JP2011155385A - Electronic device, content transmission method, and program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To appropriately determine and present other users to share contents without making a user perform troublesome work. <P>SOLUTION: A PC 100 extracts a face image from digital photo images inside a storage section 108, generates a registered person list for the respective face images, also generates a human relation meta DB, calculates a share candidate point for a person in the registered person list on the basis of the temporal and distance closeness of the selected photo and the other photos, relation strength in the human relation meta DB and a past photo share history for the photo selected from a photo list by a user, displays information related to a person of whom the share candidate point is equal to or higher than a first value as a share candidate, and displays the person of whom the share candidate point is equal to or higher than the second value by setting the check box to be ON. <P>COPYRIGHT: (C)2011,JPO&INPIT

Description

  The present invention relates to an electronic device capable of transmitting content such as a digital photograph image or metadata such as a URL thereof to another device and allowing the user of the other device to share the content, and the content in the electronic device The present invention relates to a transmission method and a program.

  Conventionally, there is a technique for sharing content of a certain user with other users.

  For example, in the following Patent Document 1, personal identification information such as a face image or voiceprint pattern of a specific user is registered in advance with a user ID together with a user ID. The member is associated with the group ID and registered in the server, and information such as image data output from a sensor device such as a camera arranged at a predetermined position is collected by the server together with the user ID. A system is disclosed in which, when corresponding information is detected, the server distributes the information to users belonging to the group ID associated with the user ID corresponding to the identification information.

JP 2008-198135 A

  However, in the technique described in Patent Document 1, in order to share a user's content with other users, not only the user's device but also a large-scale system using a server is required. In addition, this system requires a complicated operation for registering other users as groups in the server in advance. Furthermore, in this system, the distribution destination of information is managed by a group registered in the server in advance, so that it is possible to respond immediately when there is a situation where it is desired to share information with a user who does not belong to the group. Can not.

  In view of the circumstances as described above, an object of the present invention is to provide an electronic device and content transmission capable of appropriately determining and presenting other users who should share content without causing the user to perform complicated operations. It is to provide a method and a program.

  In order to achieve the above object, an electronic device according to an embodiment of the present invention includes a storage unit, a communication unit, an operation input unit, a control unit, and an output unit. The storage unit stores a plurality of pieces of content including identification information for identifying a person, and person information regarding the plurality of persons including at least the identification information and a person name corresponding to the identification information. The communication unit transmits at least one of the plurality of contents to an apparatus related to at least one person corresponding to the person information. Alternatively, the communication unit transmits the content to a storage device on the network, and transmits location information of the content on the storage device to a device related to the person. The operation input unit receives an input of a user operation for selecting at least one content from the plurality of contents. The control unit recognizes the identification information included in other content having a predetermined relationship with the selected content, and is identified by the recognized identification information according to the strength of the predetermined relationship. The points of each person included in the information are calculated. The output unit is configured to transmit the personal information of a person having the point equal to or greater than a predetermined threshold to the selected device or the location information of the selected content to the device related to the person. Output for display as a destination candidate.

  As a result, the electronic device can automatically extract a transmission destination (share) destination candidate selected by the user based on the points calculated for each person and present it to the user. Therefore, the user can easily share the content with others without worrying about who should share each content. Here, the electronic devices are all capable of storing content such as PCs, digital still cameras, digital video cameras, mobile phones, portable AV (Audio / Visual) devices, recording / playback devices, television devices, digital voice recorders, and the like. It is an electronic device. The content is still image data (digital photograph image data), moving image data, audio data, and the like. The network may be any network such as a LAN or the Internet. The storage device is, for example, a server, and further an online album on the server. The location information is, for example, a URL or a file path.

  The control unit may display a check box for selecting whether or not the selected content can be transmitted via the operation input unit together with the person information as the transmission destination candidate. In this case, the control unit may display the check box displayed together with the person information of the person having the point equal to or larger than the second value larger than the first value in a state where the transmission is permitted. Good.

  As a result, the electronic device can display a person having a point greater than or equal to the second value among the transmission destination candidates with the check box turned on, so that the user can perform the transmission destination candidate without performing any operation. Of these, the person who has a particularly high point can be set so that the content is automatically transmitted.

  The said memory | storage part may memorize | store the human relationship information which shows the intensity | strength of the relationship between the persons contained in the said personal information. In this case, the control unit recognizes the identification information included in the selected content, and based on the human relationship information, the relationship between the person identified by the identification information and the person included in the personal information You may calculate the said point according to the intensity | strength of.

  As a result, the electronic device can automatically extract the transmission destination candidates for the content and present them to the user in accordance with the strength of the human relationship of each person included in the content.

  The person relation information may include direction information indicating an interest that each person has toward other persons. In this case, the control unit may calculate the point according to the strength of the relationship and the direction information.

  As a result, the electronic device wants the person included in the content to share the content, for example, based on the direction information regarding the mutual interest between the person identified by the identification information included in the content and the other person Another person or a person who wants content including a specific person can be extracted as a transmission destination candidate and presented to the user.

  The content may be a digital photographic image having shooting time information, and the identification information may be a face image of the person. In this case, the control unit recognizes the face image included in another digital photo image having the second shooting time information within a predetermined time from the first shooting time information included in the selected digital photo image, and The point may be calculated according to a difference between the first shooting time information and the second shooting time information.

  As a result, the electronic device can add a person who appears in another photographic image whose shooting time is close to that of the photographic image, even if it is not shown in the selected photographic image, to the transmission destination candidate. Here, it is highly possible that such a person was present together with the person shown in the selected photo image because the person shown in the other photo image whose shooting time is near is added to the destination candidate. This is because there is a high possibility of wanting to share a photographic image.

  Alternatively, the control unit recognizes the face image included in another digital photo image having the second shooting position information within a predetermined distance from the first shooting position information of the selected digital photo image. The point may be calculated according to a difference between the first shooting position information and the second shooting position information.

  As a result, the electronic device can add a person who is not shown in the selected photographic image but is shown in another photographic image whose shooting position is close to that photographic image to the transmission destination candidates. Here, it is highly possible that such a person was present together with the person shown in the selected photographic image because the person shown in another photographic image with a close shooting position is added to the destination candidate. This is because there is a high possibility of wanting to share a photographic image.

  The said memory | storage part may memorize | store the transmission history information regarding the content transmitted to the apparatus relevant to the said person based on the display of the said transmission destination candidate. In this case, the control unit compares the first identification information included in the transmitted content with the second identification information included in the selected content based on the transmission history information, and The degree of matching between one identification information and the second identification information may be calculated, and the point of the person related to the content destination device may be calculated according to the degree of matching.

  As a result, when the degree of matching between the identification information included in the previously transmitted content and the identification information included in the selected content is high, the electronic device selects the past transmission destination of the content as the selected content. Can be displayed as transmission destination candidates. In other words, for example, when many of the subjects of a photo sent to a specific person share the same photo as the photo that is going to be sent this time, the electronic device should send that photo to that particular person again. Can be automatically determined and presented to the user.

  The person relation information may include direction information indicating an interest that each person has toward other persons. In this case, the control unit may calculate the point according to the strength of the relationship and the direction information.

  As a result, the electronic device wants the person included in the content to share the content, for example, based on the direction information regarding the mutual interest between the person identified by the identification information included in the content and the other person Another person or a person who wants content including a specific person can be extracted as a transmission destination candidate and presented to the user.

  The control unit recognizes the identification information included in the content every time the content is stored in the storage unit, generates the personal information related to the person identified by the identification information, and stores the personal information in the storage unit May be.

  Thereby, whenever a user takes in contents to the electronic device, the electronic device can generate new person information for the person included in the electronic device, and as a result, the number of transmission destination candidates can be increased.

  The control unit may recognize the identification information included in the content every time the content is stored in the storage unit, and store the identification information in the storage unit as temporary person information. The control unit may update the temporary person information as the personal information when the operation input unit inputs a person name for the temporary person information. Further, the control unit does not input the person name within a predetermined period after storing the temporary person information, and the content stored in the storage unit does not include the identification information as the temporary person information. In this case, the temporary person information may be deleted.

  As a result, the electronic device temporarily stores all the identification information included in the content as temporary person information, and deletes temporary person information that is not updated as personal information within a predetermined period of time, so that the user can happen to the content without being aware of it. It is possible to prevent the person information relating to the included person from being stored in vain.

  The control unit may display a first mark together with the person information when the identification information corresponding to the person information displayed as the transmission destination candidate is included in the selected content. In addition, when the identification information is not included in the selected content, the control unit includes a second mark different from the first mark and the person information as the transmission destination candidate together with the person information. Information indicating the reason for the display may be displayed.

  Thereby, the electronic device can make the user easily grasp the reason why the transmission destination candidate is displayed by using the first and second marks, and can be used as a determination material for determining whether or not to use the transmission destination candidate.

  The control unit may transmit the selected content to a device related to the person when the person has a point greater than or equal to a third value greater than the first value. In addition, when the person has a point less than the third value, the control unit transmits the selected content to a storage device on the network, and stores the location information of the content on the storage device. You may transmit to the apparatus relevant to the said person.

  Accordingly, the electronic device transmits the content itself according to each person's point, that is, according to the strength of the relationship with the selected content, or transmits the location information (URL) without transmitting the content itself. You can decide what to do.

  A content transmission method according to another aspect of the present invention stores a plurality of contents including identification information for identifying a person, and personal information relating to the plurality of persons including at least the identification information and a person name corresponding to the identification information. Including doing. An input of a user operation for selecting at least one content from the plurality of contents is accepted. The identification information included in the other content having a predetermined relationship with the selected content is recognized, and each of the individual information included in the person information is identified by the recognized identification information according to the strength of the predetermined relationship. A person's points are calculated. The person information of the person who has the point equal to or greater than a predetermined threshold is displayed as a transmission destination candidate for transmitting the selected content or the location information of the content to the device related to the person. The selected content is transmitted to a device related to the person corresponding to the person information as the displayed transmission destination candidate. Alternatively, the selected content is transmitted to a storage device on the network, and the location information of the content on the storage device is transmitted to a device related to the corresponding person.

  A program according to still another aspect of the present invention causes an electronic device to execute a storage step, an operation input step, a calculation step, a display step, and a transmission step. In the storing step, a plurality of contents including identification information for identifying a person, and personal information regarding the plurality of persons including at least the identification information and a person name corresponding to the identification information are stored. In the operation input step, an input of a user operation for selecting at least one content from the plurality of contents is received. In the calculation step, the identification information included in other content having a predetermined relationship with the selected content is recognized, and the person is identified by the recognized identification information according to the strength of the predetermined relationship. Points of each person included in the information are calculated. In the display step, the person information of the person having the point equal to or greater than a predetermined threshold is used as a transmission destination candidate for transmitting the selected content or the location information of the content to the device related to the person. Is displayed. In the transmission step, the selected content is transmitted to a device related to a person corresponding to the person information as the displayed transmission destination candidate. Alternatively, the selected content is transmitted to a storage device on the network, and the location information of the content on the storage device is transmitted to a device related to the corresponding person.

  As described above, according to the present invention, other users who should share the content are appropriately judged and presented without causing the user to perform complicated work, and the content is transmitted to the other users. Can do.

It is the figure which showed the hardware constitutions of PC concerning one Embodiment of this invention. It is the flowchart which showed the flow of the process of PC when share software is installed in PC concerning one Embodiment of this invention. It is the figure which showed the example of the registration screen of the registration person list in one Embodiment of this invention. It is a figure for demonstrating human relationship metaDB in one Embodiment of this invention. It is the flowchart which showed the flow of the process of PC when a new photograph is added to the memory | storage part of PC concerning one Embodiment of this invention. It is the figure which showed the example of the screen for PC for a user to confirm the necessity of registration of the information corresponding to new face image information in one Embodiment of this invention. It is the flowchart which showed the flow of the share execution process by PC concerning one Embodiment of this invention. It is the figure which showed the example of a display of the share candidate list screen in one Embodiment of this invention. It is the flowchart which showed the flow of the share process by method (1) of PC which concerns on one Embodiment of this invention. It is the figure which showed the photography condition of each photograph in the share process by method (1) of PC which concerns on one Embodiment of this invention. It is the figure which showed a mode that the user selected the photograph which wants to share from a photograph list in the share process by method (1) of PC concerning one Embodiment of this invention. It is a figure for demonstrating the photograph close | similar in time in the share process by the method (1) of PC concerning one Embodiment of this invention. It is a figure for demonstrating the photograph close | similar in distance in the share process by the method (1) of PC concerning one Embodiment of this invention. It is a figure for demonstrating the process which extracts a share candidate about one photograph in the share process by method (1) of PC which concerns on one Embodiment of this invention about the selected photograph. It is a figure for demonstrating the process which extracts a share candidate about another photograph among the selected photographs in the share process by method (1) of PC which concerns on one Embodiment of this invention. It is a figure for demonstrating the summation process of the extraction result of the share candidate about all the selected photographs in the share process by method (1) of PC which concerns on one Embodiment of this invention. It is the figure which showed the example of the share candidate list screen displayed in the share process by method (1) of PC which concerns on one Embodiment of this invention. It is the flowchart which showed the flow of the share process using a classification of a person among the share processes by method (2) of PC which concerns on one Embodiment of this invention. It is the figure which showed a mode that the user selected the photograph which wants to share from a photograph list in the share process by the method (2) of PC which concerns on one Embodiment of this invention. It is the figure which showed the classification figure of the person who is reflected in the photograph which a user desires to share in the share process by the method (2) of PC concerning one Embodiment of this invention. It is the figure which showed the example of the extraction result of the share candidate in the process which uses a classification diagram among the share processes by the method (2) of the PC concerning one Embodiment of this invention, and a share candidate list screen. Of the sharing process by the method (2) of the PC according to the embodiment of the present invention, a process of sharing a photograph to a person who is assumed to want a photograph of the person in the photograph using the relationship strength diagram It is the flowchart which showed the flow of. FIG. 5 shows a relationship strength diagram of one of the persons in a photograph that the user wants to share in the processing using the relationship strength diagram in the share processing by the method (2) of the PC according to an embodiment of the present invention. It is a figure. The figure which showed the relationship intensity | strength figure of each person reflected in the photograph which a user desires to share in the process which uses a relationship intensity | strength figure among the share processes by the method (2) of PC concerning one Embodiment of this invention. It is. It is the figure which showed the example of the extraction result of the share candidate in the process using a relationship strength figure among the share processes by the method (2) of the PC concerning one Embodiment of this invention, and a share candidate list screen. Of the share processing by the method (2) of the PC according to the embodiment of the present invention, using the relationship strength diagram, the person who is in the photograph is supposed to give the photograph to the person who is supposed to give the photograph. It is the flowchart which showed the flow of the process to share. The figure which showed the relationship intensity | strength figure of each person reflected in the photograph which a user desires to share in the process which uses a relationship intensity | strength figure among the share processes by the method (2) of PC concerning one Embodiment of this invention. It is. It is the figure which showed the example of the extraction result of the share candidate in the process using a relationship strength figure among the share processes by the method (2) of the PC concerning one Embodiment of this invention, and a share candidate list screen. It is the flowchart which showed the flow of the share process by method (3) of PC which concerns on one Embodiment of this invention. 30 is a flowchart showing a flow of a match degree calculation process in the flowchart of FIG. 29. It is the figure which showed the share history in the share process by the method (3) of PC concerning one Embodiment of this invention. It is the figure which showed the calculation conditions of the share candidate point in the share process by method (3) of PC which concerns on one Embodiment of this invention. It is the figure which showed the extraction result of the share candidate in the share process by method (3) of PC which concerns on one Embodiment of this invention. It is the figure which showed the example of the share candidate list screen in the share process by method (3) of PC which concerns on one Embodiment of this invention. It is the flowchart which showed the flow of the deletion process of the data from the registered person list of PC concerning one Embodiment of this invention. FIG. 10 is a diagram showing an example of a user interface for setting an ignore flag to ON in another embodiment of the present invention.

  Hereinafter, embodiments of the present invention will be described with reference to the drawings.

[PC hardware configuration]
FIG. 1 is a diagram showing a hardware configuration of a PC according to an embodiment of the present invention. As shown in the figure, the PC 100 includes a central processing unit (CPU) 101, a read only memory (ROM) 102, a random access memory (RAM) 103, an input / output interface 105, and a bus 104 that connects these components to each other.

  The CPU 101 appropriately accesses the RAM 103 or the like as necessary, and performs overall control of each block of the PC 100 while performing various arithmetic processes. The ROM 102 is a nonvolatile memory in which firmware such as an OS to be executed by the CPU 101, programs, and various parameters is fixedly stored. The RAM 103 is used as a work area for the CPU 101 and temporarily holds the OS, various programs being executed, and various data being processed.

  A display unit 106, an input unit 107, a storage unit 108, a communication unit 109, a drive unit 110, and the like are connected to the input / output interface 105.

  The display unit 106 is a display device using, for example, liquid crystal, EL (Electro-Luminescence), CRT (Cathode Ray Tube), or the like. The display unit 106 may be built in the PC 100 or may be externally connected to the PC 100.

  The input unit 107 is, for example, a pointing device, a keyboard, a touch panel, or other operation device. When the input unit 107 includes a touch panel, the touch panel can be integrated with the display unit 106.

  The storage unit 108 is a non-volatile memory such as an HDD (Hard Disk Drive), a flash memory, or other solid-state memory. The storage unit 108 stores data such as a digital photo image, registered person list, and a human relationship meta database (Database) described later, and software for sharing the digital photo image with other users (hereinafter referred to as share software). ) And the like are stored.

  The drive unit 110 is a device capable of driving a removable recording medium 111 such as an optical recording medium, a floppy (registered trademark) disk, a magnetic recording tape, and a flash memory. On the other hand, the storage unit 108 is often used as a device mounted in advance on the PC 100, which mainly drives a non-removable recording medium.

  The communication unit 109 is a NIC (Network Interface Card) for communicating with other devices that can be connected to a LAN (Local Area Network), a WAN (Wide Area Network), or the like. The communication unit 109 may communicate using either wired or wireless communication. As will be described later, the PC 100 can share the digital photograph image with another person by transmitting the digital photograph image to another apparatus using the communication unit 109.

[PC operation]
Next, the operation (digital photographic image sharing process) of the PC 100 configured as described above will be described. In the following description, the CPU 101 of the PC 100 will be described as the main operating subject, but this operation is performed in cooperation with other hardware and software operating under the control of the CPU 101. In particular, after the following share software is installed, the operation is executed in cooperation with the CPU 101 and the share software.

(Share software installation)
First, the operation of the PC 100 when the share software is installed in the PC 100 will be described. FIG. 2 is a flowchart showing a process flow of the PC 100 in this case.

  As shown in the figure, the CPU 101 first installs the share software based on, for example, a user operation on a predetermined installation screen (step 21). Subsequently, the CPU 101 searches for a digital photograph image (hereinafter also simply referred to as a photograph) stored in the storage unit 108 or the recording medium 111 at that time (step 22).

  Subsequently, the CPU 101 performs face recognition processing on the retrieved photograph and extracts face image information (step 23).

  Here, as the face recognition processing, a conventional technique can be employed. That is, in the conventional face recognition system, a face extraction process for extracting a face pattern from a captured image based on face feature information and a comparison between the extracted face pattern and a registered face image are performed, and the face is a specific person. A face identification process for identifying this is executed. For face extraction processing and face identification processing, for example, “Gabor Filtering” that extracts facial image feature quantities by using multiple filters with different directional selectivity and frequency components is applied. Can do. In the face identification process, the extracted face pattern is compared with the registered face image. For the registered face image, a Gabor jet for each feature amount extraction position is calculated in advance. Then, the similarity between the Gabor jet of the input face and the Gabor jet of the registered face at the same feature amount extraction position is calculated, and a similarity vector that is a set of similarities at a plurality of feature amount extraction positions is obtained. Subsequently, class determination by a support vector machine (SVM) is performed, and an input face image and a registered face image are recognized. The support vector machine calculates the distance from the boundary surface (surface at the position where the value is 0) that determines the value of the boundary surface of the similarity vector as, for example, +1 or −1, and the intra-personal class or It is determined which of the extra-personal class it belongs to. If there is no similarity vector determined to belong to the intra-personal class, it is determined that an unregistered person's face has been input. Also, if one support vector machine learns (that is, registers) many face images, whether the newly input face image matches the registered (learned) face image (intra- whether it belongs to personal class) or does not match (whether it belongs to extra-personal class). Support vector machines are recognized in the industry as having the highest level of learning generalization in the field of pattern recognition.

  Subsequently, the CPU 101 reflects the face image information in the human relationship meta DB (step 24). The human relationship meta DB will be described later.

  Subsequently, the CPU 101 determines whether or not the extracted face image information is new (step 25). If it is determined to be new (Yes), the CPU 101 adds the face image information to the registered person list (step 26). When determining that it is not new, that is, already registered (No), the CPU 101 adds the frequency of the face image information in the registered person list (step 27).

  Here, the registered person list will be described. FIG. 3 is a diagram showing an example of a registration screen for the registered person list.

  As shown in the figure, the registration screen displays, for each registered user (face image), a face image information column 31, a name column 32, an email address column 33, a frequent occurrence column 34, an ignore flag column 35, and a last update date / time column. There are 36 display fields. A user who has entered all these items is displayed as a registration completion group 37, and a user who has an uninput item is displayed as a registration incomplete group 38.

  The face image information column 31 is a column for indicating a face image extracted from the photograph. A plurality of images can be registered as face image information. The CPU 101 displays the face images determined to be the same person by the face recognition process in the same face image information column 31. If the user determines that the plurality of face images displayed in the same face image information column 31 are the face images of another person, the user can separate the face image information and re-register as another user. The user can also select data to be used as a representative image (thumbnail) from among a plurality of face images of the same person on the registration screen.

  The name column 32 and the email address column 33 are columns for displaying the name and email address entered by the user on the registration screen. As will be described later, the e-mail address is a transmission destination when the photo is shared with other users. When the user inputs the name and email address, the data displayed in the unregistered group 38 is transferred to the registered group 37.

  The frequent appearance column 34 indicates the degree to which the user is recommended (completed) for user registration, and the higher the frequent occurrence degree, the more the face of the person is shown in the photograph stored in the storage unit 108 or the like. Show.

  The ignore flag column 35 is a column indicating whether or not the user has explicitly selected to ignore (do not execute photo sharing) for the person (face image). When the ignore flag is set to ON (1), the CPU 101 does not prompt the user for user registration even if it is shown in a photograph, and does not add it to a share candidate described later.

  The last update date / time column 36 is a column indicating the date / time when the information item of each column related to the person was last updated. The last update date / time column 36 is provided to deal with processing of a person who happens to pass through a photograph. That is, as will be described later, a person who has not appeared in a photo for a certain period of time and for whom no information about a name or email address has been input by the user is automatically deleted from the registered person list.

  Returning to FIG. 2, the CPU 101 displays a screen for confirming whether or not to register face information and contact information (email address) on the registration screen, and waits for an instruction from the user (step 28). If there is a registration instruction on the confirmation screen (Yes), the CPU 101 displays the registration screen, registers information input by the user on the registration screen in the registered person list (step 29), and Completion of registration will be displayed together with the completion of installation of the share software.

  Next, the human relationship meta DB will be described. FIG. 4 is a diagram for explaining the human relationship meta DB.

  As shown in FIG. 4A, the human relationship meta DB stores data indicating the strength of the relationship between the persons registered in the registered person list, and includes a name 41, face image information 42, attributes. -It has each information item of classification 43 and relation strength 44. The attribute / classification 43 indicates a group or category to which each person belongs, such as date of birth, work place, educational background, hobby, special skill, circle, and the like.

  In the human relationship meta DB, the strengths of mutual relationships are added if they appear in the same photograph. For example, in FIG. 5A, when Tom and Jim appear in the same picture, 1 is added to the strength of the relationship from Tom to Jim and the strength of the relationship from Jim to Tom. Furthermore, the strength of these relationships is updated in accordance with execution of a photo sharing process described later.

  FIG. 5B schematically shows the strength of the relationship between each person based on the human relationship meta DB. As shown in the figure, for example, Tom has a relatively strong relationship (interest) with Jack, and Mary has a relatively strong relationship (interest) with Tom.

(Add photo)
Next, the operation of the PC 100 when a new photo is added to the storage unit 108 of the PC 100 will be described. FIG. 5 is a flowchart showing a process flow of the PC 100 in this case.

  As shown in the figure, first, when a photograph is added to the storage unit 108 (step 51), the CPU 101 extracts face image information from the photograph (step 52), and extracts the extracted face image information from the human relationship. Reflected in the meta DB (step 53).

  Subsequently, the CPU 101 determines whether or not the extracted face image information is new (step 54). If it is determined to be new (Yes), the CPU 101 adds the face image information to the registered person list (step 55).

  When it is determined that the extracted face image information is not new (No), the CPU 101 determines whether or not the ignore flag is not set for the person corresponding to the face image information on the registered person list. Judgment is made (step 56). If it is determined that the ignore flag is set (No), registration is not necessary, and the CPU 101 ends the process. If it is determined that the ignore flag is not set (Yes), the CPU 101 adds the frequency of the registered person list as in the case of FIG.

  Subsequently, the CPU 101 determines whether a name and an e-mail address have been registered on the registered person list for the person corresponding to the extracted face image information (step 58). If it has already been registered (Yes), there is no item that needs to be registered any more, so the CPU 101 ends the process.

  When the name and the mail address are not registered (No), the CPU 101 determines whether or not the frequency of occurrence is a predetermined point or more (step 59). When it is determined that the frequency of occurrence is equal to or less than a predetermined value (No), the CPU 101 ends the process because information about the person is unnecessary.

  When the frequency of occurrence is equal to or higher than a predetermined point (Yes), the CPU 101 confirms with the user whether or not to register the extracted face image information and the contact information of the person corresponding thereto in the registered person list. A screen (registration confirmation screen) is displayed (step 60).

  FIG. 6 is a diagram showing an example of the registration confirmation screen. As shown in the figure, the registration confirmation screen is popped up at the corner of the display unit 106, for example. In the registration confirmation screen, a “Yes” button 11 for instructing registration, a “Later” button 12 for instructing registration later, and the face image information will not be registered in the future. A “ignore from now on” button 13 is displayed to instruct this.

  Returning to FIG. 5, when the user presses the “Yes” button 11 via the input unit 107, the CPU 101 displays the registration screen and registers the name and mail address input by the user in the registered person list ( Step 61).

  When the “later” button 12 is pressed or when a predetermined time has elapsed since the registration confirmation screen is displayed, the CPU 101 ends the process. When the “ignore in the future” button 13 is pressed, the CPU 101 sets the ignore flag to ON on the registered person list and ends the process.

(Share execution processing)
Next, a process for sharing a photograph in the storage unit 108 with another user based on the registered person list will be described. FIG. 7 is a flowchart showing the flow of the share processing by the PC 100.

  In this embodiment, the PC 100 gives points to the person in the registered person list by the following three methods, and automatically identifies and presents photo share candidates according to the height of the points. To do.

Method (1): Points are allocated to a person who is in a photograph whose shooting time or shooting place is close to the photograph that the user wants to share according to the closeness.

  As a use case of the method (1), for example, a user wants to travel with five friends and take a lot of photos and share a favorite photo with a friend who has taken a photo together. If only two of these friends are shown, it is possible to automatically present all five as share candidates.

Method (2): Points are allocated from the human relationship meta DB to a person who has a strong relationship with a person shown in a photograph that the user wants to share according to the strength of the relationship.

  As a use case of the method (2), for example, a user attends a student alumni association and takes a lot of photos, and she wants to share a favorite photo with a good fellow alumni. If there is a person you don't want to see, or you want to share, but there is a person who is absent from the alumni association and is not in the picture at all, regardless of whether it is in the picture or not, it will automatically share all alumni with good friends It is possible to remove those who do not want to share from the share candidates.

・ Method (3): From the past share history, find the person who frequently shares other pictures that the person in the picture the user wants to share, and allocate points according to the frequency To do.

  As a use case of the method (3), for example, when a user takes many pictures of a child at a children's athletic meet and wants to share a favorite picture with the parents, but the parents are not reflected in the picture, It is possible to automatically present parents as share candidates.

  In either method, the persons are listed in descending order of points and displayed as share candidates. On the share candidate, a check box for setting a transmission destination is automatically set to ON for a person whose points are higher than a certain value.

  Returning to FIG. 7, first, the CPU 101 accepts an operation for the user to select a photo that the user wants to share on, for example, a photo list screen stored in the storage unit 108 (step 71).

  Subsequently, the CPU 101 calculates share candidate points by the above methods (1) to (3) (steps 72 to 74). Then, the CPU 101 weights the points calculated by the respective methods, and adds up the share candidate points after weighting (step 75). Details of the share candidate point calculation processing by these methods (1) to (3) will be described later.

  Here, the weighting method will be described. The weighting is executed, for example, by the CPU 101 dynamically changing the weighting value according to the following rules as the user uses the share software after installing the share software.

  That is, as the number of photographs in the storage unit 108 increases, the result by the method (1) is emphasized, and as the number of registered face image information in the registered person list increases, the result by the method (2) is emphasized. As the past share history increases, the result by the method (3) is emphasized.

  Furthermore, the more photographs that are close in time or distance to the photos that the user is trying to share, the more important the result of the method (1) is, and the human relationship metadata of the person appearing in the photos that are to be shared The greater the number, the more important the result by the method (2), and the more frequently the other photos in which the person appearing in the photo to be shared is shared, the more the result by the method (3) is emphasized. The

  Subsequently, the CPU 101 rearranges information regarding the person who is a share candidate on the registered person list in the order of the combined share candidate points (step 76).

  Subsequently, the CPU 101 determines whether or not the ignore flag is OFF for the person who is the share candidate (step 77). If the ignore flag is OFF (Yes), information on the share candidate person is generated in the “share candidate column” on the share candidate list screen (described later) (step 78). If the ignore flag is ON (No), information on the person who is the share candidate is generated in the “excluded person column” (step 79).

  Subsequently, the CPU 101 displays a share check box on the share candidate list screen (step 80).

  Subsequently, the CPU 101 determines whether or not the share candidate point of the person who is the share candidate generated in the “share candidate field” is equal to or greater than a predetermined value (step 81). Sets the share check box to ON (step 82).

  Then, the CPU 101 displays the share candidate list screen completed by the above processing on the display unit 106 (step 83).

  FIG. 8 is a diagram showing a display example of the share candidate list screen. As shown in the figure, the share candidate list screen 90 displays a share execution button 91 and a destination addition button 92 in addition to the share candidate field 93 and the excluder field 98.

  In the share candidate column 93, as described above, the person names and e-mail addresses of the persons are listed in order from the highest share candidate point. In addition to or instead of the person name, face image information of the person may be displayed. Further, as described above, the check box 94 in the share candidate column 93 of share candidates having share candidate points equal to or greater than a predetermined value is set to ON (persons B, D, and C). For a person who is a share candidate but whose email address is not registered, a message for confirming whether or not to register the email address is displayed (person E).

  A camera mark 95 is displayed in the vicinity of the share candidate field 93 of the person who is in the photograph selected as the share candidate among the persons who are the share candidates. For a person who has not been shown in the picture but has been added to the share candidate field 93, an additional mark 96 and a message box 97 indicating the reason are displayed in the vicinity of the share candidate field 93.

  The excluder field 98 functions as a button, and when the user clicks the excluder field 98, information regarding a person who has a high share candidate point but was not displayed in the share candidate field 93 due to the setting of the ignore flag is displayed. The

  Returning to FIG. 7, when the share execution button 91 is pressed on the share candidate list screen 90, the CPU 101 selects the type of data to be shared in accordance with the share candidate points (step 85). The CPU 101 stores, for example, the photo itself if the share candidate point is equal to or greater than the first value, the thumbnail if the share candidate point is greater than or equal to the second value and less than the first value, and the photo data if less than the second value. Each URL or path is selected as data to be shared. The predetermined value as a condition for turning on the check box 94 may be the same value as the first value or the second value, or may be determined independently of these values. The thumbnail may be generated when a photo is added to the storage unit 108, or may be generated when sharing is described later. The URL or path is a URL or path of a photo stored as an online album on a server (storage device) on the network, for example. The CPU 101 may upload a photo on the online album at the same time as sharing, which will be described later, or in advance based on a user operation.

  Subsequently, the CPU 101 generates a predetermined comment as necessary (step 87). For example, the CPU 101 generates a comment for notifying a person who has been added to the share candidate column 93 but is not displayed in the photograph as a display target of the additional mark 96. Examples of the comment include “Shared by share candidate automatic extraction function”. This is because a person who is not shown in the photograph may not expect the photograph or related data to be sent to himself / herself, so as to eliminate the person's confusion and distrust. In addition, the comment may be generated for a person who is shown in a photograph but has a relatively weak relationship with the user of the PC 100. Further, among the persons added to the share candidate column 93, the comment may be generated for a person whose share candidate points are less than a certain value (for example, the second value). That is, the CPU 101 may determine whether or not the share candidate point is less than a certain value, instead of determining whether or not the photograph is reflected in the photograph and whether or not the relationship with the user of the PC 100 is weak. As will be described later, the share candidate points for a person who is not shown in the photograph or a person whose relationship with the user of the PC 100 is relatively light are generally low.

  Then, the CPU 101 executes sharing (sends data such as photos) to the mail address of the person whose share check box 94 is set to ON (step 88). At this time, if the comment is generated, the comment is also transmitted together with data such as a photograph. As described above, when the data to be shared is a URL or path, the URL or path is transmitted to the e-mail address at the timing of the execution of the share, and the photo itself is uploaded to a server on the network. Also good.

  Further, when the CPU 101 executes the share, it reflects it in the human relationship meta DB (step 89). In other words, the CPU 101 adds the relationship strength from the person shown in the shared photo to the person who is the share destination in the human relation meta DB.

  When the ON / OFF switching operation of the share check box 94 is input in step 84, the CPU 101 switches ON / OFF of the share check box 94 (step 86) and waits for the subsequent operation input (step 86). 84).

  Next, details of each process of the above methods (1) to (3) will be described. In the following description, it is assumed that the person B who is the user of the PC 100 shares some of the photos stored in the storage unit 108 with other persons. The photo includes a picture taken by the person B himself and a picture taken by the person B from another person.

(Share processing by method (1))
First, details of the share processing by the method (1) will be described. FIG. 9 is a flowchart showing the flow of share processing by the method (1). As shown in the figure, first, the CPU 101 obtains information such as a photographing time and a photographing place regarding the photograph selected by the user (step 121).

  FIG. 10 is a diagram showing the shooting situation of each photo, and FIG. 11 is a diagram showing a state in which the user selects a photo that the user wants to share from the photo list. As shown in FIG. 12, the user selects a photograph that the user desires to share by clicking on the photograph, for example. In the figure, photos P2 and P7 are selected, and a check box 131 indicating selection is displayed on each photo.

  As shown in FIG. 11, among the photos P1 to P8 on the photo list, the selected photos P2 and P7 include people B, C, D, E, and G. , Not in the same place.

  Returning to FIG. 9, subsequently, the CPU 101 determines whether or not there is a photograph with a difference in photographing time within a predetermined range (for example, within 30 minutes) for the selected photograph (step 122). When there is a photograph whose photographing time difference is within a predetermined range (Yes), the CPU 101 acquires information about the person shown in the photograph by face recognition processing (step 123). Then, the CPU 101 adds share candidate points for the person according to the difference in the shooting time (step 124).

  FIG. 12 is a diagram for explaining a difference in photographing time of each photograph. As shown in the figure, among the selected photographs P2 and P7, for the photograph P2, there is a photograph P1 whose difference in photographing time is within 10 minutes, and a photograph P3 whose difference in photographing time is within 30 minutes. And P4. On the other hand, for the photo P7, there is no other photo having a difference in shooting time within 30. Therefore, the CPU 101 acquires information about the person shown in the photos P1, P3, and P4, and adds share candidate points according to the difference in the shooting time.

  Subsequently, the CPU 101 determines whether or not there is a photograph with a difference in distance between shooting locations within a predetermined range (for example, within 500 m) for the selected photograph (step 125). If there is a photograph in which the difference in distance between the shooting locations is within a predetermined range (Yes), the CPU 101 acquires information about the person appearing in the photograph by face recognition processing (step 126). Then, the CPU 101 adds share candidate points for the person according to the difference in distance between the shooting locations (step 127).

  FIG. 13 is a diagram for explaining a difference in distance between shooting locations of each photograph. As shown in the figure, among the selected photographs P2 and P7, for the photograph P2, there is a photograph P1 having a distance difference of 100 m or less and a photograph P4 having a distance of 500 m or less, and for the photograph P7, a difference in distance is present. There is a photo P8 within 100 m. Therefore, the CPU 101 acquires information about the person shown in the photos P1, P4, and P8, and adds share points according to the difference in the distance.

  FIG. 14 is a diagram for explaining a process of extracting share candidates for the photo P2 among the selected photos. As shown in the figure, for a person person B, C, D, E, G) shown in the photograph P2, 10 points are added as share candidate points.

  In addition, for a person (A, B) in the photo P1 whose shooting time difference is within 10 minutes before and after the photo P2, 3 points are added, and the photo whose shooting time difference is within 30 minutes before and after One point is added to each person (B, C, E, H) shown in P3 and P4.

  In addition, 3 points are added to the person (A, B) in the photograph P1 whose distance of the shooting location is within 100 m from the photograph P2, and the photograph P4 whose distance is within 500 m is added. One point is added to the person (B, C) in the picture.

  FIG. 15 is a diagram for explaining a process of extracting a share candidate for the photo P7 among the selected photos. Similar to the process for the picture P2, 10 points are added to the person (B, C, D, G) shown in the picture P7, and the picture is shown in the picture P8 where the difference in distance between the shooting locations is within 100 m. 3 points are added to the person (B, F) who is present.

  FIG. 16 is a diagram for explaining a summation process of share candidate extraction results for the selected photo 2 and photo P7. As shown in the figure, the share candidate points for the photos P2 and P7 calculated in FIGS. 14 and 15 are added together. As a result, it can be seen that the share candidate points of the persons B, C, and D are prominently high.

  FIG. 17 is a diagram showing an example of the share candidate list screen 90 displayed as a result of the summing process. As shown in the figure, a share candidate column 93 is displayed on the share candidate list screen 90 in accordance with the combined share candidate points calculated in FIG. For example, the share check box 94 is set to ON for persons B, C, and D who have 20 or more share candidate points.

  By the process of the method (1) described above, the PC 100 can exclude the person (E, G) who does not want to share from the share candidate column 93 although it is shown in the photos P2 and P7 that the user wants to share. It was.

(Share processing by method (2))
Next, details of the share processing by the method (2) will be described. The share processing by the method (2) further includes a method (method (2-1)) of calculating share candidate points using classification information in the human relationship meta DB and the human relationship meta DB. There is a method (method (2-2)) for calculating a share point using a relationship strength diagram. First, the process of the method (2-1) will be described.

  FIG. 18 is a flowchart showing the flow of share processing by the above method (2-1). As shown in the figure, the CPU 101 first obtains information on a photograph selected by the user (step 181).

  FIG. 19 is a diagram illustrating a state in which a user selects a photo that the user desires to share from the photo list. As shown in the figure, the photo P6 is selected from the photos P1 to P8 in the photo list.

  Returning to FIG. 18, the CPU 101 acquires “classification” information of the person in the selected photograph from the human relationship meta DB (step 182).

  Subsequently, based on the “classification” information, the CPU 101 determines whether there is a person who belongs to the same classification as the person shown in the selected photograph (step 183). If it is determined that there is a person belonging to the same category (Yes), the CPU 101 calculates the similarity of the category (step 184).

  FIG. 20 is a diagram showing a classification diagram of persons appearing in a photograph P6 that the user wants to share and calculation conditions for share candidate points. As shown in the figure, the CPU 101, among the categories to which the person (A, B, E) shown in the photograph P6 belongs, for example, in the two main categories of company and family, subcategories of category 1 to category 3, respectively. Understand the relationship with the person belonging to. Of these, the person B is excluded from the processing because it is the person who is trying to share.

  In the figure, person A matches person C up to category 3 (same team), person E and H matches up to category 2 (old department), and persons D, F, G, I, and J are categories. Matches to 1 (company). The person C matches the persons A, C, and H up to category 2, and the persons D, F, G, and I match up to category 1.

  The similarity of the classification is determined according to the hierarchy of the matching category. For example, if it matches up to category 3, the similarity is set to 3, and if it matches up to category 1, the similarity is set to 1.

  Returning to FIG. 18, the CPU 101 adds share candidate points of each person according to the calculated similarity (step 185). FIG. 21 is a diagram showing a calculation result of the share candidate points (FIG. (A)) and an example of a share candidate list screen (FIG. (B)). As shown in the figure, as a result of the calculation of the share candidate points, in the share candidate list screen 90, persons C, H, A, D, E, F, and G are displayed in the share candidate column 93 in the order of share candidate points. ing. For example, for a person with 5 or more share candidate points, the share check box 94 is set to ON and displayed.

  By the processing of the above method (2-1), the PC 100 can check the person (person C) who wants to share although the user does not appear in the photograph P6 that the user wants to share, and the PC 100 appears in the photograph P6. I could uncheck the people I didn't want to share (persons A and E).

  Next, the process of the method (2-2) will be described. The processing of the method (2-2) further includes a method (method (2-2-1)) in which a person who is presumed to want a photograph of a person shown in the photograph selected by the user is a share candidate. ) And a method (method 2-2-2) in which a person who is presumed to be shared by a person in the photograph is selected as a share candidate.

  First, the method (2-2-1) will be described. FIG. 22 is a flowchart showing a process flow of the method (2-2-1).

  As shown in the figure, the CPU 101 first acquires the information of the photograph selected by the user as in the method (2-1) (step 221). Here again, it is assumed that the picture P6 is selected.

  Subsequently, the CPU 101 acquires the “relationship strength” information of the person shown in the photograph P6 selected by the user and the related party from the human relationship meta DB (step 222).

  Subsequently, the CPU 101 determines whether or not there is a relationship (relationship indicating interest) from a person related to the person shown in the selected photo P6 toward the person shown (step 223).

  FIG. 23 is a diagram illustrating the relationship strength between the person B who is the user of the PC 100 and another person. FIG. 24 is a diagram showing the relationship strength (arrow) toward one of the persons A, B, and E shown in the selected photo P6. As shown in both figures, an arrow is directed from persons C and J to person A, an arrow is directed from persons C, D, F, G, H, and I to person B, and a person is directed to person E. An arrow is pointing from C. Each relation strength is indicated by the thickness of each arrow.

  Returning to FIG. 22, the CPU 101 adds share candidate points to the persons A, B, and E shown in the photograph P6 according to the relationship strength (step 22).

  FIG. 25 is a diagram showing a calculation result of share candidate points based on the relationship strength (FIG. (A)) and an example of the share candidate list screen 90 (FIG. (B)). As shown in FIG. 5A, for example, when there is an interest (arrow) in the person B who is the owner of the photograph P6, the share candidate points are doubled. As shown in FIG. 5B, for example, for a person with 5 or more share candidate points, the share check box 94 is set to ON and displayed.

  By the processing of the above method (2-2-1), the CPU 101 can check a person (person C, J, D, G) that is not shown in the photograph P6 that the user wants to share but wants to share. The person (persons A and E) in the photo P6 who does not want to share can be unchecked.

  Next, the process of the above method (2-2-2) will be described. FIG. 26 is a flowchart showing a process flow of the method (2-2-2). The process of the method (2-2-2) is the same as the process of FIGS. 22 to 25 except that the direction of the arrow in the relationship strength diagram is reversed. That is, in this case, share candidate points are added according to the strength of the relationship from the person shown in the selected photo P6 to another person (steps 261 to 264).

  FIG. 27 is a diagram showing the relationship strength (arrow) from one of the persons A, B, and E shown in the selected photo P6 toward another related party. FIG. 28 is a diagram showing a calculation result of share candidate points based on the relationship strength (FIG. 28A) and an example of the share candidate list screen 90 (FIG. 28B). Similar to the above method (2-2-1), as shown in FIG. 6A, when there is an interest (arrow) from the person B who is the owner of the photograph P6, the share candidate point is 2 Doubled. As shown in FIG. 5B, for example, for a person with 5 or more share candidate points, the share check box 94 is set to ON and displayed.

  By the processing of the above method (2-2-2), the CPU 101 can check the person (person C, D, G, J) that is not shown in the photograph P6 that the user wants to share but wants to share. I could uncheck the person I want to share but not want to share (person E).

(Share processing by method (3))
Next, the share process by the method (3) will be described. FIG. 29 is a flowchart showing the flow of share processing according to the method (3).

  As shown in the figure, the CPU 101 acquires information about the photograph selected by the user (step 291). In the figure, it is assumed that the photograph P5 is selected from the photograph list. Subsequently, the CPU 101 creates a list A of persons appearing in the selected photo P5 (step 292).

  Subsequently, the CPU 101 acquires history information of the photos P1 to Pn shared in the past (step 293), and creates a list B1 to Bn of the persons shown in the photos P1 to Pn.

  Subsequently, the CPU 101 calculates the degree of matching between the list A and the lists B1 to Bn (step 295). FIG. 30 is a flowchart showing details of the matching degree calculation processing.

  As shown in the figure, the CPU 101 determines whether or not the list A is all included in the list Bx in a certain photo X (step 301). When it is determined that all of them are included (Yes), the CPU 101 determines whether or not the list Bx is all included in the list A (step 302). If it is determined that all are included (Yes), the CPU 101 sets the degree of matching between the list A and the list Bx to a large value (step 303).

  If it is determined in step 302 that the list Bx is not included in the list A (No), the CPU 101 sets the matching degree to medium (step 304).

  If it is determined in step 301 that the list A is not included in the list Bx (No), the CPU 101 sets the match degree to a small value (step 305).

  CPU101 performs the above process about all the photographs B1-Bn.

  Returning to FIG. 29, the CPU 101 determines whether or not the calculated degree of matching is higher than a predetermined value (step 296). If it is higher (Yes), the CPU 101 obtains information on the person who shared the photo Px shared in the past. (Step 297). Then, the CPU 101 adds share candidate points corresponding to the degree of match to the shared person (step 298).

  FIG. 31 is a diagram showing the share history, and FIG. 32 is a diagram showing calculation conditions for the share candidate points. FIG. 33 is a diagram showing the calculation result of the share points, and FIG. 34 is a diagram showing a display example of the share candidate list screen 90.

  As shown in FIG. 31 to FIG. 33, for example, the photograph ● shared in the past and the selected photograph P5 are completely the same in the photographed person (match level: large), so the photograph ● The share candidate points are added to the person B and the person I who share the above. In addition, since the photograph ■ shared in the past and a person other than the person shown in the photograph P5 are shown (match level: medium), the person B and the person I who shared the photograph ■ have 3 share candidate points. Points are added. In addition, the selected photo P5 is deficient in the number of people compared to the photos P6, P2 and P7 shared in the past (the degree of match is small), so that it is shown in those P6, P2 and P7. One point is added to each of the persons C, J, B, C, and D who are present.

  As shown in FIG. 34, for example, for a person with 5 or more share candidate points, the share check box 94 is set to ON and displayed.

  Through the process of the above method (3), the CPU 101 can check the people (persons B and I) who are not in the photo P5 that the user wants to share but want to share.

(Organization of registered person list)
In the present embodiment, the PC 100 can regularly organize the registered person list. That is, as described above, the PC 100 adds a person who is not shown in the photograph added for a certain period in the registered person list and whose name or email address is not registered in the registered person list. Can be deleted from the list. FIG. 35 is a flowchart showing the flow of processing for deleting data from the registered person list.

  As shown in the figure, the CPU 101 first acquires the latest update date / time information of the registered person list (step 331). Subsequently, the CPU 101 determines whether or not each person in the registered person list has been updated for a predetermined period based on the last update date and time (step 332). If it is determined that the information has not been updated for a predetermined period (Yes), the CPU 101 deletes the registered items related to the person from the registered person list.

  By this process, the PC 100 can delete the data of a person who has been captured once, for example, by passing through a photograph. Therefore, the PC 100 can prevent a person unrelated to the user from being erroneously presented as a destination candidate. Further, even if the deleted person is a person related to the user, the PC 100 can add the person to the registered person list again if the person appears in the newly added photo. .

[Summary]
As described above, according to the present embodiment, the PC 100 uses the methods (1) to (3) for the persons in the registered person list generated based on the face image information extracted from the photograph by the face recognition process. ) To calculate share candidate points, and present information about a person who has a share candidate point equal to or greater than a predetermined value to the user as a destination candidate for the photo selected by the user. Accordingly, the PC 100 can appropriately determine a transmission destination to which the photograph is to be transmitted regardless of whether or not the photograph is desired to be shared by the user and easily share the photograph with a person related to the user. it can.

[Modification]
The present invention is not limited to the above-described embodiments, and various modifications can be made without departing from the scope of the present invention.

  In the above-described embodiment, an example in which the present invention is applied to sharing a digital photographic image has been shown. However, the content to be shared is not limited to digital photo images.

  For example, as a private content, a moving image shot by a digital video recorder or a sound recorded by an IC recorder may be targeted for sharing. In the case of a moving image, a face image is extracted from each frame of the captured moving image, and sharing is performed by the same processing as described above, as in the case of the digital photograph image (still image). In the case of voice, for example, a voiceprint is analyzed from recorded data, and sharing is executed by the same processing as described above.

  As public content, broadcast programs recorded by PVR (Personal Video Recorder) or the like may be targeted for sharing. In the case of a broadcast program, performer information is acquired from the program metadata, and the performer and related parties of the user are registered in the registered person list in the same dimension. Therefore, the human relation meta DB including the performer, the user, and the related parties is generated. For example, when a user records a certain program, the strength of the relationship from the user to the performer of the program is added. Directors in movie content and characters, voice actors, and directors in anime content are treated in the same way as the above performers. In this case, it differs from the above-described embodiment in that the content is not shared with the person (performer or the like) reflected in the content to be shared. Of the methods (1) to (3), the method (1) is not used. Furthermore, when the performers etc. are registered in the registered person list, the e-mail address is not registered, and it is automatically registered from the program metadata without confirming the necessity of registration by the user.

  In this way, broadcast programs are targeted for sharing, so that, for example, it is possible to know which actors and talent fans the user himself / her and their friends are. Moreover, since the human relationship between actors and talents is created as the human relationship meta-DB just by recording the program, the user's interests can be improved.

  Similarly, book content that can be played back on an electronic book terminal may be targeted for sharing as public content. In this case, as in the case of the broadcast program, information about the author and the character is registered in the registered person list from the book metadata, and the content is not shared with the author or the character itself, and the method (1) is used. Absent.

  In this way, electronic book contents are targeted for sharing, and for example, it is possible to know which author or character fan the user himself or his friend is. Moreover, since the user's relationship between authors and characters is created as the above-described human relationship meta-DB just by reading with the electronic book terminal, the user's interest can be improved.

  In the above-described embodiment, sharing is executed based on the human relationship meta DB generated in the PC 100. However, human relationship metadata built on the network such as SNS (Social Network Service) is used for the share. May be. For example, the human relationship meta DB may be generated based on registrant information such as a so-called community or mailing list.

  In the above-described embodiment, sharing is performed between PCs using an e-mail address. For example, when a photograph is taken with a digital camera of a certain user, a digital camera of a nearby friend by wireless LAN or the like. The photo may be shared. In this case, share candidate points are added to a person shown in a photograph that is close in time to the share target photograph.

  For example, when a user of a home server including the user himself or her family is registered in the registered person list and the address of the home server is registered correspondingly, the user uses the above sharing method to You can also store photos on the server. The user can also upload a photo to an online album on a server on the Internet or LAN by making the URL share instead of the photo itself.

  In the above-described embodiment, dynamic weighting is executed for each share candidate point calculated by the above methods (1) to (3). However, the weighting may be static. That is, the PC 100 fixes the weighting value when the share software is installed, and adjusts the size of the share candidate points output by each method. For example, when a value in the order of tens of thousands is output in the method (1) and a value in the order of several hundreds is output in the method (2), the PC 100 reduces the output of the method (1) to 1/100. Meaning can be given to the output of (2). Further, the developer of the share software may release the share software after analyzing the reliability of each of the methods (1) to (3) and adjusting the weighting value in advance accordingly. Furthermore, after installing the share software, the user may try it, and the weighting value may be set larger for the method that is determined to be more effective among the methods (1) to (3).

  In the above-described embodiment, as shown in FIG. 6, the PC 100 sets the ignore flag to ON on the registered person list when the “ignore in the future” button 13 on the registration confirmation screen is pressed. It was. However, the method of setting the ignore flag to ON is not limited to this. For example, the PC 100 may set the ignore flag to ON on the share candidate list screen 90. FIG. 36 is a diagram showing an example of a user interface using the share candidate list screen 90 in this case. As shown in the figure, when a pointer 361 is placed on the display column of any person on the share candidate list screen 90 and, for example, a right click operation is input, the CPU 101 says “Ignore in the future”. A dialog box 362 in which text is described is displayed. When the dialog box 362 is further selected by, for example, left clicking, the CPU 101 sets the ignore flag to ON for the person. Further, the CPU 101 may display the dialog box 362 when an operation for turning off the share check box 94 of a certain person that is automatically set to ON is input on the share candidate list screen 90. Good. As a result, if it is determined that the person automatically extracted as a share candidate is not suitable as a share candidate, the user can be excluded from the share candidate and this person will be extracted as a share candidate in the future. Can also be prevented.

31 ... Face image information field 32 ... Name field 33 ... Mail address field 34 ... Frequent frequency field 35 ... Ignore flag field 36 ... Last update date field 43 ... Attribute / classification 44 ... Relation strength 90 ... Share candidate list screen 91 ... Share execution Button 93 ... Share candidate field 94 ... Share check box 95 ... Camera mark 96 ... Add mark 97 ... Message box 100 ... PC
101 ... CPU
106 ... Display unit 107 ... Input unit 108 ... Storage unit 109 ... Communication unit

Claims (13)

A plurality of contents including identification information for identifying a person, and a storage unit for storing person information regarding the plurality of persons including at least the identification information and a person name corresponding to the identification information;
At least one of the plurality of contents is transmitted to a device related to at least one person corresponding to the person information, or the content is transmitted to a storage device on a network, and on the storage device A communication unit for transmitting the location information of the content to a device related to the person;
An operation input unit for receiving an input of a user operation for selecting at least one content from the plurality of contents;
Recognizing the identification information included in other content having a predetermined relationship with the selected content, and according to the strength of the predetermined relationship, each identified by the recognized identification information and included in the person information A control unit for calculating a person's points;
The person information of the person having the point equal to or greater than a first value is used as a transmission destination candidate for transmitting the selected content or the location information of the selected content to the device related to the person. An electronic device comprising: an output unit that outputs data for display. The information processing apparatus according to claim 1,
The control unit displays a check box for selecting, via the operation input unit, whether or not the selected content can be transmitted together with the person information as the transmission destination candidate, and from the first value An electronic device that displays the check box displayed together with the person information of a person having the point equal to or larger than the second value in a state where the transmission is permitted. An information processing apparatus according to claim 2,
The storage unit stores human relationship information indicating the strength of a relationship between persons included in the person information,
The control unit recognizes the identification information included in the selected content, and based on the personal relationship information, the strength of the relationship between the person identified by the identification information and the person included in the personal information An electronic device that calculates the points according to the conditions. The electronic device according to claim 3,
The person relation information has direction information indicating the interest each person has toward other persons,
The said control part is an electronic device which calculates the said point according to the intensity | strength of the said relationship, and the said direction information. The electronic device according to claim 2,
The content is a digital photographic image having shooting time information,
The identification information is a face image of the person,
The controller recognizes the face image included in another digital photo image having second shooting time information within a predetermined time from the first shooting time information of the selected digital photo image, and An electronic device that calculates the point according to a difference between the shooting time information of the second and the second shooting time information. The electronic device according to claim 2,
The content is a digital photographic image having shooting position information,
The identification information is a face image of the person,
The control unit recognizes the face image included in another digital photo image having second shooting position information within a predetermined distance from the first shooting position information of the selected digital photo image, and An electronic device that calculates the point according to a difference between shooting position information and the second shooting position information. The electronic device according to claim 2,
The storage unit stores transmission history information related to content transmitted to an apparatus related to the person based on the display of the transmission destination candidates.
The control unit compares the first identification information included in the transmitted content with the second identification information included in the selected content based on the transmission history information, and compares the first identification information included in the selected content. An electronic device that calculates a fitness between identification information and the second identification information, and calculates the point of a person related to the content transmission destination device according to the fitness. The electronic device according to claim 2,
The control unit recognizes identification information included in the content every time the content is stored in the storage unit, generates the personal information related to the person identified by the identification information, and stores the personal information in the storage unit Electronic equipment. The electronic device according to claim 8,
The controller is
Each time the content is stored in the storage unit, the identification information included in the content is recognized, and the identification information is stored in the storage unit as temporary person information.
When the operation input unit inputs a person name for the temporary person information, the temporary person information is updated as the personal information,
If there is no input of the person name within a predetermined period after storing the temporary person information and the content stored in the storage unit does not include the identification information as the temporary person information, An electronic device that deletes personal information. The electronic device according to claim 2,
The controller is
When the identification information corresponding to the person information displayed as the transmission destination candidate is included in the selected content, the first mark is displayed together with the person information,
The reason why the second mark different from the first mark and the person information are displayed as the transmission destination candidates together with the person information when the identification information is not included in the selected content. An electronic device that displays information. The electronic device according to claim 2,
The controller is
If the person has a point greater than or equal to a third value greater than the first value, the selected content is transmitted to a device associated with the person;
When the person has a point less than the third value, the selected content is transmitted to a storage device on the network, and the location information of the content on the storage device is related to the person Send to electronic equipment. Storing a plurality of pieces of content including identification information for identifying a person, and personal information related to the plurality of persons including at least the identification information and a person name corresponding to the identification information;
Receiving an input of a user operation for selecting at least one content from the plurality of contents;
Recognizing the identification information included in other content having a predetermined relationship with the selected content, and according to the strength of the predetermined relationship, each identified by the recognized identification information and included in the person information Calculate the points of the person,
Displaying the person information of the person having the point equal to or greater than a predetermined threshold as a transmission destination candidate for transmitting the selected content or location information of the content to the device related to the person;
The selected content is transmitted to a device related to a person corresponding to the person information as the displayed transmission destination candidate, or the selected content is transmitted to a storage device on a network, and A content transmission method for transmitting the location information of the content on a storage device to a device related to the corresponding person. Electronic equipment,
Storing a plurality of contents including identification information for identifying a person, and personal information related to the plurality of persons including at least the identification information and a person name corresponding to the identification information;
Receiving an input of a user operation for selecting at least one content from the plurality of contents;
Recognizing the identification information included in other content having a predetermined relationship with the selected content, and according to the strength of the predetermined relationship, each identified by the recognized identification information and included in the person information Calculating a person's points;
Displaying the person information of the person having the point equal to or greater than a predetermined threshold as a transmission destination candidate for transmitting the selected content or location information of the content to the device related to the person;
The selected content is transmitted to a device related to a person corresponding to the person information as the displayed transmission destination candidate, or the selected content is transmitted to a storage device on a network, and Transmitting the location information of the content on the storage device to a device related to the corresponding person.