm generated so that the fear emotion of the estimation result becomes stronger with respect to the situation where the traveling speed of the vehicle 100 is faster. This makes it possible to make the degree of fear in the estimation result stronger when estimating the emotion of the passenger who feels scared when the speed is high, and the emotion of the estimation result and the actual feeling of the passenger. Can increase the degree of matching.

Further, the emotion estimation data is, for example, a face image of the passenger's neutral facial expression. The emotion estimation unit 210 compares, for example, the face image of the passenger acquired by the image acquisition unit 202 with the image of the neutral facial expression of the passenger corresponding to the situation acquired by the situation acquisition unit 220. Estimate the passenger's emotions. The data storage unit 240 may store a face image of the passenger's neutral facial expression for each situation of the vehicle 100. The data storage unit 240 stores, for example, a face image of the occupant's neutral facial expression in which the type of emotion that the occupant tends to hold is easily derived as an estimation result when the vehicle 100 is in a certain situation. .. Further, the data storage unit 240 associates, for example, an image of the occupant's neutral facial expression with which the degree of the emotion type that the occupant tends to hold is strong when the vehicle 100 is in a certain situation. And store. A passenger's neutral facial expression, in which the degree of emotions that the passenger is likely to hold is strong, is a facial expression in which the amount of change in the part that changes when these types of emotions are held is greater. May be. For example, if it is determined that the wider the eyes are wide open, the stronger the degree of surprise emotions is, the passenger's neutral facial expression that the degree of surprise emotions is stronger is the facial expression with less spread of eyes. be.

The data storage unit 240 stores, for example, an image of a neutral facial expression for each traveling speed of the vehicle 100. As a specific example, the data storage unit 240 associates an image of the passenger's neutral facial expression such that the feeling of fear of the estimation result becomes stronger with respect to the situation where the traveling speed of the vehicle 100 is faster. This makes it possible to make the degree of fear in the estimation result stronger when estimating the emotion of the passenger who feels scared when the speed is high, and the emotion of the estimation result and the actual feeling of the passenger. Can increase the degree of matching.

FIG. 4 schematically shows an example of the processing flow by the information processing apparatus 200. Here, the flow of processing when the emotion estimation unit 210 executes the emotion estimation process using the emotion tendency information will be described.

In step 102 (the step may be abbreviated as S) 102, the status acquisition unit 220 acquires the status of the vehicle 100. In S104, the image acquisition unit 202 acquires the image of the passenger. In S106, it is determined whether or not the emotion estimation unit 210 executes the emotion estimation process. The emotion estimation unit 210 may, for example, periodically execute the emotion estimation process, and the emotion estimation unit 210 determines whether or not the execution cycle has been reached. The cycle may be, for example, the cycle of the frame of the image acquired by the image acquisition unit 202. If it is determined that the emotion estimation process is to be executed, the process proceeds to S108, and if it is determined not to be executed, the process returns to S102.

In S108, the emotion estimation unit 210 refers to the emotion tendency information corresponding to the passenger to be emotion estimation among the plurality of emotion tendency information stored in the emotion tendency information storage unit 230. When a plurality of passengers are on board the vehicle 100, the emotion estimation unit 210 may refer to the emotional tendency information corresponding to each of the plurality of passengers. In S110, the emotion estimation unit 210 identifies the emotional tendency corresponding to the situation of the vehicle 100 acquired in S102, and executes the emotion estimation process using the emotional tendency. When a plurality of passengers are on board the vehicle 100, the emotion estimation unit 210 may execute the emotion estimation process for each passenger. Then, it returns to S102.

The process shown in FIG. 4 may be continued until the execution of the emotion estimation process is stopped. The information processing apparatus 200 is shown in FIG. 4, for example, when the passenger instructs to stop the execution of the emotion estimation process, the engine of the vehicle 100 is stopped, the power of the vehicle 100 is turned off, and the like. End the process.

FIG. 5 schematically shows an example of the processing flow by the information processing apparatus 200. Here, the flow of processing when the emotion estimation unit 210 executes the emotion estimation process using the emotion estimation data will be described.

In S202, the status acquisition unit 220 acquires the status of the vehicle 100. In S204, the image acquisition unit 202 acquires the image of the passenger. In S206, it is determined whether or not the emotion estimation unit 210 executes the emotion estimation process. If it is determined that the emotion estimation process is to be executed, the process proceeds to S208, and if it is determined not to be executed, the process returns to S202.

In S208, the emotion estimation unit 210 acquires emotion estimation data corresponding to the situation acquired in S202 and the passenger to be emotion estimation target among the plurality of emotion estimation data stored in the data storage unit 240. .. When a plurality of passengers are on board the vehicle 100, the emotion estimation unit 210 may acquire emotion estimation data for each passenger. In S210, the emotion estimation unit 210 executes an emotion estimation process using the emotion estimation data acquired in S208. When a plurality of passengers are on board the vehicle 100, the emotion estimation unit 210 may execute the emotion estimation process for each passenger. Then, it returns to S202.

The process shown in FIG. 5 may be continued until the execution of the emotion estimation process is stopped. The information processing apparatus 200 is shown in FIG. 5, for example, when the passenger instructs to stop the execution of the emotion estimation process, the engine of the vehicle 100 is stopped, the power of the vehicle 100 is turned off, and the like. End the process.

FIG. 6 schematically shows an example of the functional configuration of the information management server 300. The information management server 300 includes an emotional tendency information receiving unit 302, an emotional tendency information storage unit 304, a request receiving unit 306, and an emotional tendency information transmitting unit 308.

The emotional tendency information receiving unit 302 receives emotional tendency information associated with identification information from a plurality of information processing devices 200 via the network 10. The emotional tendency information storage unit 304 stores the emotional tendency information received by the emotional tendency information receiving unit 302.

The request receiving unit 306 receives a request for emotional tendency information including identification information. When the request receiving unit 306 receives the request, the emotional tendency information transmitting unit 308 determines whether or not the emotional tendency information corresponding to the identification information included in the request is stored in the emotional tendency information storage unit 230. If stored, send emotional tendency information to the source of the request.

FIG. 7 schematically shows an example of a hardware configuration of a computer 1200 that functions as an information processing apparatus 200. A program installed on the computer 1200 causes the computer 1200 to function as one or more "parts" of the device according to the embodiment, or causes the computer 1200 to perform an operation associated with the device according to the embodiment or the one or the like. A plurality of "parts" can be executed and / or a computer 1200 can be made to execute a process according to the above embodiment or a stage of the process. Such a program may be run by the CPU 1212 to cause the computer 1200 to perform certain operations associated with some or all of the blocks of the flowcharts and block diagrams described herein.

The computer 1200 according to this embodiment includes a CPU 1212, a RAM 1214, and a graphic controller 1216, which are interconnected by a host controller 1210. The computer 1200 also includes input / output units such as a communication interface 1222, a storage device 1224, a DVD drive 1226, and an IC card drive, which are connected to the host controller 1210 via the input / output controller 1220. The DVD drive 1226 may be a DVD-ROM drive, a DVD-RAM drive, or the like. The storage device 1224 may be a hard disk drive, a solid state drive, or the like. The computer 1200 also includes an input / output unit such as a ROM 1230 and a touch panel, which are connected to the input / output controller 1220 via an input / output chip 1240.

The CPU 1212 operates according to a program stored in the ROM 1230 and the RAM 1214, thereby controlling each unit. The graphic controller 1216 acquires the image data generated by the CPU 1212 in a frame buffer or the like provided in the RAM 1214 or itself so that the image data is displayed on the display device 1218. The computer 1200 may not be equipped with a display device 1218, in which case the graphics controller 1216 causes the image data to be displayed on an external display device.

The communication interface 1222 communicates with other electronic devices via a wireless communication network. The storage device 1224 stores programs and data used by the CPU 1212 in the computer 1200. The DVD drive 1226 reads the program or data from the DVD-ROM 1227 or the like and provides it to the storage device 1224. The IC card drive reads the program and data from the IC card and / or writes the program and data to the IC card.

The ROM 1230 stores in it a boot program or the like executed by the computer 1200 at the time of activation, and / or a program depending on the hardware of the computer 1200. The input / output chip 1240 may also connect various input / output units to the input / output controller 1220 via a USB port or the like.

The program is provided by a computer-readable storage medium such as a DVD-ROM 1227 or an IC card. The program is read from a computer-readable storage medium, installed in a storage device 1224, RAM 1214, or ROM 1230, which is also an example of a computer-readable storage medium, and executed by the CPU 1212. The information processing described in these programs is read by the computer 1200 and provides a link between the program and the various types of hardware resources described above. The device or method may be configured to implement the operation or processing of information in accordance with the use of the computer 1200.

For example, when communication is executed between the computer 1200 and an external device, the CPU 1212 executes a communication program loaded in the RAM 1214, and performs communication processing with respect to the communication interface 1222 based on the processing described in the communication program. You may order. Under the control of the CPU 1212, the communication interface 1222 reads and reads transmission data stored in a transmission buffer area provided in a recording medium such as a RAM 1214, a storage device 1224, a DVD-ROM 1227, or an IC card. The data is transmitted to the network, or the received data received from the network is written to the reception buffer area or the like provided on the recording medium.

Further, the CPU 1212 makes the RAM 1214 read all or necessary parts of a file or a database stored in an external recording medium such as a storage device 1224, a DVD drive 1226 (DVD-ROM1227), an IC card, etc., on the RAM 1214. Various types of processing may be performed on the data of. The CPU 1212 may then write back the processed data to an external recording medium.

Various types of information such as various types of programs, data, tables, and databases may be stored in recording media and processed. The CPU 1212 describes various types of operations, information processing, conditional judgment, conditional branching, unconditional branching, and information retrieval described in various parts of the present disclosure with respect to the data read from the RAM 1214. Various types of processing may be performed, including / replacement, etc., and the results are written back to the RAM 1214. Further, the CPU 1212 may search for information in a file, database, or the like in the recording medium. For example, when a plurality of entries each having an attribute value of the first attribute associated with the attribute value of the second attribute are stored in the recording medium, the CPU 1212 is the first of the plurality of entries. The attribute value of the attribute of is searched for the entry that matches the specified condition, the attribute value of the second attribute stored in the entry is read, and the attribute value of the second attribute is changed to the first attribute that satisfies the predetermined condition. You may get the attribute value of the associated second attribute.

The program or software module described above may be stored on a computer 1200 or in a computer-readable storage medium near the computer 1200. Further, a recording medium such as a hard disk or RAM provided in a dedicated communication network or a server system connected to the Internet can be used as a computer-readable storage medium, whereby the program can be transferred to the computer 1200 via the network. offer.

The blocks in the flowcharts and block diagrams of the above embodiments may represent the stages of the process in which the operation is performed or the "parts" of the device responsible for performing the operation. Specific steps and "parts" are supplied with dedicated circuits, programmable circuits supplied with computer-readable instructions stored on computer-readable storage media, and / or computer-readable instructions stored on computer-readable storage media. It may be implemented by the processor. Dedicated circuits may include digital and / or analog hardware circuits, and may include integrated circuits (ICs) and / or discrete circuits. Programmable circuits include logical products, logical sums, exclusive logical sums, negative logical sums, negative logical sums, and other logical operations, such as, for example, field programmable gate arrays (FPGAs), programmable logic arrays (PLAs), and the like. , Flipflops, registers, and reconfigurable hardware circuits, including memory elements.

The computer readable storage medium may include any tangible device capable of storing instructions executed by the appropriate device, so that the computer readable storage medium having the instructions stored therein may be in a flow chart or block diagram. It will be equipped with a product that contains instructions that can be executed to create means for performing the specified operation. Examples of the computer-readable storage medium may include an electronic storage medium, a magnetic storage medium, an optical storage medium, an electromagnetic storage medium, a semiconductor storage medium, and the like. More specific examples of computer-readable storage media include floppy (registered trademark) disks, diskettes, hard disks, random access memory (RAM), read-only memory (ROM), and erasable programmable read-only memory (EPROM or flash memory). , Electrically Erasable Programmable Read Only Memory (EEPROM), Static Random Access Memory (SRAM), Compact Disc Read Only Memory (CD-ROM), Digital Versatile Disc (DVD), Blu-ray® Disc, Memory Stick , Integrated circuit cards and the like may be included.

Computer-readable instructions are assembler instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcodes, firmware instructions, state-setting data, or object-oriented programming such as Smalltalk, JAVA®, C ++, etc. Includes either source code or object code written in any combination of one or more programming languages, including languages and traditional procedural programming languages such as the "C" programming language or similar programming languages. good.

Computer-readable instructions are used to generate means for a general-purpose computer, a special-purpose computer, or the processor of another programmable data processing device, or a programmable circuit, to perform an operation specified in a flowchart or block diagram. General purpose computers, special purpose computers, or other programmable data processing locally or via a local area network (LAN), a wide area network (WAN) such as the Internet, etc. to execute such computer-readable instructions. It may be provided to the processor of the device or a programmable circuit. Examples of processors include computer processors, processing units, microprocessors, digital signal processors, controllers, microcontrollers, and the like.

In the above embodiment, the vehicle 100 has been described as an example of the moving body, but the present invention is not limited to this. The moving body may be any as long as it can move with a plurality of passengers on board. For example, in addition to the vehicle 100, it may be a train, an airplane, a ship, or the like.

Although the present invention has been described above using the embodiments, the technical scope of the present invention is not limited to the scope described in the above embodiments. It will be apparent to those skilled in the art that various changes or improvements can be made to the above embodiments. It is clear from the description of the claims that the form with such changes or improvements may be included in the technical scope of the present invention.

The order of execution of each process such as operation, procedure, step, and step in the device, system, program, and method shown in the claims, specification, and drawings is particularly "before" and "prior to". It should be noted that it can be realized in any order unless the output of the previous process is used in the subsequent process. Even if the scope of claims, the specification, and the operation flow in the drawings are explained using "first", "next", etc. for convenience, it means that it is essential to carry out in this order. It's not a thing.

10 network, 52 driver, 54 passenger, 100 vehicle, 110 camera, 112 angle of view, 122 microphone, 124 speaker, 130 display, 142 wireless communication interface, 144 GPS antenna, 150 handle, 162 driver's seat, 164 passenger's seat, 166 rear seat, 200 information processing device, 202 image acquisition unit, 204 voice acquisition unit, 206 sensor information acquisition unit, 210 emotion estimation unit, 220 situation acquisition unit, 230 emotional tendency information storage unit, 232 emotional tendency information generation unit, 234 Identification information acquisition unit, 236 emotional tendency information transmission unit, 238 emotional tendency information acquisition unit, 240 data storage unit, 242 data acquisition unit, 300 information management server, 302 emotional tendency information reception unit, 304 emotional tendency information storage unit, 306 request Receiver, 308 Emotional trend information transmitter, 1200 computer, 1210 host controller, 1212 CPU, 1214 RAM, 1216 graphic controller, 1218 display device, 1220 input / output controller, 1222 communication interface, 1224 storage device, 1226 DVD drive, 1227 DVD -ROM, 1230 ROM, 1240 input / output chip

Claims (9)

The status acquisition unit that acquires the status of one moving object,
Emotional tendency information storage unit that stores emotional tendency information indicating the emotional tendency of the passenger for each situation of the one moving body when the passenger of the one moving body is boarding the one moving body. When,
It is an emotion estimation unit that estimates the emotions of the passenger by executing an emotion estimation process based on the image of the passenger of the moving body imaged by the imaging unit mounted on the moving body. It is equipped with an emotion estimation unit that executes emotion estimation processing according to the situation of the moving body .
The emotional tendency information includes the emotional tendency of the passenger corresponding to the situation regarding the number of passengers of the one moving object.
The emotion estimation unit is an information processing device that executes an emotion estimation process using the emotional tendency of the passenger corresponding to the situation of the moving body . The emotional tendency information associates a situation in which a plurality of passengers are on board the one moving object with an emotional tendency indicating that the passengers are likely to have joy.
The emotion estimation unit estimates the emotions of the passengers when a plurality of passengers are on board the moving object, as compared with the case where the emotions of the passengers are estimated without using the emotional tendency information. The information processing apparatus according to claim 1, wherein the passenger's emotions are estimated so that the degree of joyful emotions becomes stronger. The emotional tendency information associates a situation in which a plurality of passengers are on board the one moving object with an emotional tendency indicating that the passengers are likely to have sadness.
The emotion estimation unit estimates the emotions of the passengers when a plurality of passengers are on board the moving object, as compared with the case where the emotions of the passengers are estimated without using the emotional tendency information. The information processing apparatus according to claim 1, wherein the passenger's emotions are estimated so that the degree of sorrowful emotions becomes stronger . The status acquisition unit that acquires the status of one moving object,
Emotional tendency information storage unit that stores emotional tendency information indicating the emotional tendency of the passenger for each situation of the one moving body when the passenger of the one moving body is boarding the one moving body. When,
It is an emotion estimation unit that estimates the emotions of the passenger by executing an emotion estimation process based on the image of the passenger of the moving body imaged by the imaging unit mounted on the moving body. With the emotion estimation unit that executes the emotion estimation process according to the situation of the moving body
Equipped with
The emotional tendency information associates a situation in which the moving speed of the one moving object is faster than a predetermined speed with an emotional tendency indicating that the passenger is likely to have fear or excitement.
The emotion estimation unit estimates the emotion of the passenger when the moving speed of the one moving body is faster than a predetermined speed, as compared with the case where the emotion of the passenger is estimated without using the emotion tendency information. An information processing device that estimates the passenger's emotions so that the degree of fear or excitement of the passenger becomes stronger. The status acquisition unit that acquires the status of one moving object,
Emotional tendency information storage unit that stores emotional tendency information indicating the emotional tendency of the passenger for each situation of the one moving body when the passenger of the one moving body is boarding the one moving body. When,
It is an emotion estimation unit that estimates the emotions of the passenger by executing an emotion estimation process based on the image of the passenger of the moving body imaged by the imaging unit mounted on the moving body. With the emotion estimation unit that executes the emotion estimation process according to the situation of the moving body
Equipped with
The one moving object is a car,
The emotional tendency information associates the situation where the road on which the one moving object is traveling is a highway with the emotional tendency indicating that the passenger is likely to have excitement.
The emotion estimation unit determines the emotion of the passenger when the moving body is traveling on the highway, as compared with the case where the emotion of the passenger is estimated without using the emotion tendency information. An information processing device that estimates the emotions of the passenger so that the degree of emotions becomes stronger. The status acquisition unit that acquires the status of one moving object,
Emotional tendency information storage unit that stores emotional tendency information indicating the emotional tendency of the passenger for each situation of the one moving body when the passenger of the one moving body is boarding the one moving body. When,
It is an emotion estimation unit that estimates the emotions of the passenger by executing an emotion estimation process based on the image of the passenger of the moving body imaged by the imaging unit mounted on the moving body. With the emotion estimation unit that executes the emotion estimation process according to the situation of the moving body
Equipped with
The one moving object is a car,
The emotional tendency information associates the situation where the road on which the one moving object is traveling is a highway with the emotional tendency indicating that the passenger is likely to have tension.
The emotion estimation unit estimates the emotions of the passenger when the moving body is traveling on the highway, as compared with the case where the emotions of the passenger are estimated without using the emotion tendency information. An information processing device that estimates the emotions of the passenger so that the degree of emotions becomes stronger. The status acquisition unit that acquires the status of one moving object,
A data storage unit that stores an image of the passenger's neutral facial expression for estimating the emotion of the passenger of the one moving body for each situation of the moving body.
It is an emotion estimation unit that estimates the emotions of the passenger by executing an emotion estimation process based on the image of the passenger of the moving body imaged by the imaging unit mounted on the moving body. An emotion estimation unit that executes emotion estimation processing according to the situation of the moving body, and
Equipped with
The emotion estimation unit compares the image of the occupant captured by the imaging unit with the image of the occupant's neutral facial expression corresponding to the situation of the moving object of the occupant. An information processing device that estimates emotions. The status acquisition unit that acquires the status of one moving object,
Emotional tendency information storage unit that stores emotional tendency information indicating the emotional tendency of the passenger for each situation of the one moving body when the passenger of the one moving body is boarding the one moving body. When,
It is an emotion estimation unit that estimates the emotions of the passenger by executing an emotion estimation process based on the image of the passenger of the moving body imaged by the imaging unit mounted on the moving body. With the emotion estimation unit that executes the emotion estimation process according to the situation of the moving body
Equipped with
The emotional tendency information storage unit stores the emotional tendency information indicating the tendency of each emotion when the passenger drives the one moving body and when the passenger rides on the one moving body.
The emotion estimation unit corresponds to the situation of the one moving body by using the emotion tendency information indicating the tendency of each emotion when the passenger is a driver. The emotion estimation process using the emotional tendency of the passenger is executed, and when the passenger is a passenger, the emotional tendency information indicating the tendency of each emotion when the passenger is on board is used to describe the above. An information processing device that executes an emotion estimation process using the emotional tendency of the passenger corresponding to the situation of one moving body. A program for operating a computer as an information processing device according to any one of claims 1 to 8 .

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