JP2012226435A - Network system, control method for device, and controller - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a network system, a control method for device, and a controller, which allow effective control of both of devices with a high degree and a lower degree of necessity for preventing false recognition of a user.SOLUTION: A controller 100 includes: a communication interface 105 for communicating with at least one camera and plural devices; a memory 101 for storing information for identifying a person, and storing a probability and a first control instruction in relation to each of the plural devices; and a processor 110. The processor receives an image including the person from the at least one camera via the communication interface, and, if the probability of the person included in the image being a person identified by the information is equal to or more than the probability related to an individual device, for each of the plural devices, transmits the first control instruction related to the device, to the device via the communication interface.

Description

  The present invention relates to a network system including a controller and a device controlled by the controller, a device control method, and a controller. In particular, the present invention relates to a controller technique for controlling a plurality of devices based on an image obtained from at least one camera.

  A controller for controlling a plurality of devices is known. Some of these controllers control devices according to the user's recognition result.

  For example, Japanese Patent Application Laid-Open No. 2006-243849 (Patent Document 1) discloses a device control apparatus and a method thereof. According to Japanese Patent Laying-Open No. 2006-243849 (Patent Document 1), the device control apparatus includes a face recognition processing unit, a device setting unit, and a dialogue processing unit, and acquires and acquires personal data related to a user's face image. The personal data is compared with the registered personal dictionary data, the person corresponding to the acquired personal data is recognized, and the registered face image corresponding to the recognized person is based on the registered personal dictionary data. The confirmation information as to whether the displayed person matches the user is received from the user, and is set in the device environment parameter corresponding to the confirmed person.

JP 2006-243849 A

  However, when an image from the camera is used, there is a possibility that the user is erroneously recognized. Among the devices controlled by the controller, there are devices that are highly necessary to avoid misrecognition and devices that are low, but the conventional controller does not take that point into consideration.

  The present invention has been made to solve such a problem, and an object of the present invention is to control a network system and a device capable of effectively controlling a device that is highly necessary to avoid erroneous recognition by a user and a device that is low in necessity. A method and controller are provided.

  According to an aspect of the present invention, a network system is provided that includes at least one camera for photographing a person, a plurality of devices that operate in response to a control command, and a controller. The controller stores a communication interface for communicating with at least one camera and a plurality of devices, information for specifying a person, and stores accuracy and a first control command in association with each of the plurality of devices. Including a memory and a processor. The processor receives an image including a person from at least one camera via a communication interface, and the accuracy that the person included in the image is a person specified by information is greater than or equal to the accuracy corresponding to the device for each of the plurality of devices. In some cases, a first control command corresponding to the device is transmitted to the device via the communication interface.

  Preferably, the memory stores the first control command in association with information for specifying a person. The processor, for each of a plurality of devices, information for identifying a device and a person via a communication interface when the accuracy that the person included in the image is a person identified by the information is greater than or equal to the accuracy corresponding to the device. A first control command corresponding to is transmitted to the device.

  Preferably, the at least one camera includes a plurality of cameras. The memory stores a correspondence relationship between the plurality of cameras and the plurality of devices. The processor, for each device corresponding to a camera that has transmitted an image including a person among a plurality of devices, when the probability that the person included in the image is a person specified by the information is greater than or equal to the accuracy corresponding to the device The first control command corresponding to the device is transmitted to the device via the communication interface.

  Preferably, the information for specifying a person includes feature amounts created from a plurality of images obtained from a plurality of cameras.

  Preferably, the memory stores the second control command in association with at least one of the plurality of devices. The processor, for each of the plurality of devices, when the accuracy that the person included in the image is a person specified by the information is less than the accuracy corresponding to the device, a second control command corresponding to the device via the communication interface To the device.

  According to another aspect of the present invention, at least one camera, a plurality of devices, information for specifying a person is stored, and an accuracy and a first control command are stored in association with each of the plurality of devices. And a controller for controlling a device in a network system. In the device control method, at least one camera captures a person, a controller receives an image including the person from at least one camera, and a controller is included in the image for each of the plurality of devices. A step of transmitting a first control command corresponding to the device to the device when the probability that the person is a person specified by the information is greater than or equal to the accuracy corresponding to the device; And a step that operates in response.

  According to another aspect of the invention, a communication interface for communicating with at least one camera and a plurality of devices, information for specifying a person is stored, and the accuracy and the first are associated with each of the plurality of devices. A controller is provided that includes a memory for storing the control instructions and a processor. The processor receives an image including a person from at least one camera via a communication interface, and the accuracy that the person included in the image is a person specified by information is greater than or equal to the accuracy corresponding to the device for each of the plurality of devices. In some cases, a first control command corresponding to the device is transmitted to the device via the communication interface.

  According to another aspect of the present invention, a communication interface, a memory that stores information for specifying a person and stores accuracy and a first control instruction in association with each of a plurality of devices, a processor, There is provided a method of controlling a device in a controller including: The device control method includes a step in which a processor receives an image including a person from at least one camera via a communication interface, and a person in which a person included in the image is specified by information for each of a plurality of devices. The first control command corresponding to the device is transmitted to the device via the communication interface when the certain accuracy is equal to or higher than the accuracy corresponding to the device.

  As described above, according to the present invention, there are provided a network system, a device control method, and a controller that can effectively control a device that is highly necessary to avoid misrecognition by a user and a device that is low.

It is an image figure which shows the whole structure of the network system 1 which concerns on this Embodiment. It is a block diagram showing the hardware constitutions of the controller 100 which concerns on this Embodiment. It is an image figure which shows the data structure of the apparatus database 101B which concerns on Embodiment 1. FIG. It is an image figure which shows the data structure of user database 101C which concerns on Embodiment 1. FIG. It is a block diagram showing the structure of television 200C according to the present embodiment. It is a block diagram showing the structure of the camera 300 which concerns on this Embodiment. It is a flowchart which shows the process sequence of the control process in the controller 100 which concerns on this Embodiment. It is an image figure which shows the data structure of apparatus database 101D which concerns on Embodiment 2. FIG. 6 is a flowchart illustrating a processing procedure of control processing in a controller 100 according to Embodiment 2.

  Hereinafter, embodiments of the present invention will be described with reference to the drawings. In the following description, the same parts are denoted by the same reference numerals. Their names and functions are also the same. Therefore, detailed description thereof will not be repeated.

[Embodiment 1]
<Overall configuration of network system>
First, the overall configuration of the network system according to the present embodiment will be described. FIG. 1 is an image diagram showing an overall configuration of a network system 1 according to the present embodiment.

  Referring to FIG. 1, network system 1 according to the present embodiment is installed in, for example, a house or an office. The network system 1 includes a key 200A and an illumination 200B arranged at the entrance, a television 200C and an illumination 200D and an air conditioner 200E arranged in a living room, and a key 200F and an illumination 200G arranged in a bath. Hereinafter, the key 200A, the lighting 200B, the television 200C, the lighting 200D, the air conditioner 200E, the key 200F, the lighting 200G, and other home appliances are collectively referred to as the device 200.

  The network system 1 includes cameras 300A and 300B arranged at the entrance, a camera 300C arranged in the living room, and a camera 300D arranged in the bath. Hereinafter, the cameras 300A, 300B, 300C, and 300D are collectively referred to as the camera 300.

  The network system 1 includes a controller 100 for controlling a key 200A, an illumination 200B, a television 200C, an illumination 200D, an air conditioner 200E, a key 200F, an illumination 200G, and other devices. The controller 100 can perform data communication with the key 200A, the lighting 200B, the television 200C, the lighting 200D, the air conditioner 200E, the key 200F, the lighting 200G, and other devices via the wired or wireless network 400. The controller 100 uses a wired LAN (Local Area Network), a wireless LAN, a PLC (Power Line Communications), Bluetooth (registered trademark), or the like as the network 400, for example.

  The controller 100 stores data for specifying a user in advance for each user. Note that the data for specifying the user includes data of the user's face image itself obtained from the camera 300 or feature amount data obtained from the user's face image. The data for specifying the user may include data of a plurality of user face images obtained from each of a plurality of cameras, feature amount data obtained from a plurality of user face images, and the like. Hereinafter, data for specifying a user stored in advance is referred to as storage specifying data.

  In addition, the controller 100 stores a correspondence relationship between the device 200 and the camera 300. More specifically, the cameras 300A and 300B for photographing a person outside the door of the entrance, the key 200A arranged at the entrance, and the illumination 200B are associated with each other. A camera 300B for photographing a person in the living room, a television 200C, an illumination 200D, and an air conditioner 200E arranged in the living room are associated with each other. A camera 300D for photographing a person in the bath or a person outside the bath, a key 200F arranged in the bath, and an illumination 200G are associated with each other.

  The controller 100 stores the accuracy for each device 200 in advance. In the controller 100, high accuracy is associated with a device that is highly necessary to avoid misrecognition of a user, and low accuracy is associated with a device that is less necessary to avoid misrecognition of a user. The controller 100 stores a user and a control command in association with each other, and stores a guest (person other than the user) and a control command in association with each other.

<Overview of network system operation>
Next, an outline of the operation of the network system 1 according to the present embodiment will be described. With reference to FIG. 1, first, the camera 300 transmits periodically captured images to the controller 100. However, when the camera 300 detects a person by using a human sensor, the camera 300 may take a picture of the person and transmit the photographed image to the controller 100.

  The controller 100 creates specific data (acquired specific data) based on the face image of the person included in the image received from the camera 300. The controller 100 calculates the degree of similarity between the storage specific data and the acquired specific data (the probability that the detected person is a registered user) for each of a plurality of storage specific data stored in advance. The controller 100 specifies the user (specific user) by specifying the storage specifying data that is most similar to the acquired specifying data.

  The controller 100 specifies at least one device 200 corresponding to the camera 300. The controller 100 executes the following operation for each at least one device 200 corresponding to the camera 300.

  The controller 100 determines whether the similarity between the storage specific data most similar to the acquired specific data and the acquired specific data is equal to or higher than the accuracy of the device 200. When the similarity is equal to or higher than the accuracy of the device 200, the controller 100 transmits a control command corresponding to the specific user to the device 200.

  On the other hand, when the similarity is less than the accuracy of the device 200, the controller 100 transmits a control command corresponding to the guest to the device 200. However, if the degree of similarity is less than the accuracy of the device 200, the controller 100 may not transmit a control command to the device 200. That is, the controller 100 may ignore the captured image from the camera 300 regarding the device 200.

  As a result, in the network system 1 according to the present embodiment, it is possible to effectively control devices that are highly necessary and devices that are low in need of avoiding erroneous recognition by the user.

  More specifically, there is a possibility of misrecognizing a user regarding automatic control of equipment using personal recognition based on an image from a camera (sensor). And control which a user does not intend based on the result of misrecognition may be performed. The magnitude of the influence of misrecognition differs for each device to be controlled.

  For example, a device that requires high security control may cause a serious malfunction. The need to avoid misrecognition of the entrance key 200A is higher than the need to avoid misrecognition of the room key 200F. On the other hand, a device that controls comfort is not likely to cause a big problem even if it is misrecognized. Rather, it is inconvenient if the configuration is such that the user is not easily recognized in order to avoid erroneous recognition.

  The network system 1 according to the present embodiment can achieve the effects that cannot be achieved as described above.

  Hereinafter, a specific configuration of the network system 1 for realizing such a function will be described in detail.

<Configuration of Controller 100>
Next, an aspect of the configuration of the controller 100 according to this embodiment will be described. FIG. 2 is a block diagram showing a hardware configuration of controller 100 according to the present embodiment.

  The controller 100 includes a memory 101, a display 102, a tablet 103, buttons 104, a communication interface 105, a speaker 107, a clock 108, and a CPU (Central Processing Unit) 110.

  The memory 101 is realized by various types of RAM (Random Access Memory), ROM (Read-Only Memory), a hard disk, and the like. The memory 101 stores a control program executed by the CPU 110, storage specific data 101A, a device database 101B, a user database 101C, and the like.

  As described above, the storage specifying data 101A is data for specifying a user for each user. The storage specific data 101A includes, for each user, data of the user's face image itself obtained from the camera 300 and / or feature amount data obtained from the user's face image. The storage specifying data 101A also includes data of a plurality of face images of the user obtained from each of a plurality of cameras or feature amount data obtained from the plurality of face images of the user.

  The memory 101 stores storage specifying data 101A for each of various types corresponding to the type of camera 300 used for recognition and the number of cameras 300 used for recognition. In other words, the memory 101 stores the storage specific data 101A in association with the type of specific data and the user ID (or user name).

  FIG. 3 is an image diagram showing a data structure of device database 101B according to the present embodiment. Referring to FIG. 3, device database 101B includes, for each device, device ID, device name, accuracy for executing a control command corresponding to the user, corresponding camera ID, specific data type, or specific data address. Is stored.

  For example, the entrance key 200A is set to have a higher corresponding accuracy because the disadvantage of misrecognizing the user is greater than the advantage of easily recognizing the user. On the other hand, the living room lighting 200 </ b> D has a higher merit that it is easier to recognize the user than a demerit that misrecognizes the user, so the corresponding accuracy is set low.

  FIG. 4 is an image diagram showing a data structure of user database 101C according to the present embodiment. Referring to FIG. 4, user database 101C stores a user ID, a user name, and a control command for each device for each user. In the present embodiment, a control command for each device corresponding to “guest” is stored as a command to be executed when the similarity between the storage specific data and the acquired specific data is less than the accuracy. Note that the user database 101C may store NULL as a control command. That is, for the device 200 corresponding to NULL, the controller 100 may not transmit a control command when the similarity between the storage specific data and the acquired specific data is less than the accuracy.

  Returning to FIG. 2, the display 102 displays various types of information under the control of the CPU 110. The tablet 103 detects a touch operation with a user's finger and inputs touch coordinates or the like to the CPU 110. The CPU 110 receives a command from the user via the tablet 103.

  In the present embodiment, a tablet 103 is laid on the surface of the display 102. That is, in the present embodiment, display 102 and tablet 103 constitute touch panel 106.

  The button 104 is disposed on the surface of the controller 100. A plurality of buttons such as a numeric keypad may be arranged on the controller 100. The button 104 receives a command from the user. The button 104 inputs a command from the user to the CPU 110.

  The communication interface 105 is controlled by the CPU 110 to transmit / receive data to / from the key 200A, the lighting 200B, the television 200C, the lighting 200D, the air conditioner 200E, the key 200F, the lighting 200G, and other home appliances via the network 400.

  The speaker 107 outputs sound by being controlled by the CPU 110. For example, the CPU 110 notifies that when transmitting a control command to the device 200.

  The clock 108 measures the current time and the current date. The CPU 110 can acquire the current time and date based on the data from the clock 108.

  The CPU 110 implements the processing shown in FIG. 7 (FIG. 9) by executing various programs stored in the memory 101. The processing in the controller 100 is realized by each hardware and software executed by the CPU 110. Such software may be stored in the memory 101 in advance. The software may be stored in a storage medium and distributed as a program product. Alternatively, the software may be provided as a program product that can be downloaded by an information provider connected to the so-called Internet.

  Such software is read from the storage medium by using a reading device (not shown), or downloaded by using the communication interface 105 and temporarily stored in the memory 101. The CPU 110 stores the software in the form of an executable program in the memory 101 and then executes the program.

  As storage media, CD-ROM (Compact Disc-Read Only Memory), DVD-ROM (Digital Versatile Disk-Read Only Memory), USB (Universal Serial Bus) memory, memory card, FD (Flexible Disk), hard disk , Magnetic tape, cassette tape, MO (Magnetic Optical Disc), MD (Mini Disc), IC (Integrated Circuit) card (excluding memory card), optical card, mask ROM, EPROM, EEPROM (Electronically Erasable Programmable Read-Only Memory) And the like, for example, a medium for storing the program in a nonvolatile manner.

  The program here includes not only a program directly executable by the CPU but also a program in a source program format, a compressed program, an encrypted program, and the like.

  CPU 110 receives a captured image from camera 300 via communication interface 105. The CPU 110 creates feature amount data (acquisition specific data) based on a person's face image included in the captured image.

  CPU110 reads the feature-value data (memory | storage specific data 101A) for every user from the memory 101. FIG. CPU110 calculates the similarity (accuracy) of storage specific data and acquisition specific data for every user. CPU110 specifies a user (specific user) by specifying the memory | storage specific data most similar to acquisition specific data.

  The CPU 110 identifies at least one device 200 corresponding to the camera 300 and the accuracy corresponding to the device 200 with reference to the device database 101B. CPU110 performs the following operation | movement for every at least 1 apparatus 200. FIG.

  The CPU 110 determines whether the similarity between the storage specific data most similar to the acquired specific data and the acquired specific data is equal to or higher than the accuracy corresponding to the device 200. When the similarity is equal to or higher than the accuracy of the device 200, the CPU 110 reads a control command corresponding to the specific user and the device 200 from the user database 101C. The CPU 110 transmits a control command corresponding to the specific user to the device 200 via the communication interface 105.

  On the other hand, when the similarity is less than the accuracy of the device 200, the CPU 110 reads out a control command corresponding to the guest and the device 200 from the user database 101C. The CPU 110 transmits a control command corresponding to the guest to the device 200 via the communication interface 105.

  However, when the degree of similarity is less than the accuracy of the device 200, the CPU 110 may not transmit a control command to the device 200. That is, the CPU 110 may ignore the data from the camera 300 regarding the device 200. That is, the user database 101C does not have to store data related to guests.

<Configuration of TV 200C>
A configuration of television 200C as an example of device 200 according to the present embodiment will be described. FIG. 5 is a block diagram showing a configuration of television 200C according to the present embodiment.

  Referring to FIG. 5, television 200C includes a memory 201, a display 202, a button 204, a communication interface 205, a speaker 207, a remote control receiving unit 209, and a CPU 510.

  The memory 201 can be realized in the same manner as the memory 101 of the controller 100. The memory 201 stores a control program executed by the CPU 210, data received from the controller 100, and the like.

  The display 202 is controlled by the CPU 210. More specifically, the display 202 displays a still image or a moving image based on data from a TV tuner or VRAM (Video RAM) (not shown).

  The button 204 is disposed on the surface of the television 200C. The television 200C may include a plurality of buttons 204 such as a determination key, a direction key, and a numeric keypad. The button 204 receives a command from the user and inputs the command to the CPU 210.

  The communication interface 205 transmits and receives data to and from the controller 100 via the network 400 under the control of the CPU 210. The communication interface 205 transmits and receives data to and from the controller 100 by using a wireless LAN, ZigBee (registered trademark), Bluetooth (registered trademark), wired LAN (Local Area Network), or PLC (Power Line Communications).

  For example, the communication interface 205 according to the present embodiment inputs a control command received from the controller 100 to the CPU 210.

  The speaker 207 outputs sound based on a command from the CPU 210. For example, the CPU 210 causes the speaker 207 to output sound based on the sound data.

  The remote control receiving unit 209 receives a control signal from the controller 100. For example, the remote control receiving unit 209 receives a signal from the controller 100 by using infrared rays, a wireless LAN, ZigBee (registered trademark), Bluetooth (registered trademark), or the like.

  The CPU 210 executes various types of information processing by executing various programs stored in the memory 201. CPU 110 controls each unit of television 200 </ b> C based on a control command input via button 204, communication interface 205, or remote control receiving unit 209.

<About other devices 200>
Other devices 200 according to the present embodiment also have an input unit (button 204 or remote control reception unit 209 or touch panel) for receiving a control command from the user, and controller 100 as in television 200C shown in FIG. It is only necessary to have a communication interface 205 for receiving a control command and a CPU 210 for executing a control command from the button 204, the remote control receiving unit 209, or the controller 100.

<Configuration of Camera 300>
One aspect of the configuration of the camera 300 according to this embodiment will be described. FIG. 6 is a block diagram showing a configuration of camera 300 according to the present embodiment.

  Referring to FIG. 6, camera 300 includes a memory 301, a sensor 302, a communication interface 305, and a CPU 310. The CPU 310 periodically photographs a person using the sensor 302. The CPU 310 sequentially transmits captured images to the controller 100 via the communication interface 305. Note that the CPU 310 may transmit data of the captured image itself to the controller 100 via the communication interface 305, or may extract face image data from the captured image and transmit the face image data to the controller 100. Also good.

  The camera 300 may be equipped with a human sensor. In this case, the CPU 310 operates (photographs) the sensor 302 when a person is detected by the human sensor. The CPU 310 can also temporarily store the captured image in the memory 301.

<Control processing in controller 100>
Next, control processing in the controller 100 according to the present embodiment will be described. FIG. 7 is a flowchart showing a processing procedure of control processing in the controller 100 according to the present embodiment.

  Referring to FIG. 7, CPU 110 determines whether a captured image has been received from camera 300 via communication interface 105 (step S <b> 102). CPU110 performs the process of step S102, when the picked-up image is not received (when it is NO in step S102).

  When the captured image is received (YES in step S102), CPU 110 determines whether or not at least one face is included in the captured image (whether facial image data can be created from the captured image). (Step S104). If the captured image does not include a face (NO in step S104), the processing from step S102 is executed.

  When the photographed image includes a face (YES in step S104), CPU 110 refers to device database 101B and identifies device 200 corresponding to camera 300 (step S106). The CPU 110 enters the number of devices 200 corresponding to the camera in the variable N of the memory 101 (step S108).

  The CPU 110 creates acquisition specific data from the captured image. The CPU 110 compares the storage specific data 101A in the memory 101 with the acquired specific data for each user. The CPU 110 temporarily stores the user ID corresponding to the storage specific data having the highest similarity with the acquired specific data and the similarity in the memory 101 (step S110). CPU110 puts 1 into the variable n of the memory 101 (step S112).

  The CPU 110 reads the accuracy of the nth device 200 among the devices 200 corresponding to the camera 300 from the device database 101B. CPU110 judges whether the highest similarity is more than the accuracy of the nth device (step S114). When the highest similarity is not equal to or higher than the accuracy of the nth device (NO in step S114), CPU 110 determines that camera 300 has photographed the guest (step S116). That is, the CPU 110 specifies a guest ID for the nth device 200. CPU110 performs the process from step S120.

  When the highest similarity is equal to or higher than the accuracy of the n-th device (YES in step S114), CPU 110 captures the user corresponding to the stored specific data having the highest similarity with the acquired specific data. It is determined that it has been done (step S118). That is, the CPU 110 specifies the user ID of the user corresponding to the storage specific data having the highest similarity to the acquired specific data for the nth device 200.

  The CPU 110 reads a control command corresponding to the specified guest ID or user ID and the nth device 200 from the user database 101C. CPU 110 transmits the control command via communication interface 105 (step S120). CPU110 increments the variable n (step S122). CPU110 determines whether the variable n is larger than N (step S124).

  CPU110 repeats the process from step S114, when the variable n is N or less (when it is NO in step S124). On the other hand, when variable n is larger than N (YES in step S124), CPU 110 repeats the processing from step S102.

[Embodiment 2]
Next, a second embodiment of the present invention will be described. In the network system 1 according to Embodiment 1 described above, a control command is set for each device and for each user. However, the control command does not need to be associated with the user ID. In the network system 1 according to the present embodiment, a control command is associated with each device.

<Overall configuration of network system>
Since the entire configuration of the network system according to the present embodiment is the same as that of the first embodiment shown in FIG. 1, description thereof will not be repeated here. However, the controller 100 according to the present embodiment, for each device, the first control command transmitted when the similarity is greater than or equal to the accuracy, and the second control command transmitted when the similarity is less than the accuracy. The controller is different from the controller according to the first embodiment in that it stores the control command in association with each other. That is, in the present embodiment, the controller 100 does not store the user and the control command in association with each other.

<Overview of network system operation>
Next, an outline of the operation of the network system 1 according to the present embodiment will be described. With reference to FIG. 1, first, the camera 300 transmits periodically captured images to the controller 100. However, when the camera 300 detects a person by using a human sensor, the camera 300 may capture a person and send the captured image to the controller 100.

  The controller 100 creates acquisition specific data based on the face image of the person included in the image received from the camera 300. The controller 100 calculates the similarity between the storage specific data and the acquired specific data for each of the plurality of storage specific data stored in advance.

  The controller 100 specifies at least one device 200 corresponding to the camera 300. The controller 100 executes the following operation for each at least one device 200 corresponding to the camera 300.

  The controller 100 determines whether the similarity between the storage specific data most similar to the acquired specific data and the acquired specific data is equal to or higher than the accuracy of the device 200.

  When the similarity is equal to or higher than the accuracy of the device 200, the controller 100 transmits a first control command to the device 200. If the similarity is less than the accuracy of the device 200, the controller 100 transmits a second control command to the device 200. However, if the degree of similarity is less than the accuracy of the device 200, the controller 100 may not transmit a control command to the device 200. That is, the controller 100 may ignore the captured image from the camera 300 regarding the device 200.

  Thereby, also in the network system 1 according to the present embodiment, it is possible to effectively control devices that are highly necessary and devices that are low in need of avoiding erroneous recognition by the user.

  Hereinafter, a specific configuration of the network system 1 for realizing such a function will be described in detail.

<Configuration of Controller 100>
The configuration of controller 100 according to the present embodiment is similar to that of the first embodiment shown in FIG. 2, and therefore description thereof will not be repeated here. However, the data stored in the memory 101 according to the present embodiment and the operation of the CPU 110 are different from those of the first embodiment. Hereinafter, data stored in the memory 101 according to the present embodiment and the operation of the CPU 110 will be described.

  First, data stored in the memory 101 will be described. The memory 101 stores a control program executed by the CPU 110, storage specific data 101A, a device database 101D, and the like. That is, the memory 101 according to the present embodiment does not store the device database 101B and the user database 101C according to the first embodiment.

  As described above, the storage specifying data 101A is data for specifying a user for each user. The storage specific data 101A includes, for each user, data of the user's face image itself obtained from the camera 300 and / or feature amount data obtained from the user's face image. The storage specifying data 101A also includes data of a plurality of face images of the user obtained from each of a plurality of cameras or feature amount data obtained from the plurality of face images of the user.

  The memory 101 stores storage specifying data 101A for each of various types corresponding to the type of camera 300 used for recognition and the number of cameras 300 used for recognition. In other words, the memory 101 stores the storage specific data 101A in association with the type of specific data and the user ID (or user name).

  FIG. 8 is an image diagram showing a data structure of device database 101D according to the present embodiment. Referring to FIG. 8, the device database 101D includes, for each device, a device ID, a device name, an accuracy for executing the first control command, a corresponding camera ID, a specific data type or a specific data address, A first control command that is employed when the similarity is greater than or equal to the accuracy and a second control command that is employed when the similarity is less than the accuracy are stored.

  For example, the entrance key 200A is set to have a higher corresponding accuracy because the disadvantage of misrecognizing the user is greater than the advantage of easily recognizing the user. On the other hand, the living room lighting 200 </ b> D has a higher merit that it is easier to recognize the user than a demerit that misrecognizes the user, so the corresponding accuracy is set low.

  Next, the operation of the CPU 110 will be described. The CPU 110 operates as follows according to the control program stored in the memory 101.

  CPU 110 receives a captured image from camera 300 via communication interface 105. The CPU 110 creates feature amount data (acquisition specific data) based on a person's face image included in the captured image.

  CPU110 reads the feature-value data (memory | storage specific data 101A) for every user from the memory 101. FIG. CPU110 calculates the similarity (accuracy) of storage specific data and acquisition specific data for every user.

  The CPU 110 refers to the device database 101D and identifies at least one device 200 corresponding to the camera 300 and the accuracy corresponding to the device 200. CPU110 performs the following operation | movement for every at least 1 apparatus 200. FIG.

  The CPU 110 determines whether the similarity between the storage specific data most similar to the acquired specific data and the acquired specific data is equal to or higher than the accuracy corresponding to the device 200. When the similarity is equal to or higher than the accuracy of the device 200, the CPU 110 reads the first control command corresponding to the device 200 from the device database 101D. The CPU 110 transmits a first control command to the device 200 via the communication interface 105.

  On the other hand, when the similarity is less than the accuracy of the device 200, the CPU 110 reads a second control command corresponding to the device 200 from the device database 101D. The CPU 110 transmits a second control command to the device 200 via the communication interface 105.

  However, when the degree of similarity is less than the accuracy of the device 200, the CPU 110 may not transmit a control command to the device 200. That is, the CPU 110 may ignore the data from the camera 300 regarding the device 200. That is, the device database 101D does not have to store the second control command.

<Configuration of Device 200>
Since the configuration of device 200 such as television 200C according to the present embodiment is the same as that of Embodiment 1 shown in FIG. 5, description thereof will not be repeated here.

<Configuration of Camera 300>
Since the configuration of camera 300 according to the present embodiment is the same as that of the first embodiment shown in FIG. 6, description thereof will not be repeated here.

<Control processing in controller 100>
Next, control processing in the controller 100 according to the present embodiment will be described. FIG. 9 is a flowchart showing a processing procedure of control processing in the controller 100 according to the present embodiment.

  Referring to FIG. 9, CPU 110 determines whether a captured image has been received from camera 300 via communication interface 105 (step S <b> 202). CPU110 performs the process of step S202, when the picked-up image is not received (when it is NO in step S202).

  When the captured image is received (YES in step S202), CPU 110 determines whether or not at least one face is included in the captured image (whether or not face image data can be created from the captured image). (Step S204). If the photographed image does not include a face (NO in step S204), the processing from step S202 is executed.

  If the captured image includes a face (YES in step S204), CPU 110 refers to device database 101B and identifies device 200 corresponding to camera 300 (step S206). CPU 110 enters the number of devices 200 corresponding to the camera in variable N of memory 101 (step S208).

  The CPU 110 creates acquisition specific data from the captured image. The CPU 110 compares the acquired specific data with the stored specific data 101A for each user. The CPU 110 temporarily stores the user ID corresponding to the stored specific data having the highest similarity with the acquired specific data and the similarity in the memory 101 (step S210). CPU110 puts 1 into the variable n of the memory 101 (step S212).

  The CPU 110 reads the accuracy of the nth device 200 among the devices 200 corresponding to the camera 300 from the device database 101B. CPU 110 determines whether or not the highest similarity is equal to or higher than the accuracy of the n-th device (step S214). If the highest similarity is not equal to or higher than the accuracy of the nth device (NO in step S214), CPU 110 reads a second control command corresponding to nth device 200 from device database 101D. CPU 110 transmits the second control command via communication interface 105 (step S216). CPU110 performs the process from step S220.

  When the highest similarity is equal to or higher than the accuracy of the nth device, the CPU 110 reads a first control command corresponding to the nth device 200 from the device database 101D. CPU 110 transmits the first control command via communication interface 105 (step S218). CPU110 increments the variable n (step S222). CPU110 determines whether the variable n is larger than N (step S224).

  CPU110 repeats the process from step S214, when the variable n is N or less (when it is NO in step S224). On the other hand, when variable n is larger than N (when YES in step S224), CPU 110 repeats the processing from step S202.

<Other embodiments>
It goes without saying that the present invention can also be applied to a case where the controller 100 is achieved by supplying a program to a mobile phone, a device-dedicated terminal, or the like. Then, a storage medium storing a program represented by software for achieving the present invention is supplied to the system or apparatus, and the computer (or CPU or MPU) of the system or apparatus stores the program code stored in the storage medium It is possible to enjoy the effects of the present invention also by reading and executing.

  In this case, the program code itself read from the storage medium realizes the functions of the above-described embodiment, and the storage medium storing the program code constitutes the present invention.

  Further, by executing the program code read by the computer, not only the functions of the above-described embodiments are realized, but also an OS (operating system) running on the computer based on the instruction of the program code However, it is needless to say that a case where the function of the above-described embodiment is realized by performing part or all of the actual processing and the processing is included.

  Further, after the program code read from the storage medium is written to a memory provided in a function expansion board inserted into the computer or a function expansion unit connected to the computer, the function expansion is performed based on the instruction of the program code. It goes without saying that the CPU or the like provided in the board or the function expansion unit performs part or all of the actual processing and the functions of the above-described embodiments are realized by the processing.

  The embodiment disclosed this time should be considered as illustrative in all points and not restrictive. The scope of the present invention is defined by the terms of the claims, rather than the description above, and is intended to include any modifications within the scope and meaning equivalent to the terms of the claims.

  1 network system, 100 controller, 101, 201, 301 memory, 101A storage specific data, 101B, 101D device database, 101C user database, 102, 202 display, 103 tablet, 104, 204 buttons, 105, 205, 305 communication interface, 106 touch panel, 107, 207 speaker, 108 clock, 110, 210, 310 CPU, 200 equipment, 200A, 200F key, 200B, 200D, 200G lighting, 200C television, 200E air conditioner, 209 remote control receiver, 300, 300A, 300B, 300C, 300D camera, 302 sensor, 400 network.

Preferably, at least one camera is a plurality of cameras. The memory stores a correspondence relationship between the plurality of cameras and the plurality of devices. The processor, for each device corresponding to a camera that has transmitted an image including a person among a plurality of devices, when the probability that the person included in the image is a person specified by the information is greater than or equal to the accuracy corresponding to the device The first control command corresponding to the device is transmitted to the device via the communication interface.

According to another aspect of the present invention, a communication interface, a memory that stores information for specifying a person and stores accuracy and a first control instruction in association with each of a plurality of devices, a processor, There is provided a method of controlling a device in a controller including: The device control method includes a step in which a processor receives an image including a person from at least one camera via a communication interface, and a person in which a person included in the image is specified by information for each of a plurality of devices. The first control command corresponding to the device is transmitted to the device via the communication interface when the certain accuracy is equal to or higher than the accuracy corresponding to the device.
According to still another aspect of the present invention, a communication interface, a memory that stores information for specifying a person and stores an accuracy and a first control instruction in association with each of a plurality of devices, a processor, , A device control program executed by a computer is provided. The device control program includes a step of receiving an image including a person from at least one camera via a communication interface, and a probability that the person included in the image is a person identified by information for each of the plurality of devices. Is greater than the accuracy corresponding to the device, a step of transmitting the first control command corresponding to the device to the device via the communication interface is executed.

In addition, the controller 100 stores a correspondence relationship between the device 200 and the camera 300. More specifically, the cameras 300A and 300B for photographing a person outside the door of the entrance, the key 200A arranged at the entrance, and the illumination 200B are associated with each other. And the camera 300 C for photographing a person in the living room, and television 200C disposed in the living room and lighting 200D and air conditioning 200E, is associated. A camera 300D for photographing a person in the bath or a person outside the bath, a key 200F arranged in the bath, and an illumination 200G are associated with each other.

Referring to FIG. 5, television 200 </ b> C includes a memory 201, a display 202, a button 204, a communication interface 205, a speaker 207, a remote control receiving unit 209, and a CPU 210 .

CPU110 is (YES in step S204) If a face is included in the captured image, with reference to the device database 101 D, it identifies the device 200 corresponding to the camera 300 (step S206). CPU 110 enters the number of devices 200 corresponding to the camera in variable N of memory 101 (step S208).

CPU110 from the device database 101 D, reads the n-th accuracy of device 200 of the apparatus 200 corresponding to the camera 300. CPU 110 determines whether or not the highest similarity is equal to or higher than the accuracy of the n-th device (step S214). If the highest similarity is not equal to or higher than the accuracy of the nth device (NO in step S214), CPU 110 reads a second control command corresponding to nth device 200 from device database 101D. CPU 110 transmits the second control command via communication interface 105 (step S216). CPU110 performs the process from step S220.

Claims (8)

At least one camera for photographing people;
Multiple devices that operate in response to control instructions;
A controller, the controller comprising:
A communication interface for communicating with the at least one camera and the plurality of devices;
A memory for storing information for specifying a person, and storing the accuracy and the first control command in association with each of the plurality of devices;
A processor, the processor comprising:
Receiving an image including a person from the at least one camera via the communication interface;
For each of the plurality of devices, when the probability that the person included in the image is a person specified by the information is greater than or equal to the accuracy corresponding to the device, the device corresponding to the device via the communication interface A network system for transmitting a first control command to the device. The memory stores the first control command in association with information for specifying the person,
The processor, for each of the plurality of devices, when the accuracy that the person included in the image is a person specified by the information is equal to or higher than the accuracy corresponding to the device, the processor via the communication interface The network system according to claim 1, wherein the first control command corresponding to the information for specifying the person and the person is transmitted to the device. The at least one camera includes a plurality of cameras;
The memory stores a correspondence relationship between the plurality of cameras and the plurality of devices,
The processor, for each device corresponding to a camera that has transmitted an image including the person among the plurality of devices, the probability that the person included in the image is a person specified by the information corresponds to the device. 3. The network system according to claim 1, wherein, when the accuracy is equal to or higher than the accuracy, the first control command corresponding to the device is transmitted to the device via the communication interface.   The network system according to claim 3, wherein the information for specifying the person includes a feature amount created from a plurality of images obtained from the plurality of cameras. The memory stores a second control command in association with at least one of the plurality of devices,
The processor, for each of the plurality of devices, when the accuracy that the person included in the image is a person specified by the information is less than the accuracy corresponding to the device, the processor via the communication interface The network system according to any one of claims 1 to 4, wherein the second control command corresponding to the information is transmitted to the device. A network system including at least one camera, a plurality of devices, and a controller that stores information for specifying a person and stores an accuracy and a first control command in association with each of the plurality of devices. A method of controlling the equipment in
Said at least one camera photographing a person;
The controller receiving an image including a person from the at least one camera;
When the controller has a certainty that the person included in the image is a person specified by the information for each of the plurality of devices is greater than or equal to the accuracy corresponding to the device, the first corresponding to the device. Sending the control command to the device;
And a step of operating the device in response to the first control command. A communication interface for communicating with at least one camera and a plurality of devices;
A memory for storing information for specifying a person and storing an accuracy and a first control command in association with each of the plurality of devices;
A processor, the processor comprising:
Receiving an image including a person from the at least one camera via the communication interface;
For each of the plurality of devices, when the probability that the person included in the image is a person specified by the information is greater than or equal to the accuracy corresponding to the device, the device corresponding to the device via the communication interface A controller that transmits a first control command to the device. A device control method in a controller including a communication interface, a memory that stores information for identifying a person and stores accuracy and a first control command in association with each of a plurality of devices, and a processor There,
The processor receiving an image including a person from the at least one camera via the communication interface;
When the accuracy of the processor that the person included in the image is a person specified by the information is greater than or equal to the accuracy corresponding to the device, the device via the communication interface, for each of the plurality of devices. Transmitting the first control command corresponding to the device to the device.

Images