Patent Publication Number: US-2019193261-A1

Title: Information processing device, information processing method, and non-transitory computer-readable recording medium for acquiring information of target

Description:
CROSS-REFERENCE TO RELATED APPLICATION 
     This application is based upon and claims the benefit of priority from the prior Japanese Patent Application No. 2017-247740, filed Dec. 25, 2017, the entire contents of which are incorporated herein by reference. 
     FIELD 
     This application relates generally to an information processing device, an information processing method, and a non-transitory computer-readable recording medium for acquiring information of a target. 
     BACKGROUND 
     Techniques for acquiring preregistered information through the Internet are known. 
     Unexamined Japanese Patent Application Kokai Publication No. 2008-048287 discloses a network community system that comprises a person registration server and person information that is preregistered on the person registration server and acquires the preregistered person information. 
     SUMMARY 
     A mode of the information processing device according to the present disclosure comprises: 
     a processor and a memory, 
     wherein the processor 
     acquires information regarding a determination target, 
     determines, based on the information that is acquired, whether the determination target corresponds to a given target that is preregistered in the memory, and 
     determines, based on the information that is acquired, whether the determination target corresponds to a target that is other than the given target and has a given relationship to the given target. 
     A mode of the information processing method according to the present disclosure is an information processing method for an information processing device, including: 
     acquiring information regarding a determination target; 
     determining, based on the information that is acquired, whether the determination target corresponds to a given target that is preregistered; and 
     determining, based on the information that is acquired, whether the determination target corresponds to a target that is other than the given target and has a given relationship to the given target. 
     A mode of the non-transitory computer-readable recording medium according to the present disclosure saves a program that allows a computer of an information processing device to function as: 
     a target information acquirer that acquires information regarding a determination target; 
     a first target determiner that determines, based on the information that is acquired by the target information acquirer, whether the determination target corresponds to a given target that is preregistered; and 
     a second target determiner that determines, based on the information that is acquired by the target information acquirer, whether the determination target corresponds to a target that is other than the given target and has a given relationship to the given target. 
     Additional objects and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objects and advantages of the invention may be realized and obtained by means of the instrumentalities and combinations particularly pointed out hereinafter. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate embodiments of the invention, and together with the general description given above and the detailed description of the embodiments given below, serve to explain the principles of the invention. 
       A more complete understanding of this application can be obtained when the following detailed description is considered in conjunction with the following drawings, in which: 
         FIG. 1  is an illustration that shows the robot according to an embodiment of the present disclosure; 
         FIG. 2  is a block diagram that shows the configuration of the robot according to the embodiment of the present disclosure; 
         FIG. 3  is an illustration that shows information that is stored by the user storage of the robot according to the embodiment of the present disclosure; 
         FIG. 4  is a diagram that shows the configuration of the server according to the embodiment of the present disclosure; 
         FIG. 5  is an illustration that shows information that is stored by the database of the server according to the embodiment of the present disclosure; 
         FIG. 6  is a flowchart that shows the operation procedure according to the embodiment of the present disclosure; 
         FIG. 7  is a flowchart that shows the registration procedure according to the embodiment of the present disclosure; 
         FIG. 8  is a chart for explaining the data transmission procedure according to the embodiment of the present disclosure; 
         FIG. 9  is an illustration for explaining the operation procedure and the registration procedure according to the embodiment of the present disclosure; and 
         FIG. 10  is an illustration that shows information that is stored by the database of the server according to a modified embodiment of the present disclosure. 
     
    
    
     DETAILED DESCRIPTION 
     An information processing system that comprises a robot and a server that comprise the information processing device according to a mode for implementing the present disclosure will be described below with reference to the drawings. 
     Embodiment 
     An information processing system  1  according to an embodiment of the present disclosure comprises, as shown in  FIG. 1 , a robot  100  and a server (second device)  200 . The robot  100  is a robot device that has an imager  103  that captures images and captures an image of, for example, the face of a person who is a determination target and autonomously operates. The person includes, for example, a registered person who is a given target that is preregistered with the robot  100  and, for example, an unregistered person who is not registered with the robot  100 . The given target includes the user of the robot  100 , relatives and friends of the user, and the like. The server  200  is, for example, a social networking service (SNS) server device and stores account information of people who are registered on the SNS. People who are registered on the SNS include registered persons who are preregistered with the robot  100  and unregistered persons who are not registered with the robot  100 . The account information includes the name of a person, his facial characteristic quantity, and information of persons who are registered as his friend. The robot  100  and the server  200  are configured to be mutually communicable via a wired line or a wireless line. 
     The robot  100  has, as shown in  FIG. 1 , for example, a figure that is deformed from a human and comprises a head  101  on which members that imitate eyes, a mouth, and a nose are disposed, a body (enclosure)  102  on which members that imitate hands and feet are disposed, the imager  103  and a speaker  104  that are disposed on the head  101 , a mover (moving device)  105  that is disposed at the bottom, and an operation button  150  that is provided on the back of the body  102 . The robot  100  has a controller  110 , a communicator  120 , a user storage  130 , and a power source  140  inside the body  102 . The controller  110  functions as an information processing device and a control device. 
     The imager  103  is provided in the lower part of the front of the head  101  at the position of the nose on a human face. The imager  103  captures an image of a person or the like based on the control of the controller  110  that is described later and outputs data that present the captured image to the controller  110 . 
     The speaker  104  is provided at the position of the mouth on the head  101  and utters an utterance based on the control of the controller  110 . 
     The mover  105  comprises a motor and tires and moves the robot  100  based on the control of the controller  110 . 
     The controller  110  comprises a central processing unit (CPU), a read only memory (ROM), and a random access memory (RAM). The ROM comprises a nonvolatile memory such as a flash memory and stores programs for the controller  110  to realize various functions. The RAM comprises a volatile memory and is used as the work area for the controller  110  to execute programs for performing various procedures. Moreover, the RAM stores data of acquired images. As the CPU reads a program that is stored in the ROM and executes the program on the RAM, the controller  110  functions as, as shown in  FIG. 2 , an image acquirer (target information acquirer)  111 , an image analyzer (target determiner)  112 , a determiner (relationship determiner)  113 , an operation controller (operator)  114 , and a register  115 . 
     The image acquirer  111  controls the imaging operation of the imager  103 , acquires data that present an image that is captured by the imager  103 , and stores in the RAM the data of the image that is acquired as data of the acquired image. 
     The image analyzer  112  analyzes the acquired image that is stored in the RAM and detects the number of persons who appear in the acquired image, m (m is a natural number). Moreover, the image analyzer  112  determines whether the facial characteristic quantity of a person who appears in the acquired image matches the facial characteristic quantity of a registered person who is preregistered in the user storage  130 . In detail, the image analyzer  112  extracts the faces of persons from the acquired image through face recognition and detects the number of persons who appear in the captured image, m, from the number of extracted faces. Next, the image analyzer  112  extracts the facial characteristic quantity of the n-th person from the acquired image. n is a natural number from 1 to m. The n-th person can be determined on an arbitrary basis. For example, it is assumed that the person who appears on the right in the image is the first person and the person who appears on the left in the image is the m-th person. Next, the image analyzer  112  determines whether the facial characteristic quantity of each of the first through m-th persons matches the facial characteristic quantity of a registered person who is preregistered in the user storage  130 . 
     If the image analyzer  112  determines that a person who appears in the acquired image does not match the facial characteristic quantity of any registered person, the determiner  113  determines a relationship between the person who appears in the acquired image and the registered person. In detail, the determiner  113  accesses (logs in) the account of a registered person that is stored in the server  200  via the communicator  120  and acquires account information of the registered person that is transmitted by the server  200 . Next, it is determined, based on the account information of the registered person, whether the person who appears in the acquired image and the registered person are on close terms. For example, using as an indicator that indicates the degree of closeness whether a person is registered as a friend that is included in the account information of the registered person, a person who is registered as a friend is extracted as a person of interest who is on close terms with the registered person. Next, the determiner  113  acquires the account information of the person of interest that is transmitted by the server  200 . The account information that is acquired here is the name and the facial characteristic quantity of the person of interest. The facial characteristic quantity may be extracted from a face picture that is included in the account information. Next, the determiner  113  determines whether the facial characteristic quantity of the person who appears in the acquired image and the facial characteristic quantity of the person of interest match, thereby determining whether the person who appears in the acquired image and the registered person are on close terms. 
     If the image analyzer  112  determines that the facial characteristic quantity of a person who appears in the acquired image matches the facial characteristic quantity of a registered person who is preregistered in the user storage  130 , the operation controller  114  executes a first robot operation. In detail, the first robot operation is to move closer to the person who is determined to be matched by the mover  105 , utter the name of the person from the speaker  104 , and the like. Moreover, if the determiner  113  determines that the facial characteristic quantity of a person who appears in the acquired image matches the facial characteristic quantity of a person of interest that is acquired from the server  200 , the operation controller  114  executes a second robot operation (a given operation). In detail, the second robot operation is, for example, to move closer to the person who appears in the acquired image by the mover  105 , utter the name of the person from the speaker  104 , say “How do you do?” in greeting as an expression of feeling, and the like. 
     If the determiner  113  determines that the facial characteristic quantity of a person who appears in the acquired image matches the facial characteristic quantity of a person of interest that is acquired from the server  200  and that the person is the person of interest, the register  115  automatically registers in the user storage  130 , as a new given target, data that present the name and the facial characteristic quantity that are stored in the account of that person. 
     The communicator  120  communicates with the server  200  and receives the account information of a registered person and the account information of a person who is registered as a friend with the registered person. The communicator  120  comprises a wireless communication module of a wireless local area network (LAN), Bluetooth (registered trademark), or the like. 
     The user storage  130  comprises a nonvolatile memory such as a flash memory and stores, as shown in  FIG. 3 , the name, the facial characteristic quantity, and the like of a registered person who is preregistered. 
     Returning to  FIG. 2 , the power source  140  comprises a rechargeable battery that is built in the body  102  and supplies electric power to the parts of the robot  100 . 
     The operation button  150  is provided on the back of the body  102 , serves as a button for operating the robot  100 , and includes a power button. 
     The server  200  comprises, as shown in  FIG. 4 , a controller  210 , a communicator  220 , and a database  230 . 
     The controller  210  comprises a CPU, a ROM, and a RAM. The ROM comprises a nonvolatile memory such as a flash memory and stores programs for the controller  210  to realize various functions. The RAM comprises a volatile memory and is used as the work area for the controller  210  to execute programs for performing various procedures. As the CPU reads a program that is stored in the ROM and executes the program on the RAM, the controller  210  functions as an account information transmitter  211 . 
     The account information transmitter  211  acquires information that is transmitted by the robot  100  and presents the name of the account of a registered person via the communicator  220 , searches the database  230  for the account of the registered person, and transmits the account information of the registered person to the robot  100 . The account information includes information that presents a person of interest who is a person who is registered as a friend with the registered person. When information that is transmitted by the robot  100  and presents a person of interest is acquired, the account of the person of interest is searched for. Next, the account information of the person of interest is transmitted to the robot  100 . The account information includes the name and the facial characteristic quantity of a person. 
     The communicator  220  communicates with the communicator  120  of the robot  100  and transmits the account information of a registered person and the account information of a person of interest. The communicator  220  comprises a wireless communication module of a wireless local area network (LAN), Bluetooth (registered trademark), or the like. 
     The database  230  comprises an SNS database that stores, as shown in  FIG. 5 , accounts A, B, . . . , X, Y, . . . . The accounts A, B, . . . , X, Y, . . . each store a name, a facial characteristic quantity, persons who are registered as a friend, and the like. For example, the account A includes the name of A, the facial characteristic quantity of A, persons B, S, T, . . . who are registered as a friend with A. 
     Next, the operation procedure and the registration procedure that are executed by the robot  100  and the data transmission procedure that is executed by the server  200 , which have the above configurations, will be described. When an imaged person is a registered person, the operation procedure includes a procedure for the robot  100  to execute a given operation. When an imaged person is an unregistered person, in the registration procedure, the robot  100  accesses the server  200  to determine whether the person is on close terms with a registered person and if on close terms, executes a given operation. 
     As the user operates the operation button  150  to power on, the robot  100  responds to the order to power on and starts the operation procedure shown in  FIG. 6 . As the server administrator powers on the server  200 , the data transmission procedure shown in  FIG. 8  is started. The operation procedure that is executed by the robot  100  will be described below using the flowchart. 
     First, the image acquirer  111  makes the imager  103  start capturing an image (Step S 101 ) and stores the captured image in the RAM as an acquired image. Next, the image analyzer  112  detects the number of persons who appear in the acquired image, m (Step S 102 ). In detail, the image analyzer  112  extracts the faces of persons from the image through face recognition and detects the number of persons who appear in the acquired image, m, from the number of extracted faces. Next, a variable n=1 is set (Step S 103 ). Next, the image analyzer  112  extracts the facial characteristic quantity of the n-th person from the acquired image (Step S 104 ). The n-th person can be determined on an arbitrary basis and, for example, it is assumed that the person who appears on the right in the image is the first person and the person who appears on the left in the image is the m-th person. Next, the image analyzer  112  determines whether the facial characteristic quantity of the n-th person matches the facial characteristic quantity of a registered person who is preregistered in the user storage  130  (Step S 105 ). 
     If determined to be matched (Step S 105 ; Yes), the operation controller  114  executes a first robot operation (Step S 106 ). In detail, the first robot operation includes moving closer to the n-th person and uttering the name of the n-th person. Next, the variable n is incremented (Step S 107 ). Next, the operation controller  114  determines whether the variable n&gt;the number of persons, m, is satisfied (Step S 108 ). If determined that the variable n&gt;the number of persons, m, is not satisfied (Step S 108 ; No), the processing returns to the Step S 104  to extract the facial characteristic quantity of the n-th person. 
     If the image analyzer  112  determines that the facial characteristic quantity of the n-th person does not match the facial characteristic quantity of any registered person who is preregistered in the user storage  130  (Step S 105 ; No), the registration procedure shown in  FIG. 7  is implemented (Step S 109 ). The determiner  113  accesses the server  200  via the communicator  120  (Step S 201 ). Next, the determiner  113  accesses the account of a registered person and acquires the account information of the registered person (Step S 202 ). Next, a person who is registered as a friend with the registered person is extracted from the account information of the registered person (Step S 203 ). Next, the determiner  113  acquires account information from the account of the person who is registered as a friend (Step S 204 ). The information that is acquired here is the name and the facial characteristic quantity of the person who is registered as a friend. The facial characteristic quantity may be extracted from a face picture that is stored in the account. Next, the determiner  113  determines whether the facial characteristic quantity of the n-th person who appears in the acquired image matches the facial characteristic quantity of the person who is registered as a friend that is acquired from the server  200  (Step S 205 ). 
     If determined to be matched (Step S 205 ; Yes), the register  115  assumes that the n-th person is a person who is on close terms with the registered person and registers data that present the name and the facial characteristic quantity in the user storage  130  (Step S 206 ). Subsequently, the registration procedure ends and the processing returns to the operation procedure shown in  FIG. 6 . Moreover, if determined to be unmatched (Step S 205 ; No), the registration procedure ends and the processing returns to the operation procedure shown in  FIG. 6 . 
     Next, the operation controller  114  determines whether data that present the n-th person are registered (Step S 110 ). If determined to be registered (Step S 110 ; Yes), a second robot operation is executed (Step S 111 ). In detail, the second robot operation is, for example, to move closer to the n-th person, utter the name of the n-th person, say “How do you do?” in greeting as an expression of feeling, and the like. If determined to be not registered (Step S 110 ; No), the variable n is incremented (Step S 107 ) and if determined that the variable n&gt;the number of persons, m, is not satisfied (Step S 108 ; No), the processing returns to the Step S 104 . If determined that the variable n&gt;the number of persons, m, is satisfied (Step S 108 ; Yes), the operation procedure ends. 
     Next, the data transmission procedure that is executed by the server  200  and shown in  FIG. 8  will be described. 
     The account information transmitter  211  of the server  200  determines whether there is an access from the robot  100  via the communicator  220  (Step S 301 ). If determined that there is no access (Step S 301 ; No), the Step S 301  is repeated. If determined that there is an access (Step S 301 ; Yes), information to access that is transmitted by the robot  100  to the account of the registered person is acquired and the account of the registered person is searched for (Step S 302 ). Next, the account information of the registered person is transmitted to the robot  100  (Step S 303 ). 
     Next, acquiring information to access a person who is registered as a friend with the registered person, which is transmitted by the robot  100 , the account of the person who is registered as a friend with the registered person is searched for (Step S 304 ). Next, account information of the person who is registered as a friend is transmitted (Step S 305 ). The account information includes the name and the facial characteristic quantity of the person who is registered as a friend. Next, it is determined whether an end order is made (Step S 306 ). If determined that no end order is made (Step S 306 ; No), the processing returns to the Step S 301 . If determined that an end order is made (Step S 306 ; Yes), the data transmission procedure ends. 
     Next, the procedure that is executed by the robot  100  and the server  200  according to this embodiment will be described based on a specific case with reference to  FIGS. 3, 5, and 9 . In this case, a person A and a person B are registered with the robot  100  as shown in  FIG. 3 . There are three persons where the imager  103  of the robot  100  captures an image. The person A, who appears on the right in an acquired image I shown in  FIG. 9 , is a registered person who is preregistered with the robot  100 . A person T, who appears in the middle, is registered as a friend under the account of the person A in the database  230  of the server  200  as shown in  FIG. 5 , and thus is on close terms with the person A. A person V who appears on the left is not preregistered with the robot  100  and not registered as a friend with the person A or the person B in the database  230  of the server  200 . 
     First, the image acquirer  111  makes the imager  103  start capturing an image (Step S 101 ;  FIG. 6 ) and stores the captured image in the RAM as an acquired image I. Next, the image analyzer  112  detects the number of persons who appear in the acquired image I, m (Step S 102 ;  FIG. 6 ). Here, m=3 is detected. Next, the variable n=1 is set (Step S 103 ;  FIG. 6 ). Next, the image analyzer  112  extracts the facial characteristic quantity of the first person from the acquired image (Step S 104 ;  FIG. 6 ), In this case, it is assumed that the person A who appears on the right in the image is the first person, the person T in the middle is the second person, and the person V who appears on the left in the image is the third person. Next, the image analyzer  112  determines whether the facial characteristic quantity of the first person matches the facial characteristic quantity of a registered person who is preregistered in the user storage  130  (Step S 105 ;  FIG. 6 ). 
     The first person is the person A who appears on the right and therefore it is determined to be matched (Step S 105 ; Yes;  FIG. 6 ). The operation controller  114  executes the first robot operation of moving closer to the person A and uttering the name of the person A (Step S 106 ;  FIG. 6 ). Next, the variable n is incremented (Step S 107 ;  FIG. 6 ). Next, the variable n is 2 and the number of persons, m, is 3; therefore, it is determined that the variable n&gt;the number of persons, m, is not satisfied (Step S 108 ; No;  FIG. 6 ). The processing returns to the Step S 104  to extract the facial characteristic quantity of the second person T. 
     The person T is not preregistered in the user storage  130 ; therefore, the image analyzer  112  determines that the facial characteristic quantity of the person T does not match the facial characteristic quantity of any registered person who is preregistered in the user storage  130  (Step S 105 ; No;  FIG. 6 ) and the registration procedure is implemented (Step S 109 ;  FIG. 6 ). The determiner  113  accesses the accounts of the person A and the person B who are registered persons on the server  200  via the communicator  120  and acquires the account information of the person A and the person B (Step S 202 ;  FIG. 7 ). Next, persons who are registered as a friend with the registered persons are extracted from the account information of the person A and the person B (Step S 203 ;  FIG. 7 ). Here, the persons B, S, and T who are registered as a friend under the account of the person A and the persons A, X, and Y who are registered as a friend under the account of the person B are extracted. Next, the determiner  113  acquires account information from the accounts of persons who are registered as a friend (Step S 204 ;  FIG. 7 ). The information that is acquired here is information that presents the names and the facial characteristic quantities of the persons S, T, X, and Y who are registered as a friend. Next, the determiner  113  determines whether the facial characteristic quantity of the person T who appears in the acquired image and the facial characteristic quantity of any of the persons S, T, X, and Y match (Step S 205 ;  FIG. 7 ). 
     The person T is the same person as the person T who is registered as a friend under the account of the person A and therefore, it is determined to be matched (Step S 205 ; Yes;  FIG. 7 ). The register  115  assumes that the person T is a person who is on close terms with a registered person and automatically registers the name and the facial characteristic quantity of the person T in the user storage  130  (Step S 206 ;  FIG. 7 ). Subsequently, the registration procedure ends and the processing returns to the operation procedure. Next, the operation controller  114  determines that the person T is registered (Step S 110 ; Yes;  FIG. 6 ) and therefore, executes the second robot operation of moving closer to the person T, uttering the name of the person T, saying “How do you do?” in greeting as an expression of feeling, and the like (Step S 110 ;  FIG. 6 ). 
     Next, the variable n is incremented (Step S 107 ;  FIG. 6 ). Here, the variable n is 3 and the number of persons, m, is 3; therefore, it is determined that the variable n&gt;the number of persons, m, is not satisfied (Step S 108 ; No;  FIG. 6 ) and the processing returns to the Step S 104 . The third person is the person V who appears on the left. The person V is not preregistered in the user storage  130 ; therefore, the image analyzer  112  determines that the facial characteristic quantity of the person V does not match the facial characteristic quantity of any registered person who is preregistered in the user storage  130  (Step S 105 ; No;  FIG. 6 ) and the registration procedure is implemented (Step S 109 ;  FIG. 6 ). The determiner  113  acquires account information of the person A and the person B that is stored on the server  200  via the communicator  120  (Step S 202 ;  FIG. 7 ). Next, persons S, T, X, and Y who are registered as a friend with a registered person are extracted from the account information of the person A and the person B (Step S 203 ;  FIG. 7 ). Next, the determiner  113  acquires account information from the accounts of the persons S, T, X, and Y (Step S 204 ;  FIG. 7 ). Next, the determiner  113  determines whether the facial characteristic quantity of the person V who appears in the acquired image and the facial characteristic quantity of any of the persons S, T, X, and Y match (Step S 205 ;  FIG. 7 ). The person V is not among the persons S, T, X, and Y who are registered as a friend under the accounts of the person A and the person B and it is determined to be unmatched (Step S 205 ; No;  FIG. 7 ); then, the registration procedure ends and the processing returns to the operation procedure shown in  FIG. 6 . Next, the operation controller  114  determines that the person V is not registered (Step S 110 ; No;  FIG. 6 ), and the variable n is incremented (Step S 107 ). Here, the variable n is 4 and the number of persons, m, is 3; therefore, it is determined that the variable n&gt;the number of persons, m, is satisfied (Step S 108 ; Yes;  FIG. 6 ), and the operation procedure ends. 
     As described above, according to the robot  100  of this embodiment, even if a person is an unregistered person who is not preregistered in the user storage  130 , the name and the facial characteristic quantity of the person can automatically be registered in the user storage  130  if the person is close to a registered person who is registered in the user storage  130  based on an indicator that indicates the degree of closeness between the registered person and the unregistered person with reference to the database  230  of the server  200 . Therefore, if a single person is registered as the user, the robot  100  can easily register a person who is close to the registered person with reference to the database  230  of the server  200  and it is possible to save on labor and time for user registration. Moreover, the robot  100  can move closer to a person who is newly registered in the user storage  130 , utter the name of the person, say “How do you do?” in greeting as an expression of feeling, and the like; then, the new registration is known. Moreover, upon next startup, if the robot  100  captures an image of the newly registered person, the robot  100  can execute the same response to the response to a preregistered person. 
     Modified Embodiment 
     In the foregoing embodiment, a case is described in which the robot  100  determines whether the characteristic quantity of a face that appears in the acquired image matches the facial characteristic quantity of a registered person who is preregistered in the user storage  130  to identify the person. As long as a person is identified, the robot  100  may identify a person by a method such as voice recognition of an utterance that is collected by a microphone as an utterance collector. 
     In the foregoing embodiment, a case is described in which when the determiner  113  of the robot  100  determines that a person is close to a registered person, the name, the facial characteristic quantity, and the like of the person who is determined to be close are registered in the user storage  130 . When it is determined that a person is close to a registered person, the robot  100  may execute the same operation as the operation to respond to a registered person without registering the name, the facial characteristic quantity, and the like of the person in the user storage  130 . Moreover, the robot  100  may register a person who is determined to be close to the user or a registered person who is preregistered and not register a person who is determined to be close to a person who is automatically newly registered. In this way, it is possible to register only persons who are directly close to the user or a registered person who is preregistered. Moreover, the robot  100  may register a person who is determined to be close to a person who is determined to be close to the user or a registered person who is preregistered and automatically newly registered. In this way, it is possible to register a person who is close to a person who is close to the user or a registered person who is preregistered. In order to determine whether to newly register an unregistered person, it may be possible to set how many persons can intervene between the user or a registered person who is preregistered and the unregistered person on an arbitrary basis. 
     In the foregoing embodiment, a person is determined to be close to a registered person using as an indicator that indicates the degree of closeness whether a person is registered as a friend that is included in the account information of a registered person that is stored on the server  200 . The criterion to determine that a person is close to a registered person is not restricted to a person who is registered as a friend as long as it is based on an indicator that indicates the degree of closeness. For example, the number of times of a registered person having accessed the account of an unregistered person, the number of times of an unregistered person having accessed the account of a registered person, or the like may be used as an indicator that indicates the degree of closeness. As an indicator that indicates the degree of closeness, following from the account of a registered person to the account of an unregistered person, following from the account of an unregistered person to the account of a registered person, mutual following between the accounts of a registered person and an unregistered person, or the like may be used for the determination. 
     In detail, the determiner  113  of the robot  100  may determine that a determination target is a target that has a close relationship as a given relationship to a given target when the number of times of the account of the given target accessed by the determination target in a second device is equal to or higher than a first number of times. 
     Moreover, a determination target may be determined to be a target that has a close relationship as a given relationship to a given target when the determination target has an account on a second device or a third device that is different from the second device and when the number of times of the account of the determination target accessed by the given target is equal to or higher than a second number of times. 
     Moreover, a determination target may be determined to be a target that has a close relationship as a given relationship to a given target when the given target and the determination target have accounts on a second device or a third device that is different from the second device and when the number of times of following from the account of the given target to the account of the determination target or the number of times of following from the account of the determination target to the account of the given target is equal to or higher than a third number of times. 
     Moreover, a determination target may be determined to be a target that has a close relationship as a given relationship to a given target when the given target and the determination target have accounts on a second device or a third device that is different from the second device and when the number of times of mutual following between the account of the given target and the account of the determination target is equal to or higher than a fourth number of times. 
     In the foregoing embodiment, a case is described in which the server  200  comprises an SNS server. The server  200  has only to be a device that stores an indicator that indicates the degree of closeness between an unregistered person and a registered person. For example, a server  200 ′ has account information that is transmitted by multiple robots  100  and the account information includes the names and the facial characteristic quantities of persons who are registered with the robots  100 . It may be possible to assume that persons who are registered in the same account information are close. In detail, the server  200 ′ stores, as shown in  FIG. 10 , account information that is transmitted by a first robot  100 A, account information that is transmitted by a second robot  100 B that is other than the first robot  100 A, and account information that is transmitted by a third robot  100 C that is other than the first robot  100 A and the second robot  100 B. It is assumed that the first robot through the third robot  100 A through  100 C have the same configuration as the robot  100 . Each account stores the names and the facial characteristic quantities of persons who are registered with the first robot through the third robot  100 A through  100 C. In this case, it is assumed that the persons who are registered under each of the accounts of the first robot through the third robot  100 A through  100 C are close. A person A and a person B are registered under the account of the robot  100 A; therefore, the person A and the person B are close. A person S, a person T, and the person A are registered under the account of the robot  100 B; therefore, the person S, the person T, and the person A are close. A person X and a person Y are registered under the account of the robot  100 C; therefore, the person X and the person Y are close. 
     When a person who is not registered with the first robot  100 A appears in an acquired image that is acquired by the first robot  100 A, the first robot  100 A accesses a database  230 ′ of the server  200 ′ and searches for a person who is close to the person A and the person B who are registered with the first robot  100 A. On the server  200 ′, persons who are close to the person A is the person B who is registered under the account of the first robot  100 A and the person S and the person T who are registered under the account of the second robot  100 B. The first robot  100 A acquires the names and the facial characteristic quantities of the person B, the person S, and the person T from the server  200 ′. It is determined through face recognition whether the person who appears in the acquired image that is acquired by the first robot  100 A is the person B, the person S, or the person T. If determined that the person who appears in the acquired image is the person S, the first robot  100 A stores information of the name and the facial characteristic quantity of the person S that are acquired from the server  200 ′. In this way, the first robot  100 A can acquire the name and the facial characteristic quantity of the person S who is registered with the second robot  100 B via the server  200 ′. 
     In the foregoing embodiment, a case is described in which the robot  100  or the first robot through the third robot  100 A through  100 C determine whether a person has a close relationship to a registered person who is registered in the user storage  130  with reference to the database  230  of the server  200  or the database  230 ′ of the server  200 ′. The robot  100  does not need to make reference to the database  230  of the server  200  or the database  230 ′ of the server  200 ′ as long as the robot  100  can determine whether a person is on close terms with a registered person who is registered in the user storage  130 . For example, it may be possible that when the image analyzer  112  of the robot  100  detects in an acquired image a registered person who is registered in the user storage  130  and an unregistered person who is not registered in the user storage  130 , the determiner  113  determines whether the unregistered person and the registered person are on close terms using the positional relationship between the registered person and the unregistered person as an indicator that indicates the degree of closeness. For example, the determiner  113  may measure the distance between the registered person and the unregistered person who appear in the acquired image and use the distance as an indicator that indicates the degree of closeness. In other words, it may be possible to determine that the unregistered person and the registered person are on close terms if the distance is equal to or smaller than a specific distance. Alternatively, it may be possible to measure the time that has elapsed while the distance is equal to or smaller than a specific distance and use the time as an indicator that indicates the closeness. For example, it may be possible to determine that the unregistered person and the registered person are close when, for example, three minutes have elapsed while the distance is equal to or smaller than 1 m. In other words, it may be possible to determine that the unregistered person and the registered person are on close terms when that time is equal to or longer than a specific time. If determined that the unregistered person and the registered person are on close terms, the facial characteristic quantity of the unregistered person is registered in the user storage  130 . 
     In the foregoing embodiment, a case is described in which the robot  100  or the first robot through the third robot  100 A through  100 C identify a person as a target. The target to be determined by the robot  100  or the first robot through the third robot  100 A through  100 C (the determination target that is set forth in the claims) may be animals other than the human such as dogs and cats or objects such as other robots. This also similarly applies to the given target that is set forth in the claims. Moreover, it is determined whether a determination target corresponds to a target that has a close relationship to a given target. However, it may be determined whether to correspond to a target that has some other adequate relationship to a given target, for example a relationship through the same hobby. 
     In the foregoing embodiment, a case is described in which the imager  103  is provided at the position of the nose on the head  101 . The imager  103  may be provided at any position and may be provided at the right eye or the left eye or provided at a position between the right eye and the left eye or at a position on the forehead. Moreover, the imager  103  may be provided at the right eye and the left eye so as to acquire three-dimensional images. 
     In the foregoing embodiment, a case is described in which the robot  100  has a figure that imitates a human. However, the robot  100  is not particularly restricted in figure and may have a figure that imitates an animal including dogs and cats or may have a figure that imitates an animation character or an imaginary creature. 
     The core part that performs the procedures that are executed by the controller  110  or  210  that comprises a CPU, a RAM, a ROM, and the like can be executed using, instead of a dedicated system, a conventional portable information terminal (a smartphone or a tablet personal computer (PC)), a personal computer, or the like. For example, a portable information terminal that executes the foregoing procedures may be configured by saving and distributing the computer program for executing the foregoing operations on a non-transitory computer-readable recording medium (a flexible disk, a compact disc read only memory (CD-ROM), a digital versatile disc read only memory (DVD-ROM), or the like) and installing the computer program on a portable information terminal. Moreover, an information processing device may be configured by saving the computer program on a storage device of a server device on a communication network such as the Internet and allowing a conventional portable information terminal to download the computer program. A controller that executes a robot operation may be separated from a controller that functions as the image acquirer  111 , the image analyzer  112 , and the determiner  113 . 
     Moreover, when the function of the controller  110  or  210  is realized by apportionment of an operating system (OS) and an application program or cooperation of an OS and an application program, only the application program part may be saved on a non-transitory computer-readable recording medium or a storage device. 
     Moreover, the computer program may be superimposed on carrier waves and distributed via a communication network. For example, the computer program may be posted on a bulletin board system (BBS) on a communication network and distributed via the network. Then, the computer program is started and executed in the same manner as other application programs under the control of an OS so as to execute the foregoing procedures. 
     The foregoing describes some example embodiments for explanatory purposes. Although the foregoing discussion has presented specific embodiments, persons skilled in the art will recognize that changes may be made in form and detail without departing from the broader spirit and scope of the invention. Accordingly, the specification and drawings are to be regarded in an illustrative rather than a restrictive sense. This detailed description, therefore, is not to be taken in a limiting sense, and the scope of the invention is defined only by the included claims, along with the full range of equivalents to which such claims are entitled.