JP2011076551A - Electronic apparatus, access control method and program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To readily authenticate access rights for contents which are not created by users themselves of the apparatuses of access originations. <P>SOLUTION: A CPU 12 of a PVR 100 accepts registrations of face images of the users of the respective apparatuses from the respective apparatuses over a network 50, and detects the face images from respective contents on the network 50; and when the registered facial images and the facial images detected from the respective contents are coincided with one another, the access permission data that permit access to the contents. <P>COPYRIGHT: (C)2011,JPO&INPIT

Description

  The present invention relates to an electronic device capable of transmitting content to another device in response to a reproduction request from the other device on a network, an access control method in the electronic device, and a program.

  Conventionally, in an AV (Audio / Visual) network system in a home, for example, a device that exists in one room is used, and content stored in a device that exists in another room is not made aware of the storage location by the user. It is possible to play back.

  By the way, not only the content stored in the device in the same home but also the system which accesses the content of the device in another home from the device in one home, and reproduces the content is also assumed. In such a system, since the user of the device is usually different for each home, it is important to authenticate the access authority to the content.

  As a technique for authenticating the access authority to content, for example, in Patent Document 1 below, access from a user terminal to user-owned content stored in a server is authenticated by a user ID and a password. It is described to do.

JP 2007-317178 A

  However, as described in Patent Document 1, when authenticating access using a user ID and password, the user needs to grasp the user ID and password one by one. Can not be. In addition, the user needs to take a complicated step of inputting a user ID and a password every time the user accesses.

  Furthermore, with the technique described in Patent Document 1, complete reproduction is impossible unless the content is created (recorded) by the user and uploaded to the server. Therefore, for example, even if there is content that the user's acquaintance uploaded and may be publicly disclosed to the user, in order for the user to play it, for example, the acquaintance will give the user ID and password, etc. Complicated work is required.

  In view of the circumstances as described above, an object of the present invention is to provide an electronic device capable of easily authenticating access authority for content not created by the user of the access source device, and an access control method in the electronic device. and to provide a program.

  In order to achieve the above object, an electronic apparatus according to an embodiment of the present invention includes a storage unit, a communication unit, and a control unit. The storage unit stores content. The communication unit receives first face image data from another device on the network. The control unit extracts first facial feature data from the received first facial image data, detects second facial image data from the stored content, and extracts the second facial image data from the second facial image data. Second face feature data is extracted. The control unit determines whether the first face feature data matches the second face feature data, and determines that the first face feature data matches the second face feature data. If so, access permission data for permitting access to the content from the other device is generated.

  With this configuration, when the content includes a second image that matches the first face image transmitted from another device, the content is created by the user of the other device. Even if it is not a thing, the access from the other apparatus with respect to the said content can be permitted. That is, the electronic device can authenticate the access authority to the content using the face image as a key. Here, the first face image data is the face image data of the user of another device, and is taken by a camera of the other device, for example. In other words, users of other devices are permitted to access the content in which they are shown. Further, the first face image data may be created only by a specific application installed in another device in order to ensure that the first face image data is a face image of a user of the other device. Good. The content may be recorded on a general-purpose recording medium such as an optical disk (BD, DVD) inserted into a disk drive of the electronic device. In addition, the electronic device may generate the access permission data for content stored in a device other than the electronic device.

  The control unit executes the detection of the second face image data and the extraction of the second face feature data when storing the content in the storage unit, and the second face feature data together with the content You may memorize | store in the said memory | storage part.

  As a result, when there is a request for access to content from another device, the electronic device can quickly execute authentication of access authority to the content.

  The storage unit may store, together with the content, third face image data indicating a creator of the stored content and third face feature data extracted from the third face image data. In this case, the control unit determines whether the first face feature data and the third face feature data match, and the first face feature data and the third face feature data are When it is determined that they match, the access permission data may be generated.

  Thereby, even when the face image of the user of another device is not shown in the content, the electronic device can permit the content creator to access the content. Therefore, when the creator of the content accesses the content from another device, a situation where access is permitted is prevented.

  The control unit may generate a list of contents for which the access permission data is generated, and transmit the list to the other device by the communication unit. The control unit receives a reproduction request signal for requesting reproduction of one content on the list from the other device, and transmits the one content to the other device in response to the reproduction request signal. Good.

  Accordingly, the electronic device can cause the user to grasp and view only the content that can be accessed by the user of the other device among the content stored in the storage unit.

  An access control method according to another aspect of the present invention includes storing content and receiving first face image data from another device on the network. First facial feature data is extracted from the received first facial image data. Second facial image data is detected from the stored content, and second facial feature data is extracted from the second facial image data. Then, it is determined whether or not the first face feature data matches the second face feature data. When it is determined that the first face feature data and the second face feature data match, access permission data for permitting access to the content from the other device is generated.

  A program according to another aspect of the present invention includes a storage step, a reception step, a first extraction step, a detection step, a second extraction step, a determination step, and a generation step. Let it run. In the storage step, content is stored. In the receiving step, the first face image data is received from another device on the network. In the first extraction step, first face feature data is extracted from the received first face image data. In the detection step, second face image data is detected from the stored content. In the second extraction step, second face feature data is extracted from the second face image data. In the determining step, it is determined whether or not the first face feature data matches the second face feature data. In the generating step, when it is determined that the first face feature data matches the second face feature data, access permission data for permitting access to the content from the other device is generated.

  As described above, according to the present invention, it is possible to easily authenticate access authority for content that is not created by the user of the access source device.

1 is a diagram schematically showing an example of an AV (Audio / Visual) network system assumed in an embodiment of the present invention. FIG. It is a figure which shows the hardware constitutions of PVR which has a metadata production | generation function of content in one Embodiment of this invention. It is a figure which shows the hardware constitutions of PVR which does not have the metadata production | generation function of content in one Embodiment of this invention. It is the flowchart which showed the flow of the metadata production | generation process by default by PVR in one Embodiment of this invention. In one Embodiment of this invention, PVR is the flowchart which showed the detailed flow of the process which searches the other apparatus which can produce | generate metadata. It is the figure which showed the example of the data structure of the test data returned from the said content storage apparatus. It is the figure which showed the detail of the data for operation modes contained in the test data shown in FIG. FIG. 7 is a diagram showing details of processing data included in the test data shown in FIG. 6. In one Embodiment of this invention, when a content genre is a broadcast content and it is a news program, it is the figure which showed the process required for execution of each operation mode. In one Embodiment of this invention, when a content genre is a broadcast content and it is a sports program, it is the figure which showed the process required for execution of each operation mode. In one Embodiment of this invention, when a content genre is a broadcast content and it is a music program, it is the figure which showed the process required for execution of each operation mode. In one Embodiment of this invention, when a content genre is a private content, it is the figure which showed the process required for execution of each operation mode. It is a figure which shows notionally the camera shake feature extraction process in one Embodiment of this invention. It is a figure which shows notionally the key frame detection process in one Embodiment of this invention. It is a figure which shows notionally the metadata production | generation process by default in one Embodiment of this invention. It is the flowchart which showed the flow of the metadata production | generation process by the manual by PVR in one Embodiment of this invention. It is a figure which shows notionally the metadata production | generation process in the manual in one Embodiment of this invention. It is the flowchart which showed the flow of the content classification process in one Embodiment of this invention. It is the figure which showed the example of a display of the content list produced | generated in one Embodiment of this invention. It is the flowchart which showed the flow of the display control process of the content list according to the traffic condition etc. in one Embodiment of this invention. FIG. 6 is a diagram illustrating a state in which a thumbnail state is changed by a content list display control process in an embodiment of the present invention. It is the flowchart which showed the flow of the access control process based on face identification metadata in one Embodiment of this invention. 6 is a table showing an overview of access control processing according to an operation mode in an embodiment of the present invention.

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

[Outline of AV network system]
FIG. 1 is a diagram schematically showing an example of an AV network system assumed in an embodiment of the present invention.

  As shown in the figure, in the AV network system, for example, devices installed in different houses (A's house and B's house) are connected via a network 50 such as the Internet. For example, in Mr. A's house, two PVRs (Personal Video Recorders) 100 and 200 and a TV 60 connected to each of the PVRs 100 and 200 are installed in different rooms. For example, in Mr. B's house, one PVR 300 is installed in one room, and two TVs 60 connected to the PVR are installed in a room where the PVR 300 is installed and in a different room. .

  The figure shows an example in which four devices in Mr. A's house and three devices in Mr. B's house are connected via the network 50. Of course, the number of devices installed in each house is shown. The type is not limited to this, and other home devices can be connected to the network 50. The following description may be made on the assumption that devices other than the devices shown in the figure are connected to the network 50.

  In such a configuration, the device at Mr. A's house and the device at Mr. B's house can access each other via the network 50 when predetermined authentication can be performed. Therefore, for example, Mr. B can access the PVRs 100 and 200 of Mr. A's house from the PVR 300 existing at Mr. B's house via the network 50 and view the contents stored in the PVRs 100 and 200.

  Here, among the PVRs 100, 200, and 300, the PVR 100 has a function of generating metadata for performing special reproduction such as content editing and digest reproduction, content classification, and the like. It does not have such a function. Therefore, for example, even when Mr. B wants to perform special playback or classification of the content stored in the PVR 200 from Mr. B's house, the special playback or classification cannot be performed by the PVR 300.

  Therefore, in this embodiment, a device that does not have a content metadata generation function, such as the PVR 300, causes the other devices on the network 50 that have the metadata generation function, such as the PVR 100, to generate the metadata. It is made possible.

[Hardware configuration of PVR]
FIG. 2 is a diagram illustrating a hardware configuration of the PVR 100 having a metadata generation function. As shown in the figure, the PVR 100 includes a digital tuner 1, a demodulator 2, a demultiplexer 3, a decoder 4, a recording / reproducing unit 5, an HDD (Hard Disk Drive) 8, an optical disk drive 9, and a communication unit 11. The PVR 100 includes a CPU (Central Processing Unit) 12, a flash memory 13, and a RAM (Random Access Memory) 14. The PVR 100 further includes an operation input unit 15, a graphic control unit 16, a video D / A (Digital / Analog) converter 17, an audio D / A (Digital / Analog) converter 18, an external interface 19, and a feature extraction circuit 20.

  The digital tuner 1 selects a specific channel of digital broadcasting via the antenna 22 under the control of the CPU 12 and receives a broadcast signal including program data. This broadcast signal is, for example, an MPEG stream (TS: transport stream) encoded in the MPEG-2 TS format, but is not limited to this format. The demodulator 2 demodulates the modulated broadcast signal.

  The demultiplexer 3 separates the multiplexed broadcast signal into signals such as a video signal, an audio signal, a caption signal, and an SI (Service Information) signal, and supplies them to the decoder 4. The demultiplexer 3 can also supply the separated signals before decoding to the feature extraction circuit 20. The SI signal is a signal for transmitting data or the like for displaying an EPG (Electronic Program Guide). The EPG information is used for content genre determination as described later.

  The decoder 4 decodes the video signal, audio signal, caption signal, and SI signal separated by the demultiplexer 3, respectively. Each decoded signal is supplied to the recording / reproducing unit 5.

  The recording / reproducing unit 5 includes a recording unit 6 and a reproducing unit 7. The recording unit 6 temporarily stores the video signal and the audio signal decoded and input by the decoder 4 and outputs and records them on the HDD 8 and the optical disk drive 9 while controlling the timing and the data amount. The recording unit 6 can also read the content recorded on the HDD 8, output it to the optical disc drive 9, and record it on the optical disc 10. The playback unit 7 reads the video signal and audio signal of the video content recorded on the HDD 8 or the optical disk 10 and outputs them to the decoder 4 for playback while controlling the timing and the data amount.

  The HDD 8 stores a program received via the digital tuner 1 and various contents received via the network 50 by the communication unit 11 in a built-in hard disk. When these stored contents are reproduced, the HDD 8 reads these data from the hard disk and outputs them to the recording / reproducing unit 5.

  The HDD 8 may store various programs and other data. These programs and data are read from the HDD 8 according to a command from the CPU 12 and executed in the RAM 14 at the time of execution and reference.

  Similar to the HDD 8, the optical disk drive 9 can record various data such as the program content on the mounted optical disk 10, and can read the recorded data. The various programs may be recorded on a general-purpose recording medium such as the optical disk 10 and installed in the PVR 100 by the optical disk drive 9.

  The communication unit 11 is a network interface for connecting to the network 50 and exchanging data with other devices on the network 50 using a protocol such as TCP / IP (Transmission Control Protocol / Internet Protocol). When the data received by the communication unit 11 is multiplexed, the data is supplied to the demultiplexer 3. At least a part of the received data is also supplied to the feature extraction circuit 20 as necessary. The EPG information may be acquired by the communication unit 11 from the network 50 instead of from the broadcast signal received by the digital tuner 1.

  The external interface 19 includes, for example, a USB interface and a memory card interface, and is connected to an external device such as a digital video camera and a digital still camera, a memory card, and the like, and reads data such as content from them.

  The CPU 12 accesses the RAM 14 or the like as necessary, and comprehensively controls processing of each block of the PVR 100 such as video data reception processing, content recording / playback processing, and feature extraction (metadata generation) processing.

  The flash memory 13 is, for example, a NAND type, and is a non-volatile memory in which firmware such as an OS, a program, and various parameters executed by the CPU 12 is fixedly stored. The flash memory 13 stores a program that operates together with the feature extraction circuit 20 in the metadata generation process, various other programs, and various data such as the EPG information.

  The RAM 14 is used as a work area of the CPU 12 and is a memory that temporarily holds an OS, a program, processing data, and the like during the content recording / playback processing and metadata generation processing.

  The operation input unit 15 inputs various setting values and commands by a user's operation from, for example, a remote controller 21 having a plurality of keys (hereinafter referred to as a remote controller 21), and outputs it to the CPU 12. Of course, the operation input unit 15 may be configured by a keyboard or mouse connected to the PVR 100, a switch mounted on the PVR 100, or the like, without using the remote controller 21.

  The graphic control unit 16 performs graphic processing such as OSD (On Screen Display) processing on the video signal output from the decoder 4 and other video data output from the CPU 12, and displays the result on a display device such as the TV 60, for example. to generate a video signal.

  The video D / A converter 17 converts the digital video signal input from the graphic control unit 16 into an analog video signal, and outputs the analog video signal to a display device via a video output terminal or the like.

  The audio D / A converter 18 converts the digital audio signal input from the decoder 4 into an analog audio signal and outputs the analog audio signal to a TV or the like via an audio output terminal or the like.

  The feature extraction circuit 20 extracts predetermined video features and audio features from content stored in the HDD 8 and content stored in other devices on the network 50, and special reproduction of each content is performed based on the features. Various metadata used for processing and classification processing are generated. Specifically, the feature extraction circuit 20 divides the video signal and audio signal of the content into data at predetermined time intervals (every frame interval) (data segmentation process), and temporarily stores them in the RAM 14. The feature extraction circuit 20 extracts video features by detecting, for example, motion vectors for video data, and extracts audio features by analyzing power levels, for example, for audio data. .

  The predetermined video features include, for example, camera features such as pan, tilt, and zoom, and image features that show objects such as people (faces), animals, and buildings. The predetermined voice feature is, for example, a feature showing a human voice, more specifically, a feature showing a duration of voice power. Metadata refers to metadata (scene feature metadata) related to swell scenes (keyframes) in content generated based on the above camera features and audio features, subjects in the content (people or otherwise), etc. Accordingly, metadata for classifying content (classification metadata), metadata used for identifying a human face in the content and controlling access to the content (face identification metadata), and the like. Details of these various metadata will be described later. The metadata may be the feature data itself extracted by the feature extraction process.

  FIG. 3 is a diagram illustrating a hardware configuration of the PVR 300 that does not have a metadata generation function. As shown in the figure, the configuration of the PVR 300 is the same as that of the PVR 100 shown in FIG. 2 except that the feature extraction circuit 20 of the PVR 100 is not provided. Therefore, description of each block of the PVR 300 is omitted here. The configuration of the PVR 200 is the same as that of the PVR 300.

[Operation of each device in the AV network system]
Next, the operation of each device in the AV network system configured as described above will be described. Hereinafter, the operation of the PVR 300 will be mainly described. In the following, the operation of the PVR 300 will be described with the CPU 42 of the PVR 300 as the main operation subject, but this operation is also performed in cooperation with other hardware and programs executed under the control of the CPU 42.

(Metadata generation process)
First, metadata generation processing in this system will be described. In the present embodiment, there are a case where metadata is automatically generated by default for all contents stored in all devices on the network 50 and a case where metadata is generated for specific contents.

  First, a case where metadata of each content stored in each device on the network 50 is generated by default will be described. FIG. 4 is a flowchart showing a flow of default metadata generation processing by the PVR 300.

  As shown in the figure, the CPU 42 of the PVR 300 attempts to access each device on the network 50 and receives access authentication from each device (step 41). When the authentication is passed (Yes in step 42), the CPU 42 detects the content stored in the accessed device (step 43). If the authentication fails (No), that is, if no other accessible device exists on the network 50, the CPU 42 shifts from the user to an operation mode other than the metadata generation operation, such as normal playback of content, for example. It is determined whether or not there is an instruction to perform (step 44), and if there is such an instruction (Yes), the process proceeds to another operation mode.

  If there is another device accessible in step 42 (Yes), the CPU 42 detects the content stored in the other device (step 43). Then, the CPU 42 determines whether metadata is generated for each detected content (step 45).

  If it is determined in step 45 that metadata has been generated (Yes), the CPU 42 determines whether metadata has been generated for all contents stored in all devices on the network 50, that is, other It is determined whether there is any content for which metadata is to be generated (step 51). If it is determined that there is no content for which metadata is to be generated (Yes), the process ends, and if it exists (No), the process returns to Step 41 and repeats the process.

  If it is determined in step 45 that metadata has not been generated (No), the CPU 42 searches the network 50 for other devices capable of generating metadata (step 46). Details of this search process will be described later.

  If another device corresponding to the generation of metadata is found as a result of the search process (Yes in step 47), the CPU 42 transmits a command for generating metadata to the other device (step 48). . Then, the CPU 42 receives metadata generated by another device in response to the command (step 50). The CPU 42 repeats the above processing for all contents of all devices on the network 50 (step 51).

  If no other device corresponding to the generation of metadata is found as a result of the search process (Yes in step 47), the CPU 42 indicates that the metadata cannot be generated, for example, via the TV 60 connected to the PVR 300. A warning is displayed (step 49).

FIG. 5 is a flowchart showing a detailed flow of a search process for another device capable of generating the metadata.
As shown in the figure, the CPU 42 first transmits test data to each device other than the other device to another device (hereinafter referred to as a content storage device) on the network 50 that stores the content. A command for instructing is transmitted (step 61). Here, the test data is data for inquiring whether or not the metadata can be generated, and is transmitted to search for a device that can perform the metadata generation processing most reliably and efficiently.

  Subsequently, the CPU 42 receives a return result of the test data received by the content storage device from another device (step 62). Here, the details of the test data will be described.

  FIG. 6 is a diagram showing an example of the data structure of test data returned from the other device to the content storage device. As shown in the figure, the test data includes synchronization data 71, system data 72, operation mode data 73, processing data 74, and error processing data 75.

  The synchronization data 71 is data for synchronizing the test data transmitted from the content storage device with the test data returned from another device. The system data 72 is data such as an IP address of another device of the reply source.

  FIG. 7 is a diagram showing details of the operation mode data 73. As shown in the figure, the operation mode data 73 is composed of, for example, 16 bits (m1 to m16), and for a plurality of operation modes, whether or not it can be processed in the other device is 0 or 1 bit. there is shown. In the figure, an operation mode can be added as appropriate to a location (−) where the operation mode is not defined. The operation modes include a video / audio display output mode, a normal content playback mode, a content digest playback mode, a content automatic editing mode, a content storage (recording) mode, a content shooting (camera function) mode, and the like. In the example shown in the figure, it is shown that other devices from which test data is returned correspond to all these modes.

  In the flowcharts of FIGS. 4 and 5, metadata to be generated by other devices is determined in advance, and it is determined from the operation mode data whether the specific metadata can be generated. For example, when generating metadata for digest playback is intended, it is determined from the operation mode data whether or not another device supports digest playback.

  FIG. 8 is a diagram showing details of the processing data 74. As shown in the figure, the processing data 74 is composed of, for example, 12 bits (g1 to g4, c1 to c4, a1 to a4), and various video and audio feature extraction required in the digest playback mode, the automatic editing mode, and the like. Whether or not processing is possible is indicated by 0 or 1 bit. In the figure, a processing function can be added as appropriate to a location (-) where the processing function is not defined. The processing data includes an image feature, a camera feature, and an audio feature. Image feature processing functions include a face detection function and a telop detection function. Camera features include zoom, pan, tilt, and camera shake detection functions. The voice features include a voice swell (high level) detection function, a music detection function, and a human voice detection function. In the example shown in the figure, it is shown that other devices from which the test data is returned correspond to all these processing functions.

  The error processing data 75 is composed of, for example, 16 bits, and is data for measuring an error rate of an error that occurs until the test data is transmitted from the content storage device and returned. Specifically, for example, an error detection code such as a CRC code or a Reed-Solomon code is used.

  Returning to the flowchart of FIG. 5, when the CPU 42 receives the return result data of the test data, there is another device (hereinafter also simply referred to as a “corresponding device”) corresponding to generation of specific metadata from the data. Whether or not (step 63). When it is determined that the corresponding device does not exist (No), the CPU 42 performs a warning display shown in step 49 of FIG.

  When it is determined that there is a corresponding device (Yes), the CPU 42 determines whether or not there are a plurality of the corresponding devices (step 64). If it is determined that there are a plurality of compatible devices (Yes), the CPU 42 detects the error rate and the delay time based on the return result data of the test data (step 65). The error rate is calculated from the error processing data in the returned test data. The delay time is calculated from the time when the content storage device transmits the test data and the time when it is returned from another device. The CPU 42 calculates the error rate and delay time for each corresponding device.

  Then, the CPU 42 selects a corresponding device that minimizes the error rate and the delay time from among the plurality of corresponding devices (step 66). That is, the CPU 42 selects another device that can perform the metadata generation most efficiently and with high accuracy when the metadata is generated. Further, the CPU 42 may perform the selection based on a value obtained by multiplying the error rate and the delay time.

  Subsequently, the CPU 42 determines a genre for each content stored in the content storage device (step 67). The reason why the genre of the content is determined here is that the characteristic data required for the automatic editing mode and the digest reproduction mode differ depending on the genre. That is, if the content genre is different, the metadata that is requested to be generated by other devices and the operation mode to be handled for the metadata also differ, so the PVR 300 appropriately selects the corresponding device according to the genre and the operation mode. It is set to be.

Here, the relationship between the genre of the content and the operation mode necessary for generating the metadata of the content will be described.
9 to 12 show that the content genre is broadcast content (television content) and is a news program (FIG. 9), a sports program (FIG. 10), a music program (FIG. 11), and a content genre. It is the figure which showed the process required for execution of each operation mode about each when each is private content image | photographed by the general user (FIG. 12).

  As shown in FIG. 9, when the content is a broadcast content and a news program, in order to execute the digest playback and automatic editing modes, the face detection and telop detection processes are essential in the image feature extraction process. Of human voice feature extraction processing, human voice detection processing is essential. This is because the news program has features unique to the news program, such as a news caster image and a telop that is normally displayed below the news caster. Further, in this case, detection processing of camera features such as zoom, pan, and tilt among camera features is not essential, but it is better to improve accuracy. This is because a characteristic scene is extracted from the video of the actual news site.

  As shown in FIG. 10, when the content is a broadcast content and a sports program, in order to execute each mode of digest playback and automatic editing, face detection processing is essential among image feature extraction processing, and camera feature extraction processing Among these, zoom, pan, and tilt camera feature detection processing is indispensable, and audio feature detection processing is indispensable in audio feature extraction processing. This is because sports programs are characterized by active player movements and camera movements, for example, in soccer goal scenes, and cheers. In this case, it is better that the telop detection process is not essential among the image features. This is because information such as player information and game progress may be displayed as a telop.

  As shown in FIG. 11, in the case where the content is a broadcast content and a music program, in order to execute each mode of digest playback and automatic editing, face detection processing is essential among image feature extraction processing, and audio feature extraction processing Among them, music detection processing and human voice detection processing are essential. This is because in a music program, it is necessary to identify the performing singer and the music that the singer sings. In this case, the zoom, pan, and tilt camera feature detection processing of the camera feature extraction processing is preferably not essential. This is to extract a scene or the like where the singer actually sings a song.

  As shown in FIG. 12, when the content is private content, face detection processing is essential among the image feature extraction processing, detection processing of each camera feature of zoom, pan, tilt, and camera shake is indispensable. Among them, voice excitement detection processing and human voice detection processing are essential. This is to detect a person reflected in the private content and the behavior of the person. In addition, the camera shake feature detection process is to exclude a camera shake image that cannot be seen when detecting a key frame from the private content.

  Here, when the content is a broadcast content, each genre is recorded based on the genre information recorded together with the content itself when the content is recorded in each content storage device, for example, based on the RPG information. it can be determined. On the other hand, whether the content is broadcast content or private content can be determined by detecting the above-described camera shake feature. That is, if there is a camera shake image in the content video, it can be determined that the content is private content photographed by a general user, not a professional. However, in this embodiment, since the PVR 300 does not have a metadata generation function in the first place, it does not support the camera feature extraction process. Therefore, the PVR 300 requests a device (for example, the above-described PVR 100) corresponding to the shake feature extraction process to determine whether the content is the broadcast content or the private content based on the returned test data. As will be described later, the data relating to the genre of the content including the discrimination data based on the hand movement feature is also used as the classification metadata.

  In addition, for example, when the broadcast content and the private content are recorded in the content storage device, the determination data for the broadcast content is automatically stored as a genre ID together with the genre information based on the EPG information. May be. This can be achieved, for example, by identifying a device (camcorder or the like) that is an input source of private content.

  The other device that has received the request for the determination processing acquires the target content from the content storage device, and extracts the shake feature from the content using the shake feature extraction function that the device has. Here, details of the camera shake feature extraction processing will be described.

  FIG. 13 is a diagram conceptually illustrating the camera shake feature extraction process. Another device that receives a request from the PVR 300 uses a feature extraction circuit to detect a motion vector by block matching processing between a reference frame and a search frame in the content, and performs multiple regression analysis based on the motion vector. to calculate the affine coefficient by. Then, as shown in the figure, the other device uses the pan coefficient Px and the tilt coefficient calculated from the affine coefficients for each predetermined section (t0 to t1, t1 to t2, t2 to t3, t3 to t4) in the video content. Camera shake can be determined by the variance of Py and the number of intersections with the average value level of a predetermined section. As the predetermined section, for example, a time length of about 0.5 seconds to 5 seconds is set.

  For example, in the interval from t0 to t1 in the figure, Px or Py intersects the average level value 12 times. The feature extraction circuit of another device sets the threshold of the number of intersections as Thcr, the number of intersections is larger than Thcr, and the variance value of each of the predetermined sections of Px or Py is larger than the predetermined threshold Thv, It is determined that the video in the predetermined section is a camera shake video. Otherwise, it is determined that the video is not a camera shake video. The determination result is transmitted to the PVR 300 in order to determine whether the content is broadcast content or personal content.

  Returning to FIG. 5, the CPU 42 detects an operation mode necessary for metadata to be generated by another device according to the genre determined for each content, using the criteria shown in FIG. 9 to FIG. 12 ( Step 68). Then, the CPU 42 detects an operation feature ID (g1 to g4, c1 to c4, a1 to a4) that is indispensable for executing the operation mode (step 69).

  Subsequently, in step 47 in FIG. 4, the CPU 42 determines whether or not there is another device corresponding to the process indicated by the operation feature amount ID, and selects the corresponding device. Then, as described above, the CPU 42 transmits a command for instructing generation of metadata to the selected device (step 48).

  The other device instructed to generate the metadata receives the content to be instructed from the content storage device, and uses the feature extraction circuit of the other device to perform feature extraction processing and metadata generation processing based on the feature extraction processing Execute.

  Here, the feature extraction process will be described. FIG. 14 is a diagram conceptually showing the feature extraction processing. In the figure, an example is shown in which a rising scene (key frame) is detected as a feature amount, for example, in order to generate the scene feature metadata.

  As shown in the figure, the feature extraction circuit of another device instructed to generate the metadata executes the camera feature extraction process, the image feature extraction process, and the audio feature extraction process for the video scene of the moving image content. Based on the extraction result, a frame in a section in which a feature equal to or greater than a predetermined threshold is extracted is extracted as a key frame.

  Here, the key frame is extracted based on the camera feature and the image feature, because the camera feature section is a section that is shot by the user operating the camera intentionally, and thus is a scene having high importance for the user. This is because the human face is likely to be the focus of the user's attention. Moreover, the reason why key frames are extracted based on voice features is that, for example, it is considered that a user's attention is high in a section where the voice level is high.

  Specifically, the feature extraction circuit detects a motion vector by block matching processing between a reference frame and a search frame in video content. The feature extraction circuit calculates an affine coefficient by multiple regression analysis based on the motion vector, and calculates a pan coefficient Px, a tilt coefficient Py, and a zoom coefficient Pz from the affine coefficient. A section in which the pan coefficient Px, tilt coefficient Py, and zoom coefficient Pz each exceed a predetermined threshold is detected as a key frame. In addition, the feature extraction circuit extracts a section having a power equal to or higher than a predetermined threshold, for example, as an audio excitement section from the audio signal of the moving image content. The feature extraction circuit detects, for example, a section where a key frame section extracted from the video scene and a voice excitement section extracted from the audio signal overlap as a key frame of the moving image content. The key frame information (time code or the like) is generated as scene feature metadata.

  FIG. 15 is a diagram conceptually showing the metadata generation processing by default described above. As shown in the figure, for example, it is assumed that PVRs 100 and 500 corresponding to generation of metadata and PVRs 200, 300, and 400 not corresponding to generation of metadata exist on the network 50. The PVRs 200 and 400 are the content storage devices that store the content A and the content B, respectively.

  In this example, when the PVR 300 that does not support generation of metadata generates metadata for the content A stored in the PVR 200, the PVR 300 generates metadata among the corresponding devices based on the test data. In this case, the PVR 100 is selected as another device that minimizes the error rate and the delay time, and metadata is generated. As shown in the figure, this is because the PVR 100 and PVR 500, which are compatible devices, are located closer to the PVR 200, which is a content storage device. The generated metadata (default metadata A) is stored in the recording medium of the PVR 200 and downloaded to the PVR 300 as necessary for special reproduction, for example.

  Similarly, when the PVR 300 generates metadata for the content B stored in the PVR 400, the PVR 300 is based on the test data as other devices that minimize the error rate and delay time among the corresponding devices. Select PVR 500 and generate metadata. The generated metadata (default metadata B) is stored in the recording medium of the PVR 400 and downloaded to the PVR 300 as necessary.

  Next, a case where metadata is manually generated for specific content on the network 50 will be described. FIG. 16 is a flowchart showing a manual metadata generation process performed by the PVR 300. This processing is usually executed during content playback processing (special playback or normal playback).

  As shown in the figure, the CPU 42 of the PVR 300 attempts to access a specific device on the network 50 and receives access authentication from the device (step 161), similarly to steps 41 and 42 in the flowchart of FIG. When the authentication is passed (Yes in Step 162), the CPU 42 selects specific content from the content stored in the accessed device (Step 163). When the authentication fails (No), the CPU 42 determines whether or not there is an instruction from the user to shift to an operation mode other than the content reproduction operation (step 164), and when the instruction is present (Yes). to shift to other modes of operation.

  Here, the selection of the content is performed based on a content list displayed on a display device such as the TV 60 connected to the PVR 300. The content list will be described later.

  Subsequently, the CPU 42 determines whether to perform special reproduction or normal reproduction for the selected content based on a user operation (step 165). When instructed to perform normal reproduction (No), the CPU 42 shifts to the normal reproduction mode of the content and performs normal reproduction (step 167).

  If special playback is instructed in step 165 (Yes), the CPU 42 determines whether metadata exists for the selected content (step 166). When it is determined that the metadata exists (Yes), the CPU 42 receives the metadata and executes special reproduction of the selected content based on the metadata (step 179).

  If it is determined in step 166 that there is no metadata (No), the CPU 42 shifts to the metadata generation operation mode (step 168). Then, the CPU 42 searches for the device corresponding to the metadata generation for the selected content in the same manner as the processing of FIG. 5 (step 169). In this case, when there are a plurality of corresponding devices, the device that minimizes the error rate and the delay time is selected based on the test data, as described above.

  If there is a device corresponding to the metadata generation (Yes in Step 170), the CPU 42 checks whether or not the selected content exists in the content storage device at that time (Step 172), and if it exists. Is instructed to generate metadata to the selected device (step 178). Then, the CPU 42 receives the generated metadata (step 178), and executes special reproduction of the content using the metadata (step 179).

  If it is determined in step 170 that there is no corresponding device, the CPU 42 displays a warning similar to that described above (step 173) and prompts the user to instruct whether or not to perform normal playback of the content (step 173). Step 174). When the normal reproduction is instructed (Yes), the CPU 42 shifts to the normal reproduction mode (step 167). When normal reproduction is not instructed (No), the CPU 42 ends the process.

  If it is determined in step 175 that there is no content (No), the CPU 42 displays a warning to that effect (step 177) and ends the process.

  FIG. 17 is a diagram conceptually illustrating the metadata generation process in the manual described above. In this figure, the configuration of the devices on the network 50 is the same as that shown in FIG.

  As shown in FIG. 15, compared to FIG. 15, the individual metadata A for the content A stored in the PVR 200 is not stored in the PVR 200 but is directly received by the PVR 300 instructed to generate metadata. used in special reproduction processing, and the like. Similarly, the individual metadata B for the content B stored in the PVR 400 is not stored in the PVR 400 but is directly received by the PVR 300 and used for special reproduction processing or the like.

(Content classification process)
Next, content classification processing existing in each device on the network 50 will be described. As a premise of the content classification processing, it is assumed that the above-mentioned classification metadata is generated and stored in each device on the network 50 by the above-described metadata generation processing together with the content. The classification metadata is data related to the content genre described above. It is assumed that the classification metadata has already been generated in the content genre determination process in step 67 of FIG. 5 described above.

  FIG. 18 is a flowchart showing a flow of content classification processing by the PVR 300. As shown in the figure, the CPU 42 receives access authentication from each device on the network 50 in the same manner as described above (step 181). When the authentication is passed (Yes in Step 182), the CPU 42 detects the content stored in each device (Step 183). The target of the content detection process includes the own device (PVR300).

  When the authentication is not passed (No), the CPU 42 determines whether or not the user has instructed the transition to the other operation mode (Step 186), and when the transition is instructed (Yes), the other operation is performed. If the mode is entered and no instruction is given (No), the process returns to step 181.

  When the content is detected in step 183, the CPU 42 determines whether or not the detected content is new content that has not yet been classified (step 184). When it is determined that the content is content that is already subject to classification processing (No), the CPU 42 executes the processing from step 186 onward.

  When it is determined that the content is content that has not yet been classified (Yes), the CPU 42 detects the genre of the content based on the classification metadata (step 185). Here, when the classification metadata is not generated for the content, the generation of the classification metadata is instructed to other devices on the network 50 according to the above-described metadata generation processing. In generating the classification metadata for the private content, the camera shake feature extraction process is also performed as described above.

  Subsequently, the CPU 42 determines whether or not the same genre as the detected genre or a similar genre exists for other contents (step 187). In order to determine the similarity of the genre, the PVR 300 may store data describing the similarity relationship in advance.

  If it is determined in step 187 that there is an identical or similar genre (Yes), the CPU 42 adds the content to the existing genre and adds a classification ID (step 188). On the other hand, when it is determined that there is no same or similar genre (No), the CPU 42 adds the content to a new genre and adds a new classification ID (step 189). The classification ID includes discrimination data for the private content or the broadcast content.

  The CPU 42 generates a content list for content on the network 50 including those stored in the PVR 300 by using the classification ID generated by the above classification processing, and uses the content list on a display device such as the TV 60. it can be displayed.

  FIG. 19 is a diagram showing a display example of the generated content list. As shown in the figure, in the content list, a plurality of contents are classified into the classification ID private contents and the television contents, and a thumbnail 91 and a title 92 of the contents are displayed for each classification. Here, information (such as an athletic meet, a trip, etc.) indicating the content of the private content may be displayed. The information is generated by, for example, user input when the private content is recorded or transferred to another device. For television content, the genre or sub-genre (baseball, song program, etc.) is displayed based on the classification ID.

  When the user performs an operation of selecting a specific content for reproduction on the content list, the CPU 42 can receive the content from the content storage device in which the content is stored and reproduce it. .

(Content list display control processing according to traffic conditions)
Here, in the present embodiment, the PVR 300 can indicate whether or not each content on the content list can be smoothly reproduced on the displayed content list. That is, the PVR 300 allows the user to grasp whether smooth playback is possible or not according to the traffic status (access status) of the network 50 by changing the status of the thumbnail corresponding to each content. Furthermore, when new content is added on the network 50 or when content no longer exists on the network 50, the PVR 300 can reflect the situation on the content list and allow the user to grasp the situation. . Hereinafter, details of the processing will be described.

FIG. 20 is a flowchart showing the flow of content list display control processing in accordance with the traffic status and the like.
As shown in the figure, the CPU 42 first initializes a counter n for discrimination of each content to 0 (step 191). Subsequently, the CPU 42 receives access authentication from each device on the network 50 (step 192), and when the authentication passes (Yes in step 193), detects the content stored in each device (step 194). The detection of the content is also executed for the content stored in the PVR 300 itself. Therefore, in the content list, all contents stored in the PVR 300 and other devices are displayed. As a result, the user does not have to be aware of whether the content is stored in the device operated by the user or the content stored in another device.

  If the authentication is not passed in step 193 (No), the CPU 42 determines whether or not the content list display operation mode is continuing (step 198), and proceeds to step 202 if continuing. When the end of the display operation mode is instructed by the user (No), it is determined whether or not the user has instructed the transition to another operation mode (Step 199). When instructed (Yes), the other to shift to modes of operation. On the other hand, when the shift to another operation mode is not instructed (No), the CPU 42 returns to step 192 and repeats the subsequent processing.

  When the content is detected in step 194, the CPU 42 determines whether or not there is content that is not yet the target of the content list display control process (step 195). When it is determined that there is content that is not the target of the processing (Yes), the CPU 42 sets the displayable flag indicating whether the content (n) can be displayed on the content list to ON. (step 196).

  Subsequently, the CPU 42 determines whether or not all contents on the network 50 have been detected (step 197). If there is still content to be detected (No), the counter n is incremented and the above steps are performed. The process after 194 is repeated.

  If it is determined that all contents have been detected (Yes), the CPU 42 determines whether or not the content list display operation mode is continuing (step 201). A counter k for detecting the access state is initialized to 0 (step 202). In step 201, when the user instructs the end of the display operation mode (No), the same processing as in step 199 is executed.

  When the counter k is initially set, the CPU 42 detects the access state of the content (k) (step 203). In other words, the CPU 42 estimates the error rate of the content stored in each device by transmitting the above-described test data to each device, receiving the response, and detecting the traffic situation (error rate). If the predetermined threshold value is exceeded, it is determined that the content cannot be reproduced smoothly (is not accessible).

  Subsequently, for the content (k) determined to be accessible, the CPU 42 displays the thumbnails in the normal state on the content list (step 205), and when it is determined that access is impossible (No) The thumbnail state is changed and displayed (step 208).

  Subsequently, the CPU 42 increments the counter k, and repeats the above processing for all the detected contents (n contents) (step 207). Then, the CPU 42 determines whether or not a predetermined timing for authenticating each device on the network 50 has arrived (step 209). When it is determined that the timing has not arrived (No), the CPU 42 returns to Step 201, and when it is determined that it has arrived (Yes), the CPU 42 returns to Step 192 to execute the authentication process.

  Through the above processing, the thumbnail is displayed in a changed state when smooth playback of the content is impossible according to the traffic situation on the network 50. Further, the CPU 42 repeats the authentication process at a predetermined timing, so that when new content is added on the network 50 or when the content is disconnected from the network 50, the CPU 42 displays the content list according to the state of the content. You can add or delete thumbnails.

  FIG. 21 is a diagram showing a state in which the thumbnail state changes due to the content list display control process. FIG. 4A shows the state before the change, and FIG. 4B shows the state after the change. As shown in FIG. 6A, the thumbnail 91 of the content 2a that has been normally displayed is displayed as a result of the deterioration of traffic conditions or the content 2a being disconnected from the network 50, as shown in FIG. , Shaded (gray). The change in the display state of the thumbnail is not limited to the shaded state, and may be performed by, for example, a change in saturation or brightness.

  In the flowchart of FIG. 20, one predetermined threshold value regarding the error rate is set. However, a plurality of threshold values may be set, and the display change may be performed step by step according to the error rate.

  Further, when the traffic situation is improved and the error rate is lowered, the CPU 42 may change the state of the thumbnail to the normal display and display some mark indicating it in the vicinity of the thumbnail. At this time, the CPU 42 may cause the user to select content that the user desires to reproduce on the content list in advance, and display the mark only for the selected content.

(Access control processing using face identification metadata)
In the present embodiment, each device on the network 50 can authenticate the access authority to the content for each device depending on whether the user's face of the access source device is reflected in the content. . In other words, when each device has access to the content stored by itself, the device permits access if the user's face of the accessing device is reflected in the content, and permits otherwise. Can do. This is based on the idea that a user should be allowed to access content that the user himself / herself shows. The access control process will be described below. In this access control process, face identification metadata generated in the metadata generation process is used.

  FIG. 22 is a flowchart showing the flow of access control processing based on the face identification metadata. In the figure, a case will be described in which the PVR 100 corresponding to the metadata generation process generates data indicating access permission / denial for all contents on the network 50.

  As shown in the figure, the CPU 12 of the PVR 100 accepts registration of the face image of the user A of the other device from the other device (step 211). The face image may be taken by a camera of the other device, or may be taken by the user A using a digital camera or a mobile phone with the user A and transmitted via the other device. It may be what was done.

  When the face image is registered, the CPU 12 extracts face feature data (feature vector) such as eyes, nose, mouth, contour, texture feature and the like from the face image data. For the extraction of the facial feature data, for example, feature filters, luminance distribution information, skin color information, and the like corresponding to the positional relationship of each part of the face are used.

  Subsequently, the CPU 12 receives access authentication from each device on the network 50 (step 212). When the authentication passes (Yes in step 213), the CPU 12 detects content from each device (step 214). Each device that is the target of content detection includes its own device (PVR 100). If the authentication is not successful (No), the CPU 12 determines whether or not the user of the PVR 100 is instructed to move to another operation mode (step 219). If the instruction is received (Yes), the other If there is no instruction (No), the process returns to step 212.

  When the content is detected, the CPU 12 determines whether or not there is content that is not yet subject to the access control process (step 215). If the content does not exist, the process proceeds to step 219. When the content exists, the CPU 12 detects a face image and a facial feature from the content. For detecting the face image, a known method such as skin color detection is used. The detection of the facial feature is the same as the processing for the registered facial image. Here, each detection process is not necessary when the face identification metadata is generated, and the face identification metadata can be used as it is for the access control process. If a face image is not detected by the detection process (No in step 217), the process returns to step 212 and the process is repeated for other devices.

  When any face image is detected in step 216 (Yes in step 217), the CPU 12 collates the face feature data of the registered face image with the face feature data detected from the content, and registers the registered face image. It is determined whether the face of user A exists in the content (step 218).

  When it is determined that the face of the user A exists in the content (Yes in Step 220), the CPU 12 generates permission data for permitting access from the device of the user A for the content (Step 221). Then, for example, the CPU 12 transfers the thumbnail of the face image detected from the content to the user A's device (step 222). The thumbnail may be transferred as a content list. Thus, when the user A device is in the display operation mode, accessible content is displayed as a content list, so that the user A device immediately accesses the content on the list and reproduces the content. It becomes possible.

  Then, the CPU 12 determines whether or not the analysis has been completed for all the contents that are to be newly subjected to access control (step 223). When the analysis has been completed (Yes), the processing is terminated, and when it has not been completed. In (No), it returns to said 212 and repeats subsequent processes.

  Although the above processing is a mode for automatically generating the access permission data, the permission data may be manually performed. FIG. 23 is a table showing an outline of the access control process corresponding to each manual / automatic operation mode.

  As shown in the figure, in the automatic mode, the CPU 12 automatically notifies the face shown in the content as described above when the face is registered in the device. In this case, as described above, the thumbnail is transferred to, for example, a cache memory of the user's device. Further, in the manual mode, the registration source device sets an operation mode for detecting whether or not content showing the user exists on the network 50 based on the operation of the user of the device. In this case, when the presence / absence of the face image is detected by the search for the face image, the thumbnail is transferred to the cache memory of the registration source device.

  With the above processing, it is possible to authenticate the access authority to each content on the network 50 using the face image as a key, and more intuitive authentication is possible as compared with the case of using an ID or password.

  Here, the detection processing of the face image and the face feature data in each content is executed by the recorded device when the content is recorded, and the detected face feature data may be stored as metadata together with the content. Good. As a result, each device can immediately authenticate the access request.

  Further, not only the user shown in the content but also the creator of the content may be permitted access. In this case, the face feature data detected from the face image of the creator of the content is stored as metadata when the content is recorded (created). At the time of the analysis, in addition to the collation with the facial feature data of the facial image in the content, the collation with the facial feature data of the stored creator's facial image is also performed. As a result, it is possible to prevent the content creator from being unable to reproduce its own content.

[Summary]
As described above, according to the present embodiment, each device on the network 50 searches for other devices on the network that can do this even if the device itself cannot generate metadata. Metadata can be generated, and the metadata can be used for various processes.

  In addition, each device changes whether or not the content corresponding to the thumbnail image can be smoothly reproduced by changing the state of the thumbnail image on the content list according to the error rate estimated when the content is reproduced. The user can intuitively grasp it. Accordingly, each device can prevent a situation in which the user reproduces content that cannot be smoothly reproduced due to a bad traffic situation and feels uncomfortable.

  Furthermore, when each device includes a face image that matches a face image transmitted from another device, even if the content is not created by the user of the other device, Access to the content from other devices can be permitted.

[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 PVR 300 instructs the PVR 100 to generate metadata of content stored in another device has been described. However, for the content stored by the PVR 300 itself, test data is itself transmitted to the PVR 100. May be instructed to generate metadata.

  In the above-described embodiment, the case where content is stored in a storage device such as an HDD has been described. However, the present invention is also applied to content stored in a general-purpose recording medium such as a BD or DVD. be able to.

  The various metadata described in the above embodiment is merely an example, and the present invention can be applied to any metadata corresponding to any operation.

  In the above-described embodiment, the thumbnail display change process according to the traffic situation on the content list has been described on the assumption that the content classification process has been performed, but of course, the content classification process has not been performed. The display change may be executed even in the state.

  In the above-mentioned embodiment, the example which applied this invention to PVR was demonstrated. However, the present invention is applicable to all electronic devices such as a PC (Personal Computer), a television device, a game device, a mobile phone, and other AV (Audio / Visual) devices.

7, 37 ... Playback unit 8, 38 ... HDD
11, 41 ... Communication unit 12, 42 ... CPU
14, 44 ... RAM
15, 45 ... Operation input unit 16, 46 ... Graphic control unit 20 ... Feature extraction circuit 50 ... Network 60 ... TV
73 ... Data for operation mode 74 ... Data for processing 75 ... Data for error processing 91 ... Thumbnail 100, 200, 300, 400, 500 ... PVR

Claims (6)

A storage unit for storing content;
A communication unit that receives first face image data from another device on the network;
First facial feature data is extracted from the received first facial image data, second facial image data is detected from the stored content, and second facial feature data is detected from the second facial image data. Data is extracted, and it is determined whether or not the first face feature data and the second face feature data match, and it is determined that the first face feature data and the second face feature data match. And a control unit that generates access permission data for permitting access to the content from the other device. The electronic device according to claim 1,
The control unit executes detection of the second face image data and extraction of the second face feature data when storing the content in the storage unit, and the second face feature data together with the content Electronic equipment stored in the storage unit. The electronic device according to claim 2,
The storage unit stores third facial image data indicating a creator of the stored content and third facial feature data extracted from the third facial image data together with the content,
The controller determines whether or not the first face feature data and the third face feature data match, and if the first face feature data and the third face feature data match, An electronic device that generates the access permission data when it is determined. The electronic device according to claim 2,
The control unit generates a list of contents for which the access permission data is generated, transmits the list to the other device by the communication unit, and reproduces one content on the list from the other device. An electronic device that receives a reproduction request signal that requests the one content and transmits the one content to the other device in response to the reproduction request signal. Remember the content,
Receive first face image data from other devices on the network,
Extracting first facial feature data from the received first facial image data;
Detecting second face image data from the stored content;
Extracting second facial feature data from the second facial image data;
Determining whether the first facial feature data and the second facial feature data match;
An access control method for generating access permission data permitting access to the content from the other device when it is determined that the first face feature data matches the second face feature data. Electronic equipment,
Storing the content;
Receiving first face image data from another device on the network;
Extracting first facial feature data from the received first facial image data;
Detecting second face image data from the stored content;
Extracting second facial feature data from the second facial image data;
Determining whether the first facial feature data and the second facial feature data match;
A program for executing, when it is determined that the first face feature data matches the second face feature data, generating access permission data for permitting access to the content from the other device.