WO2019176728A1 - Information generation device and program - Google Patents

Information generation device and program Download PDF

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Publication number
WO2019176728A1
WO2019176728A1 PCT/JP2019/009111 JP2019009111W WO2019176728A1 WO 2019176728 A1 WO2019176728 A1 WO 2019176728A1 JP 2019009111 W JP2019009111 W JP 2019009111W WO 2019176728 A1 WO2019176728 A1 WO 2019176728A1
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Prior art keywords
image
target
unit
information generation
images
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PCT/JP2019/009111
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French (fr)
Japanese (ja)
Inventor
智弘 柴田
暁郎 二ツ寺
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本田技研工業株式会社
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Priority to JP2020506451A priority Critical patent/JP6940682B2/en
Priority to CN201980018682.XA priority patent/CN111886589B/en
Publication of WO2019176728A1 publication Critical patent/WO2019176728A1/en

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/70—Information retrieval; Database structures therefor; File system structures therefor of video data
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/10—Services

Definitions

  • the present invention relates to an information generation device and a program.
  • Patent Document 1 Japanese Patent Application Laid-Open No. 2006-221537
  • an information generating device may include an image acquisition unit that acquires a plurality of images captured by a plurality of imaging devices mounted on each of a plurality of vehicles.
  • the information generation apparatus may include a determination unit that determines whether a predetermined target is included in each of the plurality of images acquired by the image acquisition unit.
  • the information generation apparatus may include an image selection unit that selects an image satisfying a predetermined condition from among images including the target.
  • the information generation device may include an information generation unit that generates target information that can identify a target corresponding to the image selected by the image selection unit.
  • the information generation unit may generate the target information including a position where the image selected by the image selection unit is captured.
  • the image selection unit is a condition in which a change in the target determined based on a plurality of images including the same target captured at different times among the plurality of images acquired by the image acquisition unit is predetermined. Images that satisfy the condition may be selected.
  • the image selection unit may select an image for which the predetermined target requires maintenance.
  • the information generation device identifies a time when the target needs maintenance based on a plurality of images including the same target captured at different times among the plurality of images acquired by the image acquisition unit.
  • the information generation unit may generate the target information including the time specified by the time specification unit.
  • the information generation apparatus may include an image storage unit that stores the plurality of images acquired by the image acquisition unit, and a search condition acquisition unit that acquires a search condition indicating the target. It may be determined whether each of the images stored in the image storage unit satisfies the search condition.
  • the information generation apparatus may include a price setting unit that sets a price for the image acquisition unit acquiring the image, and the price setting unit includes an image that satisfies the search condition acquired by the search condition acquisition unit. The price may be set higher than the price of an image that does not satisfy the search condition acquired by the search condition acquisition unit.
  • the information generation apparatus may include a price setting unit that sets a price for the image acquisition unit acquiring the image, and the price setting unit may set a different price for each target type.
  • An example of the communication environment of the image management apparatus 100 is shown schematically.
  • An example of the flow of processing by the image management apparatus 100 is schematically shown.
  • An example of conditions for every object is shown roughly.
  • Another example of the flow of processing by the image management apparatus 100 is schematically shown.
  • An example of a functional composition of image management device 100 is shown roughly.
  • An example of the priority table 184 is schematically shown.
  • 1 schematically shows an example of a computer 1000 that functions as an image management apparatus 100.
  • FIG. 1 schematically shows an example of a communication environment of the image management apparatus 100.
  • the image management device 100 manages images captured by each of the plurality of imaging devices 202 mounted on each of the plurality of vehicles 200.
  • the image captured by the imaging device 202 is an image captured around the vehicle 200.
  • the imaging device 202 is, for example, a drive recorder.
  • the image management apparatus 100 collects images captured by each of the plurality of imaging apparatuses 202 mounted on each of the plurality of vehicles 200 via the network 10.
  • the network 10 may be any network.
  • the network 10 includes the Internet, a mobile phone network such as 3G (3rd Generation), LTE (Long Term Evolution), 4G (4th Generation), and 5G (5th Generation), and a public wireless LAN (Local Area Network). , And / or a dedicated network.
  • the image management apparatus 100 and the network 10 may be connected by wire.
  • the image management apparatus 100 and the network 10 may be wirelessly connected.
  • the network 10 and the vehicle 200 may be wirelessly connected.
  • the network 10 and the vehicle 200 may be wired.
  • the image management apparatus 100 receives an image from the vehicle 200 via the network 10, for example. Further, the image management apparatus 100 receives an image via the network 10 from a reading apparatus that reads an image from a storage medium such as a hard disk of the vehicle 200, for example. The image management apparatus 100 receives and stores images captured by the plurality of imaging apparatuses 202 at various timings at various timings.
  • the image management apparatus 100 determines whether each of the plurality of stored images includes a predetermined target, selects an image satisfying a predetermined condition from among the images including the target, Object information that can identify an object corresponding to the selected image is generated.
  • the image management apparatus 100 may generate target information including a position where the selected image is captured.
  • the image management apparatus 100 may generate target information including a target type.
  • the image management apparatus 100 receives data specifying a predetermined target and a predetermined condition from the communication terminal 300, and transmits the generated target information to the communication terminal 300.
  • the image management apparatus 100 may be an example of an information generation apparatus.
  • the communication terminal 300 may be any terminal as long as it can communicate.
  • the communication terminal 300 is, for example, a mobile phone such as a smartphone, a tablet terminal, and a PC (Personal Computer).
  • the image management apparatus 100 stores the data. It is determined whether or not each of the plurality of images includes a garden, and an image satisfying the condition that the lawn length is longer than the threshold value is selected. Next, the image management apparatus 100 indicates that the object is a garden, and generates object information in which each image is arranged at a position on the map corresponding to the imaged position. Then, the image management apparatus 100 transmits the generated target information to the communication terminal 300. Thereby, the user 30 can be made aware of the location of the garden requiring maintenance and the state of the garden.
  • FIG. 2 schematically shows an example of the flow of processing by the image management apparatus 100.
  • a flow of processing from when the image management apparatus 100 acquires a search condition indicating a target, generates target information, and transmits the target information will be described.
  • the process shown in FIG. 2 is executed mainly by a control unit included in the image management apparatus 100.
  • step 102 (step may be abbreviated as S) 102, the image management apparatus 100 acquires a search condition indicating a target.
  • the image management apparatus 100 may receive a search condition from the communication terminal 300.
  • the image management apparatus 100 searches for an image including the target indicated by the search condition acquired in S102.
  • the image management apparatus 100 selects an image that satisfies a predetermined condition from the images searched in S104.
  • the image management apparatus 100 generates target information that can identify the target corresponding to the image selected in S106. For example, the image management apparatus 100 generates target information including the position where the image selected in S106 is captured and the type of target indicated by the search condition acquired in S102. In S110, the image management apparatus 100 transmits the target information generated in S108 to the communication terminal 300. Then, the process ends.
  • FIG. 3 shows an example of a predetermined condition for each target.
  • a condition that “the length of the lawn is longer than the threshold” is illustrated as a condition corresponding to “garden”.
  • the image management apparatus 100 selects an image satisfying the condition that “the lawn length is longer than the threshold” from among the stored images including the garden.
  • the image management apparatus 100 may select an image that satisfies a condition using an arbitrary method. For example, the image management apparatus 100 determines the length of the lawn in the image by analyzing the image, and determines whether the condition is satisfied by comparing the length with a threshold value. For example, the image management apparatus 100 stores at least one of a lawn image whose length is shorter than a threshold and a lawn image whose length is longer than a threshold, and compares the image including a garden with the image. Thus, it is determined whether or not the condition is satisfied. Also, the image management apparatus 100 collects a plurality of garden images whose lawn length is longer than the threshold and garden images whose lawn length is shorter than the threshold, and performs machine learning on these to give the images. Learning data that can determine whether or not the length of the lawn in the garden image is longer than a threshold value may be generated, and the determination may be made using the learning data.
  • the image management apparatus 100 may generate target information including the position where the selected image is captured and the type of the target, and transmit the target information to the communication terminal 300. This allows the user 30 to grasp the location and state of the garden that requires maintenance due to the lawn being stretched.
  • FIG. 3 illustrates a condition “at least a part is broken” as a condition corresponding to “wall”.
  • the image management apparatus 100 selects an image satisfying the condition that “at least a part is damaged” from among the stored images including the wall.
  • the image management apparatus 100 determines whether or not at least a part of the wall is damaged, for example, by analyzing the image. In addition, the image management apparatus 100 performs at least a part of a given wall image by performing machine learning on a plurality of non-damaged wall images and at least a part of the wall image that is broken. It is also possible to generate learning data that can determine whether or not is damaged, and use the learning data to determine.
  • the image management apparatus 100 may generate target information including the position where the selected image is captured and the type of the target, and transmit the target information to the communication terminal 300. Thereby, the user 30 can be made aware of the location and state of the wall that requires maintenance because at least a part of the wall is damaged.
  • the condition that “the groove depth is shallower than the threshold” is illustrated as a condition corresponding to “automobile tire”.
  • the image management apparatus 100 selects an image satisfying the condition that “the groove depth is shallower than the threshold” from the images including the tires of the automobile among the stored images.
  • the image management apparatus 100 determines whether or not the condition is satisfied by, for example, identifying the depth of the tire groove by analyzing the image and comparing it with a threshold value. Further, for example, the image management apparatus 100 stores at least one of an image of a tire with a groove depth deeper than a threshold and an image of a tire with a groove depth shallower than a threshold, It is determined whether or not a condition is satisfied by comparing the image. Further, the image management apparatus 100 is provided by collecting a plurality of tire images having a groove depth deeper than the threshold and tire images having a groove depth shallower than the threshold, and performing machine learning on these images. Learning data that can determine whether or not the depth of the groove of the tire image is deeper than a threshold value may be generated and determined using the learning data.
  • the image management apparatus 100 generates target information using the selected image.
  • the image management apparatus 100 may generate target information including information that can specify the target.
  • the image management apparatus 100 generates target information including the position where the image is captured, the target is a car tire, and the car number.
  • the image management apparatus 100 may specify the number of the automobile by recognizing characters in the image.
  • the image management apparatus 100 may transmit the generated target information to the communication terminal 300. Thereby, the user's 30 number can be made to grasp
  • FIG. 4 schematically shows another example of the processing flow by the image management apparatus 100.
  • the process illustrated in FIG. 4 is executed mainly by a control unit included in the image management apparatus 100.
  • the image management apparatus 100 acquires a search condition indicating a target. For example, the image management apparatus 100 receives a search condition from the communication terminal 300. In S204, the image management apparatus 100 searches for an image including the target indicated by the search condition acquired in S202.
  • the image management apparatus 100 groups the images searched in S204 for each target. Each group has images that contain the same object.
  • the image management apparatus 100 identifies one group among the plurality of groups grouped in S206.
  • the image management apparatus 100 calculates the temporal change of the target based on the plurality of images in the group specified in S208. For example, in the case of a group having a garden image, the image management apparatus 100 calculates a temporal change amount of the lawn length based on a plurality of images taken at different times. Alternatively, the image management apparatus 100 may calculate the speed at which the turf extends. Further, the image management apparatus 100 may specify how much the turf length is maintained from the images before and after the turf is maintained and cut.
  • the image management apparatus 100 determines whether the change calculated in S210 satisfies a predetermined condition. For example, the image management apparatus 100 determines that the current turf is in a state to be maintained using the information specified in S210 about how long the turf length is maintained. In this case, it is determined that the condition is satisfied. If it is determined that the condition is satisfied, the process proceeds to S214. If it is determined that the condition is not satisfied, the process proceeds to S216. In S214, the image management apparatus 100 selects the group specified in S208.
  • the image management apparatus 100 determines whether the determination has been completed for all the groups grouped in S206. If it is determined that the processing has not ended, the process returns to S208. If it is determined that the processing has ended, the process proceeds to S218.
  • the image management apparatus 100 In S218, the image management apparatus 100 generates target information for each group selected in S214.
  • the image management apparatus 100 for example, for a group determined that the current turf is in a state to be maintained, the image, the position where the image was taken, the target is a garden, and the current turf should be maintained Target information including the information indicating that the In S220, the image management apparatus 100 transmits the target information generated in S218 to the communication terminal 300.
  • FIG. 5 schematically shows an example of the functional configuration of the image management apparatus 100.
  • the image management apparatus 100 includes an image acquisition unit 102, an image storage unit 104, a search condition acquisition unit 106, a determination unit 108, an image selection unit 110, an information generation unit 112, a time specification unit 114, and a price setting unit 120. Note that it is not essential that the image management apparatus 100 has all these configurations.
  • the image acquisition unit 102 acquires a plurality of images captured by the plurality of imaging devices 202 mounted on each of the plurality of vehicles 200.
  • the image acquisition unit 102 may receive an image from the vehicle 200 via the network 10.
  • the image acquisition unit 102 may receive an image via the network 10 from a reading device that reads an image from a storage medium included in the vehicle 200.
  • the image storage unit 104 stores the image acquired by the image acquisition unit 102.
  • the search condition acquisition unit 106 acquires a search condition indicating the target.
  • the search condition acquisition unit 106 receives the search condition from the communication terminal 300, for example.
  • the search condition acquisition unit 106 may acquire a search condition of an arbitrary aspect.
  • the search condition acquisition unit 106 acquires search conditions in, for example, keyword search, image search, and concept search.
  • the search condition acquisition unit 106 acquires a search condition of a mode such as a keyword, an image, and a natural sentence.
  • the determination unit 108 determines whether each of the images stored in the image storage unit 104 includes a predetermined target.
  • the determination unit 108 determines, for example, an image that satisfies the search condition acquired by the search condition acquisition unit 106 as an image including a target.
  • the image selection unit 110 selects an image satisfying a predetermined condition from among images including the target.
  • the image selection unit 110 selects, for example, an image that satisfies a predetermined condition for a change in a target determined based on a plurality of images including the same target captured at different times.
  • the image selection unit 110 selects an image for which a predetermined target requires maintenance.
  • the image selection unit 110 determines the amount of change in turf length based on a plurality of images including the same garden captured at different times, and the turf length is longer than a threshold value within a few days. Select an image that satisfies the condition.
  • the information generation unit 112 generates target information based on the image selected by the image selection unit 110.
  • the information generation unit 112 may generate target information that can identify a target corresponding to the image selected by the image selection unit 110.
  • the information generation unit 112 generates target information including, for example, a position where the image selected by the image selection unit 110 is captured and a predetermined target type.
  • the target information may include an image selected by the image selection unit 110.
  • the information generation unit 112 selects the position where the image is captured and the target is the turf.
  • Object information may be generated that includes information indicating that the turf needs to be maintained within a few days.
  • the time specifying unit 114 specifies the time when the target needs maintenance based on a plurality of images captured at different times determined by the determining unit 108 to include the same target. For example, the time specifying unit 114 determines the speed of change of the target state based on a plurality of images taken at different times. Further, the timing specifying unit 114 determines what kind of state the target is to be maintained from the images before and after the target is maintained. Then, the time specifying unit 114 determines how much time has passed from the current state of the target and the determined rate of change, so that the target is in a state requiring maintenance, so that the target performs maintenance. Identify when you need it.
  • the time specifying unit 114 may transmit the specified time to the information generating unit 112.
  • the information generation unit 112 may generate target information that further includes the time specified by the time specification unit 114.
  • the price setting unit 120 sets a price for the image acquisition unit 102 acquiring an image. That is, the consideration setting unit 120 sets a consideration for providing an image to the vehicle 200 or the owner of the vehicle 200 that provided the image to the image management apparatus 100.
  • the price setting unit 120 may set the price of the image satisfying the search condition acquired by the search condition acquiring unit 106 higher than the price of the image not satisfying the search condition acquired by the search condition acquiring unit 106. As a result, a high price is set for an image including a target in which any one of the users 30 is interested, and an increase in the collection amount of images including the target in which any of the users 30 is interested. Can contribute.
  • the consideration setting unit 120 may set a different consideration for each target type. For example, the consideration setting unit 120 provides a priority for each target type, and sets a higher consideration as the priority is higher.
  • FIG. 6 shows an example of the priority table 184 indicating the priority for each target.
  • the priority table 184 shown in FIG. 6 illustrates a case where the garden and automobile tire priority is 5, the wall priority is 4, and the bicycle priority is 1.
  • Priority is determined according to the number of times each target is specified as a search condition, for example.
  • the image management apparatus 100 may determine a higher priority as the number of times specified as the search condition increases. Further, the priority may be determined according to whether or not it is specified as a search condition at each timing. The image management apparatus 100 may set the priority of the target specified as the search condition high at the timing of determining or updating the priority.
  • the image management apparatus 100 may transmit the priority table 184 to the vehicle 200.
  • the vehicle 200 stores the image captured by the imaging device 202 in a storage medium such as a hard disk, and the image including the target with the higher priority indicated by the priority table 184 is given to the image management device 100 more preferentially. May be sent.
  • the vehicle 200 first transmits an image including a garden or a car tire among images captured by the imaging device 202 to the image management device 100.
  • the vehicle 200 transmits an image including a wall to the image management apparatus 100.
  • FIG. 7 schematically shows an example of a computer 1000 that functions as the image management apparatus 100.
  • the computer 1000 includes a CPU peripheral unit including a CPU 1010, a RAM 1030, and a graphic controller 1085 that are connected to each other by a host controller 1092; a ROM 1020 that is connected to the host controller 1092 by an input / output controller 1094; An input / output unit having F1040, a hard disk drive 1050, and an input / output chip 1080 is provided.
  • the CPU 1010 operates based on programs stored in the ROM 1020 and the RAM 1030 and controls each unit.
  • the graphic controller 1085 acquires image data generated by the CPU 1010 or the like on a frame buffer provided in the RAM 1030 and displays the image data on the display.
  • the graphic controller 1085 may include a frame buffer that stores image data generated by the CPU 1010 or the like.
  • the communication I / F 1040 communicates with another device via a wired or wireless network.
  • the communication I / F 1040 functions as hardware that performs communication.
  • the hard disk drive 1050 stores programs and data used by the CPU 1010.
  • the ROM 1020 stores a boot program that is executed when the computer 1000 starts up, a program that depends on the hardware of the computer 1000, and the like.
  • the input / output chip 1080 connects various input / output devices to the input / output controller 1094 via, for example, a parallel port, a serial port, a keyboard port, a mouse port, and the like.
  • the program provided to the hard disk drive 1050 via the RAM 1030 is stored in a recording medium such as an IC card and provided by the user.
  • the program is read from the recording medium, installed in the hard disk drive 1050 via the RAM 1030, and executed by the CPU 1010.
  • a program that is installed in the computer 1000 and causes the computer 1000 to function as the image management apparatus 100 may work on the CPU 1010 or the like to cause the computer 1000 to function as each unit of the image management apparatus 100.
  • Information processing described in these programs is read by the computer 1000, whereby the image acquisition unit 102, the image storage unit 104, and the specific means in which the software and the various hardware resources described above cooperate with each other. It functions as the search condition acquisition unit 106, the determination unit 108, the image selection unit 110, the information generation unit 112, the time specification unit 114, and the consideration setting unit 120.
  • the specific image management apparatus 100 according to the use purpose is constructed
  • 10 network 30 users, 100 image management device, 102 image acquisition unit, 104 image storage unit, 106 search condition acquisition unit, 108 determination unit, 110 image selection unit, 112 information generation unit, 114 time specification unit, 120 value setting unit , 184 priority table, 200 vehicle, 202 imaging device, 300 communication terminal, 1000 computer, 1010 CPU, 1020 ROM, 1030 RAM, 1040 communication I / F, 1050 hard disk drive, 1080 input / output chip, 1085 graphic controller, 1092 host Controller, 1094 I / O controller

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Abstract

The present invention provides an information generation device provided with: an image acquisition unit which acquires a plurality of images captured by a plurality of image capturing devices respectively mounted in a plurality of vehicles; a determination unit which determines whether a predetermined target is included in each of the plurality of images acquired by the image acquisition unit; an image selection unit which selects, from among images including the target, an image that meets a predetermined condition; and an information generation unit which generates target information through which a target corresponding to the image selected by the image selection unit is identifiable.

Description

情報生成装置及びプログラムInformation generating apparatus and program
　本発明は、情報生成装置及びプログラムに関する。 The present invention relates to an information generation device and a program.
　車両に搭載された撮像装置から車両周辺の撮像画像を収集するシステムが知られていた（例えば、特許文献１参照）。
　［先行技術文献］
　［特許文献］
　［特許文献１］特開２００６－２２１５３７号公報 There has been known a system for collecting captured images around a vehicle from an imaging device mounted on the vehicle (see, for example, Patent Document 1).
[Prior art documents]
[Patent Literature]
[Patent Document 1] Japanese Patent Application Laid-Open No. 2006-221537
解決しようとする課題Challenges to be solved
　車両に搭載された撮像装置から収集した撮像画像を用いて有益な情報を提供する技術を提供することが望ましい。 It is desirable to provide a technology that provides useful information using captured images collected from an imaging device mounted on a vehicle.
一般的開示General disclosure
　本発明の第１の態様によれば、情報生成装置が提供される。情報生成装置は、複数の車両のそれぞれに搭載された複数の撮像装置によって撮像された複数の画像を取得する画像取得部を備えてよい。情報生成装置は、画像取得部によって取得された複数の画像のそれぞれに予め定められた対象が含まれるか否かを判断する判断部を備えてよい。情報生成装置は、対象を含む画像の内、予め定められた条件を満たす画像を選択する画像選択部を備えてよい。情報生成装置は、画像選択部によって選択された画像に対応する対象を識別可能な対象情報を生成する情報生成部を備えてよい。 According to the first aspect of the present invention, an information generating device is provided. The information generation device may include an image acquisition unit that acquires a plurality of images captured by a plurality of imaging devices mounted on each of a plurality of vehicles. The information generation apparatus may include a determination unit that determines whether a predetermined target is included in each of the plurality of images acquired by the image acquisition unit. The information generation apparatus may include an image selection unit that selects an image satisfying a predetermined condition from among images including the target. The information generation device may include an information generation unit that generates target information that can identify a target corresponding to the image selected by the image selection unit.
　上記情報生成部は、上記画像選択部によって選択された上記画像が撮像された位置を含む上記対象情報を生成してよい。上記画像選択部は、上記画像取得部によって取得された上記複数の画像のうち、異なる時間に撮像された同一の対象を含む複数の画像に基づいて判定した当該対象の変化が予め定められた条件を満たす画像を選択してよい。上記画像選択部は、上記予め定められた対象がメンテナンスを必要とする画像を選択してよい。上記情報生成装置は、上記画像取得部によって取得された上記複数の画像のうち、異なる時間に撮像された同一の対象を含む複数の画像に基づいて、当該対象がメンテナンスを必要とする時期を特定する時期特定部をさらに備えてよく、上記情報生成部は、上記時期特定部によって特定された時期を含む上記対象情報を生成してよい。 The information generation unit may generate the target information including a position where the image selected by the image selection unit is captured. The image selection unit is a condition in which a change in the target determined based on a plurality of images including the same target captured at different times among the plurality of images acquired by the image acquisition unit is predetermined. Images that satisfy the condition may be selected. The image selection unit may select an image for which the predetermined target requires maintenance. The information generation device identifies a time when the target needs maintenance based on a plurality of images including the same target captured at different times among the plurality of images acquired by the image acquisition unit. The information generation unit may generate the target information including the time specified by the time specification unit.
　上記情報生成装置は、上記画像取得部によって取得された上記複数の画像を格納する画像格納部と、上記対象を示す検索条件を取得する検索条件取得部とを備えてよく、上記判断部は、上記画像格納部に格納されている画像のそれぞれが上記検索条件を満たすか否かを判断してよい。上記情報生成装置は、上記画像取得部が上記画像を取得したことに対する対価を設定する対価設定部を備えてよく、上記対価設定部は、上記検索条件取得部が取得した検索条件を満たす画像の対価を、上記検索条件取得部が取得した検索条件を満たさない画像の対価よりも高く設定してよい。上記情報生成装置は、上記画像取得部が上記画像を取得したことに対する対価を設定する対価設定部を備えてよく、上記対価設定部は、対象の種類毎に異なる対価を設定してよい。 The information generation apparatus may include an image storage unit that stores the plurality of images acquired by the image acquisition unit, and a search condition acquisition unit that acquires a search condition indicating the target. It may be determined whether each of the images stored in the image storage unit satisfies the search condition. The information generation apparatus may include a price setting unit that sets a price for the image acquisition unit acquiring the image, and the price setting unit includes an image that satisfies the search condition acquired by the search condition acquisition unit. The price may be set higher than the price of an image that does not satisfy the search condition acquired by the search condition acquisition unit. The information generation apparatus may include a price setting unit that sets a price for the image acquisition unit acquiring the image, and the price setting unit may set a different price for each target type.
　本発明の第２の態様によれば、コンピュータを、上記情報生成装置として機能させるためのプログラムが提供される。 According to the second aspect of the present invention, there is provided a program for causing a computer to function as the information generating device.
　なお、上記の発明の概要は、本発明の必要な特徴の全てを列挙したものではない。また、これらの特徴群のサブコンビネーションもまた、発明となりうる。 Note that the above summary of the invention does not enumerate all the necessary features of the present invention. In addition, a sub-combination of these feature groups can also be an invention.
画像管理装置１００の通信環境の一例を概略的に示す。An example of the communication environment of the image management apparatus 100 is shown schematically. 画像管理装置１００による処理の流れの一例を概略的に示す。An example of the flow of processing by the image management apparatus 100 is schematically shown. 対象毎の条件の一例を概略的に示す。An example of conditions for every object is shown roughly. 画像管理装置１００による処理の流れの他の一例を概略的に示す。Another example of the flow of processing by the image management apparatus 100 is schematically shown. 画像管理装置１００の機能構成の一例を概略的に示す。An example of a functional composition of image management device 100 is shown roughly. 優先度テーブル１８４の一例を概略的に示す。An example of the priority table 184 is schematically shown. 画像管理装置１００として機能するコンピュータ１０００の一例を概略的に示す。1 schematically shows an example of a computer 1000 that functions as an image management apparatus 100.
　以下、発明の実施の形態を通じて本発明を説明するが、以下の実施形態は請求の範囲にかかる発明を限定するものではない。また、実施形態の中で説明されている特徴の組み合わせの全てが発明の解決手段に必須であるとは限らない。 Hereinafter, the present invention will be described through embodiments of the invention. However, the following embodiments do not limit the invention according to the claims. In addition, not all the combinations of features described in the embodiments are essential for the solving means of the invention.
　図１は、画像管理装置１００の通信環境の一例を概略的に示す。本実施形態に係る画像管理装置１００は、複数の車両２００のそれぞれに搭載された複数の撮像装置２０２のそれぞれによって撮像された画像を管理する。撮像装置２０２によって撮像された画像は、車両２００の周囲を撮像した画像である。撮像装置２０２は、例えば、ドライブレコーダである。 FIG. 1 schematically shows an example of a communication environment of the image management apparatus 100. The image management device 100 according to the present embodiment manages images captured by each of the plurality of imaging devices 202 mounted on each of the plurality of vehicles 200. The image captured by the imaging device 202 is an image captured around the vehicle 200. The imaging device 202 is, for example, a drive recorder.
　画像管理装置１００は、複数の車両２００のそれぞれに搭載された複数の撮像装置２０２のそれぞれによって撮像された画像を、ネットワーク１０を介して収集する。ネットワーク１０は、任意のネットワークであってよい。例えば、ネットワーク１０は、インターネットと、いわゆる３Ｇ（３ｒｄ　Ｇｅｎｅｒａｔｉｏｎ）、ＬＴＥ（Ｌｏｎｇ　Ｔｅｒｍ　Ｅｖｏｌｕｔｉｏｎ）、４Ｇ（４ｔｈ　Ｇｅｎｅｒａｔｉｏｎ）及び５Ｇ（５ｔｈ　Ｇｅｎｅｒａｔｉｏｎ）等の携帯電話網と、公衆無線ＬＡＮ（Ｌｏｃａｌ　Ａｒｅａ　Ｎｅｔｗｏｒｋ）と、専用網との少なくともいずれかを含んでよい。画像管理装置１００とネットワーク１０とは有線接続されよい。画像管理装置１００とネットワーク１０とは無線接続されてもよい。ネットワーク１０と車両２００とは、無線接続されてよい。ネットワーク１０と車両２００とは、有線接続されてもよい。 The image management apparatus 100 collects images captured by each of the plurality of imaging apparatuses 202 mounted on each of the plurality of vehicles 200 via the network 10. The network 10 may be any network. For example, the network 10 includes the Internet, a mobile phone network such as 3G (3rd Generation), LTE (Long Term Evolution), 4G (4th Generation), and 5G (5th Generation), and a public wireless LAN (Local Area Network). , And / or a dedicated network. The image management apparatus 100 and the network 10 may be connected by wire. The image management apparatus 100 and the network 10 may be wirelessly connected. The network 10 and the vehicle 200 may be wirelessly connected. The network 10 and the vehicle 200 may be wired.
　画像管理装置１００は、例えば、車両２００から、ネットワーク１０を介して画像を受信する。また、画像管理装置１００は、例えば、車両２００が有するハードディスク等の記憶媒体から画像を読み取る読取装置から、ネットワーク１０を介して画像を受信する。画像管理装置１００は、複数の撮像装置２０２によって様々な場所で様々なタイミングで撮像された画像を受信して格納することになる。 The image management apparatus 100 receives an image from the vehicle 200 via the network 10, for example. Further, the image management apparatus 100 receives an image via the network 10 from a reading apparatus that reads an image from a storage medium such as a hard disk of the vehicle 200, for example. The image management apparatus 100 receives and stores images captured by the plurality of imaging apparatuses 202 at various timings at various timings.
　画像管理装置１００は、格納している複数の画像のそれぞれに予め定められた対象が含まれるか否かを判断し、対象を含む画像の内、予め定められた条件を満たす画像を選択し、選択した画像に対応する対象を識別可能な対象情報を生成する。画像管理装置１００は、選択した画像が撮像された位置を含む対象情報を生成してもよい。画像管理装置１００は、対象の種類を含む対象情報を生成してもよい。画像管理装置１００は、例えば、予め定められた対象と予め定められた条件とを指定するデータを通信端末３００から受信し、生成した対象情報を通信端末３００に送信する。画像管理装置１００は、情報生成装置の一例であってよい。 The image management apparatus 100 determines whether each of the plurality of stored images includes a predetermined target, selects an image satisfying a predetermined condition from among the images including the target, Object information that can identify an object corresponding to the selected image is generated. The image management apparatus 100 may generate target information including a position where the selected image is captured. The image management apparatus 100 may generate target information including a target type. For example, the image management apparatus 100 receives data specifying a predetermined target and a predetermined condition from the communication terminal 300, and transmits the generated target information to the communication terminal 300. The image management apparatus 100 may be an example of an information generation apparatus.
　通信端末３００は、通信可能な端末であればどのような端末であってもよい。通信端末３００は、例えば、スマートフォン等の携帯電話、タブレット端末及びＰＣ（Ｐｅｒｓｏｎａｌ　Ｃｏｍｐｕｔｅｒ）等である。 The communication terminal 300 may be any terminal as long as it can communicate. The communication terminal 300 is, for example, a mobile phone such as a smartphone, a tablet terminal, and a PC (Personal Computer).
　例えば、通信端末３００のユーザ３０が造園業者であり、対象として庭、条件として芝生の長さが閾値より長いことを指定するデータを画像管理装置１００に送信した場合、画像管理装置１００は、格納している複数の画像のそれぞれに庭が含まれるか否かを判断し、芝生の長さが閾値より長いという条件を満たす画像を選択する。次に、画像管理装置１００は、対象が庭であることを示し、各画像を撮像された位置に対応する地図上の位置に配置した対象情報を生成する。そして、画像管理装置１００は、生成した対象情報を通信端末３００に送信する。これにより、ユーザ３０に、メンテナンスを必要とする庭の場所と当該庭の状態とを把握させることができる。 For example, when the user 30 of the communication terminal 300 is a gardener, and transmits data specifying that the target is a garden and the length of a lawn is longer than a threshold as a condition to the image management apparatus 100, the image management apparatus 100 stores the data. It is determined whether or not each of the plurality of images includes a garden, and an image satisfying the condition that the lawn length is longer than the threshold value is selected. Next, the image management apparatus 100 indicates that the object is a garden, and generates object information in which each image is arranged at a position on the map corresponding to the imaged position. Then, the image management apparatus 100 transmits the generated target information to the communication terminal 300. Thereby, the user 30 can be made aware of the location of the garden requiring maintenance and the state of the garden.
　図２は、画像管理装置１００による処理の流れの一例を概略的に示す。ここでは、画像管理装置１００が対象を示す検索条件を取得して、対象情報を生成し、送信するまでの処理の流れについて説明する。図２に示す処理は、画像管理装置１００が備える制御部が主体となって実行される。 FIG. 2 schematically shows an example of the flow of processing by the image management apparatus 100. Here, a flow of processing from when the image management apparatus 100 acquires a search condition indicating a target, generates target information, and transmits the target information will be described. The process shown in FIG. 2 is executed mainly by a control unit included in the image management apparatus 100.
　ステップ（ステップをＳと省略して記載する場合がある。）１０２では、画像管理装置１００が、対象を示す検索条件を取得する。画像管理装置１００は、例えば、通信端末３００から検索条件を受信してよい。 In step 102 (step may be abbreviated as S) 102, the image management apparatus 100 acquires a search condition indicating a target. For example, the image management apparatus 100 may receive a search condition from the communication terminal 300.
　Ｓ１０４では、画像管理装置１００が、Ｓ１０２において取得した検索条件が示す対象を含む画像を検索する。Ｓ１０６では、画像管理装置１００が、Ｓ１０４において検索された画像から、予め定められた条件を満たす画像を選択する。 In S104, the image management apparatus 100 searches for an image including the target indicated by the search condition acquired in S102. In S106, the image management apparatus 100 selects an image that satisfies a predetermined condition from the images searched in S104.
　Ｓ１０８では、画像管理装置１００が、Ｓ１０６において選択した画像に対応する対象を識別可能な対象情報を生成する。画像管理装置１００は、例えば、Ｓ１０６において選択した画像が撮像された位置と、Ｓ１０２において取得した検索条件が示す対象の種類とを含む対象情報を生成する。Ｓ１１０では、画像管理装置１００が、Ｓ１０８において生成した対象情報を通信端末３００に送信する。そして、処理を終了する。 In S108, the image management apparatus 100 generates target information that can identify the target corresponding to the image selected in S106. For example, the image management apparatus 100 generates target information including the position where the image selected in S106 is captured and the type of target indicated by the search condition acquired in S102. In S110, the image management apparatus 100 transmits the target information generated in S108 to the communication terminal 300. Then, the process ends.
　図３は、対象毎の予め定められた条件の一例を示す。図３では、「庭」に対応する条件として「芝生の長さが閾値より長い」という条件が例示されている。この場合、画像管理装置１００は、格納している画像のうち庭を含む画像から、「芝生の長さが閾値より長い」という条件を満たす画像を選択する。 FIG. 3 shows an example of a predetermined condition for each target. In FIG. 3, a condition that “the length of the lawn is longer than the threshold” is illustrated as a condition corresponding to “garden”. In this case, the image management apparatus 100 selects an image satisfying the condition that “the lawn length is longer than the threshold” from among the stored images including the garden.
　画像管理装置１００は、任意の手法を用いて条件を満たす画像を選択してよい。例えば、画像管理装置１００は、画像を解析することによって画像内の芝生の長さを特定し、閾値と比較することによって条件を満たすか否かを判定する。また、例えば、画像管理装置１００は、長さが閾値より短い芝生の画像及び長さが閾値より長い芝生の画像の少なくともいずれかを格納しておき、庭を含む画像と当該画像とを比較することによって、条件を満たすか否かを判定する。また、画像管理装置１００は、芝生の長さが閾値より長い庭の画像及び芝生の長さが閾値より短い庭の画像を複数収集し、これらに対して機械学習を行うことによって、与えられた庭の画像の芝生の長さが閾値より長いか否かを判定可能な学習データを生成し、当該学習データを用いて判定してもよい。 The image management apparatus 100 may select an image that satisfies a condition using an arbitrary method. For example, the image management apparatus 100 determines the length of the lawn in the image by analyzing the image, and determines whether the condition is satisfied by comparing the length with a threshold value. For example, the image management apparatus 100 stores at least one of a lawn image whose length is shorter than a threshold and a lawn image whose length is longer than a threshold, and compares the image including a garden with the image. Thus, it is determined whether or not the condition is satisfied. Also, the image management apparatus 100 collects a plurality of garden images whose lawn length is longer than the threshold and garden images whose lawn length is shorter than the threshold, and performs machine learning on these to give the images. Learning data that can determine whether or not the length of the lawn in the garden image is longer than a threshold value may be generated, and the determination may be made using the learning data.
　画像管理装置１００は、選択した画像が撮像された位置と、対象の種類とを含む対象情報を生成し、通信端末３００に送信してよい。これにより、芝生が伸びていることによりメンテナンスが必要な庭の場所及び状態をユーザ３０に把握させることができる。 The image management apparatus 100 may generate target information including the position where the selected image is captured and the type of the target, and transmit the target information to the communication terminal 300. This allows the user 30 to grasp the location and state of the garden that requires maintenance due to the lawn being stretched.
　また、図３は、「壁」に対応する条件として、「少なくとも一部が破損している」という条件が例示されている。この場合、画像管理装置１００は、格納している画像のうち壁を含む画像から、「少なくとも一部が破損している」という条件を満たす画像を選択する。 Further, FIG. 3 illustrates a condition “at least a part is broken” as a condition corresponding to “wall”. In this case, the image management apparatus 100 selects an image satisfying the condition that “at least a part is damaged” from among the stored images including the wall.
　画像管理装置１００は、例えば、画像を解析することによって、壁の少なくとも一部が破損しているか否かを判定する。また、画像管理装置１００は、複数の破損していない壁の画像及び少なくとも一部が破損している壁の画像に対して機械学習を行うことによって、与えられた壁の画像について、少なくとも一部が破損しているか否かを判定可能な学習データを生成し、当該学習データを用いて判定してもよい。 The image management apparatus 100 determines whether or not at least a part of the wall is damaged, for example, by analyzing the image. In addition, the image management apparatus 100 performs at least a part of a given wall image by performing machine learning on a plurality of non-damaged wall images and at least a part of the wall image that is broken. It is also possible to generate learning data that can determine whether or not is damaged, and use the learning data to determine.
　画像管理装置１００は、選択した画像が撮像された位置と、対象の種類とを含む対象情報を生成し、通信端末３００に送信してよい。これにより、少なくとも一部が破損していることによりメンテナンスが必要な壁の場所及び状態をユーザ３０に把握させることができる。 The image management apparatus 100 may generate target information including the position where the selected image is captured and the type of the target, and transmit the target information to the communication terminal 300. Thereby, the user 30 can be made aware of the location and state of the wall that requires maintenance because at least a part of the wall is damaged.
　また、図３では、「自動車のタイヤ」に対応する条件として「溝の深さが閾値より浅い」という条件が例示されている。この場合、画像管理装置１００は、格納している画像のうち自動車のタイヤを含む画像から、「溝の深さが閾値より浅い」という条件を満たす画像を選択する。 Further, in FIG. 3, the condition that “the groove depth is shallower than the threshold” is illustrated as a condition corresponding to “automobile tire”. In this case, the image management apparatus 100 selects an image satisfying the condition that “the groove depth is shallower than the threshold” from the images including the tires of the automobile among the stored images.
　画像管理装置１００は、例えば、画像を解析することによってタイヤの溝の深さを特定し、閾値と比較することによって条件を満たすか否かを判定する。また、例えば、画像管理装置１００は、溝の深さが閾値より深いタイヤの画像及び溝の深さが閾値より浅いタイヤの画像の少なくともいずれかを格納しておき、自動車のタイヤを含む画像と当該画像とを比較することによって、条件を満たすか否かを判定する。また、画像管理装置１００は、溝の深さが閾値より深いタイヤの画像及び溝の深さが閾値より浅いタイヤの画像を複数収集し、これらに対して機械学習を行うことによって、与えられたタイヤの画像の溝の深さが閾値より深いか否かを判定可能な学習データを生成し、当該学習データを用いて判定してもよい。 The image management apparatus 100 determines whether or not the condition is satisfied by, for example, identifying the depth of the tire groove by analyzing the image and comparing it with a threshold value. Further, for example, the image management apparatus 100 stores at least one of an image of a tire with a groove depth deeper than a threshold and an image of a tire with a groove depth shallower than a threshold, It is determined whether or not a condition is satisfied by comparing the image. Further, the image management apparatus 100 is provided by collecting a plurality of tire images having a groove depth deeper than the threshold and tire images having a groove depth shallower than the threshold, and performing machine learning on these images. Learning data that can determine whether or not the depth of the groove of the tire image is deeper than a threshold value may be generated and determined using the learning data.
　画像管理装置１００は、選択した画像を用いて対象情報を生成する。ここで、画像管理装置１００は、対象を特定可能な情報を含む対象情報を生成してよい。例えば、画像管理装置１００は、画像が撮像された位置、対象が自動車のタイヤであること、及び、自動車のナンバーを含む対象情報を生成する。画像管理装置１００は、例えば、画像を文字認識することによって自動車のナンバーを特定してよい。 The image management apparatus 100 generates target information using the selected image. Here, the image management apparatus 100 may generate target information including information that can specify the target. For example, the image management apparatus 100 generates target information including the position where the image is captured, the target is a car tire, and the car number. For example, the image management apparatus 100 may specify the number of the automobile by recognizing characters in the image.
　画像管理装置１００は、生成した対象情報を通信端末３００に送信してよい。これにより、タイヤの溝が浅くなっていることによりメンテナンス又は交換が必要なタイヤを有する自動車のナンバーをユーザ３０に把握させることができる。 The image management apparatus 100 may transmit the generated target information to the communication terminal 300. Thereby, the user's 30 number can be made to grasp | ascertain the number of the motor vehicle which has a tire which needs a maintenance or replacement | exchange since the groove | channel of a tire is shallow.
　図４は、画像管理装置１００による処理の流れの他の一例を概略的に示す。図４に示す処理は、画像管理装置１００が備える制御部が主体となって実行される。 FIG. 4 schematically shows another example of the processing flow by the image management apparatus 100. The process illustrated in FIG. 4 is executed mainly by a control unit included in the image management apparatus 100.
　Ｓ２０２では、画像管理装置１００が、対象を示す検索条件を取得する。画像管理装置１００は、例えば、通信端末３００から検索条件を受信する。Ｓ２０４では、画像管理装置１００が、Ｓ２０２において取得した検索条件が示す対象を含む画像を検索する。 In S202, the image management apparatus 100 acquires a search condition indicating a target. For example, the image management apparatus 100 receives a search condition from the communication terminal 300. In S204, the image management apparatus 100 searches for an image including the target indicated by the search condition acquired in S202.
　Ｓ２０６では、画像管理装置１００が、Ｓ２０４において検索された画像を、対象毎にグループ化する。各グループは、同一の対象を含む画像を有する。 In S206, the image management apparatus 100 groups the images searched in S204 for each target. Each group has images that contain the same object.
　Ｓ２０８では、画像管理装置１００が、Ｓ２０６においてグループ化した複数のグループのうちの一のグループを特定する。Ｓ２１０では、画像管理装置１００が、Ｓ２０８において特定したグループ内の複数の画像に基づいて、対象の時間的変化を算出する。例えば、庭の画像を有するグループの場合、画像管理装置１００は、撮像された時間の異なる複数の画像によって、芝の長さの時間的変化量を算出する。或いは、画像管理装置１００は、芝が伸びる速さを算出してもよい。また、画像管理装置１００は、芝がメンテナンスされてカットされる前後の画像から、芝の長さがどの程度になった場合に、芝がメンテナンスされるかを特定してもよい。 In S208, the image management apparatus 100 identifies one group among the plurality of groups grouped in S206. In S210, the image management apparatus 100 calculates the temporal change of the target based on the plurality of images in the group specified in S208. For example, in the case of a group having a garden image, the image management apparatus 100 calculates a temporal change amount of the lawn length based on a plurality of images taken at different times. Alternatively, the image management apparatus 100 may calculate the speed at which the turf extends. Further, the image management apparatus 100 may specify how much the turf length is maintained from the images before and after the turf is maintained and cut.
　Ｓ２１２では、画像管理装置１００が、Ｓ２１０において算出した変化が、予め定められた条件を満たすか否かを判定する。画像管理装置１００は、例えば、Ｓ２１０において特定した、芝の長さがどの程度になった場合に芝がメンテナンスされるかという情報を用いて、現在の芝がメンテナンスすべき状態であると判断した場合に、条件を満たすと判定する。条件を満たすと判定した場合、Ｓ２１４に進み、満たさないと判定した場合、Ｓ２１６に進む。Ｓ２１４では、画像管理装置１００が、Ｓ２０８において特定したグループを選択する。 In S212, the image management apparatus 100 determines whether the change calculated in S210 satisfies a predetermined condition. For example, the image management apparatus 100 determines that the current turf is in a state to be maintained using the information specified in S210 about how long the turf length is maintained. In this case, it is determined that the condition is satisfied. If it is determined that the condition is satisfied, the process proceeds to S214. If it is determined that the condition is not satisfied, the process proceeds to S216. In S214, the image management apparatus 100 selects the group specified in S208.
　Ｓ２１６では、画像管理装置１００が、Ｓ２０６においてグループ化した全グループについて判定が終了したか否かを判断する。終了していないと判断した場合、Ｓ２０８に戻り、終了したと判断した場合、Ｓ２１８に進む。 In S216, the image management apparatus 100 determines whether the determination has been completed for all the groups grouped in S206. If it is determined that the processing has not ended, the process returns to S208. If it is determined that the processing has ended, the process proceeds to S218.
　Ｓ２１８では、画像管理装置１００が、Ｓ２１４において選択したグループ毎に、対象情報を生成する。画像管理装置１００は、例えば、現在の芝がメンテナンスすべき状態であると判断したグループについて、画像と、画像が撮像された位置と、対象が庭であること及び現在の芝がメンテナンスすべき状態であることを示す情報とを含む対象情報を生成する。Ｓ２２０では、画像管理装置１００が、Ｓ２１８において生成した対象情報を通信端末３００に送信する。 In S218, the image management apparatus 100 generates target information for each group selected in S214. The image management apparatus 100, for example, for a group determined that the current turf is in a state to be maintained, the image, the position where the image was taken, the target is a garden, and the current turf should be maintained Target information including the information indicating that the In S220, the image management apparatus 100 transmits the target information generated in S218 to the communication terminal 300.
　図５は、画像管理装置１００の機能構成の一例を概略的に示す。画像管理装置１００は、画像取得部１０２、画像格納部１０４、検索条件取得部１０６、判断部１０８、画像選択部１１０、情報生成部１１２、時期特定部１１４、及び対価設定部１２０を備える。なお、画像管理装置１００がこれらのすべての構成を備えることは必須とは限らない。 FIG. 5 schematically shows an example of the functional configuration of the image management apparatus 100. The image management apparatus 100 includes an image acquisition unit 102, an image storage unit 104, a search condition acquisition unit 106, a determination unit 108, an image selection unit 110, an information generation unit 112, a time specification unit 114, and a price setting unit 120. Note that it is not essential that the image management apparatus 100 has all these configurations.
　画像取得部１０２は、複数の車両２００のそれぞれに搭載された複数の撮像装置２０２によって撮像された複数の画像を取得する。画像取得部１０２は、車両２００から、ネットワーク１０を介して画像を受信してよい。画像取得部１０２は、車両２００が有する記憶媒体から画像を読み取る読取装置から、ネットワーク１０を介して画像を受信してもよい。画像格納部１０４は、画像取得部１０２が取得した画像を格納する。 The image acquisition unit 102 acquires a plurality of images captured by the plurality of imaging devices 202 mounted on each of the plurality of vehicles 200. The image acquisition unit 102 may receive an image from the vehicle 200 via the network 10. The image acquisition unit 102 may receive an image via the network 10 from a reading device that reads an image from a storage medium included in the vehicle 200. The image storage unit 104 stores the image acquired by the image acquisition unit 102.
　検索条件取得部１０６は、対象を示す検索条件を取得する。検索条件取得部１０６は、例えば、通信端末３００から検索条件を受信する。検索条件取得部１０６は、任意の態様の検索条件を取得してよい。検索条件取得部１０６は、例えば、キーワード検索、画像検索、及び概念検索等における検索条件を取得する。具体例として、検索条件取得部１０６は、キーワード、画像、及び自然文等の態様の検索条件を取得する。 The search condition acquisition unit 106 acquires a search condition indicating the target. The search condition acquisition unit 106 receives the search condition from the communication terminal 300, for example. The search condition acquisition unit 106 may acquire a search condition of an arbitrary aspect. The search condition acquisition unit 106 acquires search conditions in, for example, keyword search, image search, and concept search. As a specific example, the search condition acquisition unit 106 acquires a search condition of a mode such as a keyword, an image, and a natural sentence.
　判断部１０８は、画像格納部１０４に格納されている画像のそれぞれに予め定められた対象が含まれるか否かを判断する。判断部１０８は、例えば、検索条件取得部１０６が取得した検索条件を満たす画像を、対象を含む画像と判断する。 The determination unit 108 determines whether each of the images stored in the image storage unit 104 includes a predetermined target. The determination unit 108 determines, for example, an image that satisfies the search condition acquired by the search condition acquisition unit 106 as an image including a target.
　画像選択部１１０は、対象を含む画像の内、予め定められた条件を満たす画像を選択する。画像選択部１１０は、例えば、異なる時間に撮像された同一の対象を含む複数の画像に基づいて判定した対象の変化が予め定められた条件を満たす画像を選択する。画像選択部１１０は、例えば、予め定められた対象がメンテナンスを必要とする画像を選択する。具体例として、画像選択部１１０は、異なる時間に撮像された同一の庭を含む複数の画像に基づいて芝の長さの変化量を判定し、数日中に芝の長さが閾値より長くなるという条件を満たす画像を選択する。 The image selection unit 110 selects an image satisfying a predetermined condition from among images including the target. The image selection unit 110 selects, for example, an image that satisfies a predetermined condition for a change in a target determined based on a plurality of images including the same target captured at different times. For example, the image selection unit 110 selects an image for which a predetermined target requires maintenance. As a specific example, the image selection unit 110 determines the amount of change in turf length based on a plurality of images including the same garden captured at different times, and the turf length is longer than a threshold value within a few days. Select an image that satisfies the condition.
　情報生成部１１２は、画像選択部１１０によって選択された画像に基づいて、対象情報を生成する。情報生成部１１２は、画像選択部１１０によって選択された画像に対応する対象を識別可能な対象情報を生成してよい。情報生成部１１２は、例えば、画像選択部１１０によって選択された画像が撮像された位置、及び予め定められた対象の種類を含む対象情報を生成する。対象情報は、画像選択部１１０によって選択された画像を含んでもよい。 The information generation unit 112 generates target information based on the image selected by the image selection unit 110. The information generation unit 112 may generate target information that can identify a target corresponding to the image selected by the image selection unit 110. The information generation unit 112 generates target information including, for example, a position where the image selected by the image selection unit 110 is captured and a predetermined target type. The target information may include an image selected by the image selection unit 110.
　例えば、画像選択部１１０によって、数日中に芝の長さが閾値より長くなるという条件を満たす画像が選択された場合、情報生成部１１２は、画像が撮像された位置と、対象が芝であること及び数日中に芝のメンテナンスが必要になることを示す情報とを含む対象情報を生成してよい。 For example, when the image selection unit 110 selects an image that satisfies the condition that the length of the turf is longer than a threshold value within a few days, the information generation unit 112 selects the position where the image is captured and the target is the turf. Object information may be generated that includes information indicating that the turf needs to be maintained within a few days.
　時期特定部１１４は、判断部１０８によって同一の対象を含むと判定された異なる時間に撮像された複数の画像に基づいて、当該対象がメンテナンスを必要とする時期を特定する。例えば、時期特定部１１４は、異なる時間に撮像された複数の画像に基づいて、対象の状態の変化の速度を判定する。また、時期特定部１１４は、対象がメンテナンスされる前後の画像から、対象がどのような状態になったらメンテナンスされるのかを判定する。そして、時期特定部１１４は、対象の現在の状態と、判定した変化の速度とから、どのくらいの時間が経過すると対象がメンテナンスを必要とする状態になるかを判定することにより、対象がメンテナンスを必要とする時期を特定する。 The time specifying unit 114 specifies the time when the target needs maintenance based on a plurality of images captured at different times determined by the determining unit 108 to include the same target. For example, the time specifying unit 114 determines the speed of change of the target state based on a plurality of images taken at different times. Further, the timing specifying unit 114 determines what kind of state the target is to be maintained from the images before and after the target is maintained. Then, the time specifying unit 114 determines how much time has passed from the current state of the target and the determined rate of change, so that the target is in a state requiring maintenance, so that the target performs maintenance. Identify when you need it.
　時期特定部１１４は、特定した時期を情報生成部１１２に送信してよい。情報生成部１１２は、時期特定部１１４によって特定された時期をさらに含む対象情報を生成してよい。 The time specifying unit 114 may transmit the specified time to the information generating unit 112. The information generation unit 112 may generate target information that further includes the time specified by the time specification unit 114.
　対価設定部１２０は、画像取得部１０２が画像を取得したことに対する対価を設定する。すなわち、対価設定部１２０は、画像を画像管理装置１００に対して提供した車両２００又は車両２００の所有者に対する、画像を提供したことに対する対価を設定する。 The price setting unit 120 sets a price for the image acquisition unit 102 acquiring an image. That is, the consideration setting unit 120 sets a consideration for providing an image to the vehicle 200 or the owner of the vehicle 200 that provided the image to the image management apparatus 100.
　対価設定部１２０は、検索条件取得部１０６が取得した検索条件を満たす画像の対価を、検索条件取得部１０６が取得した検索条件を満たさない画像の対価よりも高く設定してよい。これにより、いずれかのユーザ３０が興味を持っている対象を含む画像に対して高い対価を設定することになり、いずれかのユーザ３０が興味を持っている対象を含む画像の収集量の増加に貢献することができる。 The price setting unit 120 may set the price of the image satisfying the search condition acquired by the search condition acquiring unit 106 higher than the price of the image not satisfying the search condition acquired by the search condition acquiring unit 106. As a result, a high price is set for an image including a target in which any one of the users 30 is interested, and an increase in the collection amount of images including the target in which any of the users 30 is interested. Can contribute.
　対価設定部１２０は、対象の種類毎に異なる対価を設定してもよい。例えば、対価設定部１２０は、対象の種類毎に優先度を設け、優先度が高いほど高い対価を設定する。 The consideration setting unit 120 may set a different consideration for each target type. For example, the consideration setting unit 120 provides a priority for each target type, and sets a higher consideration as the priority is higher.
　図６は、対象毎の優先度を示す優先度テーブル１８４の一例を示す。図６に示す優先度テーブル１８４では、庭と自動車のタイヤの優先度が５、壁の優先度が４、自転車の優先度が１である場合を例示している。 FIG. 6 shows an example of the priority table 184 indicating the priority for each target. The priority table 184 shown in FIG. 6 illustrates a case where the garden and automobile tire priority is 5, the wall priority is 4, and the bicycle priority is 1.
　優先度は、例えば、各対象が検索条件として指定された回数に応じて決定される。画像管理装置１００は、検索条件として指定された回数が多いほど高い優先度を決定してよい。また、優先度は、各タイミングにおいて、検索条件として指定されているか否かに応じて決定されてもよい。画像管理装置１００は、優先度を決定又は更新するタイミングにおいて、検索条件として指定されている対象の優先度を高く設定してよい。 Priority is determined according to the number of times each target is specified as a search condition, for example. The image management apparatus 100 may determine a higher priority as the number of times specified as the search condition increases. Further, the priority may be determined according to whether or not it is specified as a search condition at each timing. The image management apparatus 100 may set the priority of the target specified as the search condition high at the timing of determining or updating the priority.
　画像管理装置１００は、優先度テーブル１８４を車両２００に送信してもよい。車両２００は、撮像装置２０２によって撮像された画像をハードディスク等の記憶媒体に格納しておき、優先度テーブル１８４が示す優先度がより高い対象を含む画像を、より優先的に画像管理装置１００に送信してよい。例えば、図６に例示する優先度テーブル１８４を受信した場合、車両２００は、撮像装置２０２によって撮像された画像のうち、庭又は自動車のタイヤを含む画像をまず画像管理装置１００に送信する。そして、次に、車両２００は、壁を含む画像を画像管理装置１００に送信する。 The image management apparatus 100 may transmit the priority table 184 to the vehicle 200. The vehicle 200 stores the image captured by the imaging device 202 in a storage medium such as a hard disk, and the image including the target with the higher priority indicated by the priority table 184 is given to the image management device 100 more preferentially. May be sent. For example, when the priority table 184 illustrated in FIG. 6 is received, the vehicle 200 first transmits an image including a garden or a car tire among images captured by the imaging device 202 to the image management device 100. Next, the vehicle 200 transmits an image including a wall to the image management apparatus 100.
　図７は、画像管理装置１００として機能するコンピュータ１０００の一例を概略的に示す。本実施形態に係るコンピュータ１０００は、ホストコントローラ１０９２により相互に接続されるＣＰＵ１０１０、ＲＡＭ１０３０、及びグラフィックコントローラ１０８５を有するＣＰＵ周辺部と、入出力コントローラ１０９４によりホストコントローラ１０９２に接続されるＲＯＭ１０２０、通信Ｉ／Ｆ１０４０、ハードディスクドライブ１０５０、及び入出力チップ１０８０を有する入出力部を備える。 FIG. 7 schematically shows an example of a computer 1000 that functions as the image management apparatus 100. The computer 1000 according to this embodiment includes a CPU peripheral unit including a CPU 1010, a RAM 1030, and a graphic controller 1085 that are connected to each other by a host controller 1092; a ROM 1020 that is connected to the host controller 1092 by an input / output controller 1094; An input / output unit having F1040, a hard disk drive 1050, and an input / output chip 1080 is provided.
　ＣＰＵ１０１０は、ＲＯＭ１０２０及びＲＡＭ１０３０に格納されたプログラムに基づいて動作し、各部の制御を行う。グラフィックコントローラ１０８５は、ＣＰＵ１０１０などがＲＡＭ１０３０内に設けたフレーム・バッファ上に生成する画像データを取得し、ディスプレイ上に表示させる。これに代えて、グラフィックコントローラ１０８５は、ＣＰＵ１０１０などが生成する画像データを格納するフレーム・バッファを、内部に含んでもよい。 The CPU 1010 operates based on programs stored in the ROM 1020 and the RAM 1030 and controls each unit. The graphic controller 1085 acquires image data generated by the CPU 1010 or the like on a frame buffer provided in the RAM 1030 and displays the image data on the display. Alternatively, the graphic controller 1085 may include a frame buffer that stores image data generated by the CPU 1010 or the like.
　通信Ｉ／Ｆ１０４０は、有線又は無線によりネットワークを介して他の装置と通信する。また、通信Ｉ／Ｆ１０４０は、通信を行うハードウエアとして機能する。ハードディスクドライブ１０５０は、ＣＰＵ１０１０が使用するプログラム及びデータを格納する。 The communication I / F 1040 communicates with another device via a wired or wireless network. The communication I / F 1040 functions as hardware that performs communication. The hard disk drive 1050 stores programs and data used by the CPU 1010.
　ＲＯＭ１０２０は、コンピュータ１０００が起動時に実行するブート・プログラム及びコンピュータ１０００のハードウエアに依存するプログラムなどを格納する。入出力チップ１０８０は、例えばパラレル・ポート、シリアル・ポート、キーボード・ポート、マウス・ポートなどを介して各種の入出力装置を入出力コントローラ１０９４へと接続する。 The ROM 1020 stores a boot program that is executed when the computer 1000 starts up, a program that depends on the hardware of the computer 1000, and the like. The input / output chip 1080 connects various input / output devices to the input / output controller 1094 via, for example, a parallel port, a serial port, a keyboard port, a mouse port, and the like.
　ＲＡＭ１０３０を介してハードディスクドライブ１０５０に提供されるプログラムは、ＩＣカードなどの記録媒体に格納されて利用者によって提供される。プログラムは、記録媒体から読み出され、ＲＡＭ１０３０を介してハードディスクドライブ１０５０にインストールされ、ＣＰＵ１０１０において実行される。 The program provided to the hard disk drive 1050 via the RAM 1030 is stored in a recording medium such as an IC card and provided by the user. The program is read from the recording medium, installed in the hard disk drive 1050 via the RAM 1030, and executed by the CPU 1010.
　コンピュータ１０００にインストールされ、コンピュータ１０００を画像管理装置１００として機能させるプログラムは、ＣＰＵ１０１０などに働きかけて、コンピュータ１０００を、画像管理装置１００の各部としてそれぞれ機能させてよい。これらのプログラムに記述された情報処理は、コンピュータ１０００に読込まれることにより、ソフトウエアと上述した各種のハードウエア資源とが協働した具体的手段である画像取得部１０２、画像格納部１０４、検索条件取得部１０６、判断部１０８、画像選択部１１０、情報生成部１１２、時期特定部１１４、及び対価設定部１２０として機能する。そして、これらの具体的手段によって、本実施形態におけるコンピュータ１０００の使用目的に応じた情報の演算又は加工を実現することにより、使用目的に応じた特有の画像管理装置１００が構築される。 A program that is installed in the computer 1000 and causes the computer 1000 to function as the image management apparatus 100 may work on the CPU 1010 or the like to cause the computer 1000 to function as each unit of the image management apparatus 100. Information processing described in these programs is read by the computer 1000, whereby the image acquisition unit 102, the image storage unit 104, and the specific means in which the software and the various hardware resources described above cooperate with each other. It functions as the search condition acquisition unit 106, the determination unit 108, the image selection unit 110, the information generation unit 112, the time specification unit 114, and the consideration setting unit 120. And the specific image management apparatus 100 according to the use purpose is constructed | assembled by implement | achieving the calculation or processing of the information according to the use purpose of the computer 1000 in this embodiment by these concrete means.
　以上、本発明を実施の形態を用いて説明したが、本発明の技術的範囲は上記実施の形態に記載の範囲には限定されない。上記実施の形態に、多様な変更または改良を加えることが可能であることが当業者に明らかである。その様な変更または改良を加えた形態も本発明の技術的範囲に含まれ得ることが、請求の範囲の記載から明らかである。 As mentioned above, although this invention was demonstrated using embodiment, the technical scope of this invention is not limited to the range as described in the said embodiment. It will be apparent to those skilled in the art that various modifications or improvements can be added to the above-described embodiment. It is apparent from the scope of the claims that the embodiments added with such changes or improvements can be included in the technical scope of the present invention.
　請求の範囲、明細書、および図面中において示した装置、システム、プログラム、および方法における動作、手順、ステップ、および段階などの各処理の実行順序は、特段「より前に」、「先立って」などと明示しておらず、また、前の処理の出力を後の処理で用いるのでない限り、任意の順序で実現しうることに留意すべきである。請求の範囲、明細書、および図面中の動作フローに関して、便宜上「まず、」、「次に、」などを用いて説明したとしても、この順で実施することが必須であることを意味するものではない。 The execution order of each process such as operations, procedures, steps, and stages in the apparatus, system, program, and method shown in the claims, the description, and the drawings is particularly “before” or “prior”. It should be noted that it can be realized in any order unless the output of the previous process is used in the subsequent process. Regarding the operation flow in the claims, the description, and the drawings, even if it is described using “first”, “next”, etc. for the sake of convenience, it means that it is essential to carry out in this order. is not.
１０　ネットワーク、３０　ユーザ、１００　画像管理装置、１０２　画像取得部、１０４　画像格納部、１０６　検索条件取得部、１０８　判断部、１１０　画像選択部、１１２　情報生成部、１１４　時期特定部、１２０　対価設定部、１８４　優先度テーブル、２００　車両、２０２　撮像装置、３００　通信端末、１０００　コンピュータ、１０１０　ＣＰＵ、１０２０　ＲＯＭ、１０３０　ＲＡＭ、１０４０　通信Ｉ／Ｆ、１０５０　ハードディスクドライブ、１０８０　入出力チップ、１０８５　グラフィックコントローラ、１０９２　ホストコントローラ、１０９４　入出力コントローラ 10 network, 30 users, 100 image management device, 102 image acquisition unit, 104 image storage unit, 106 search condition acquisition unit, 108 determination unit, 110 image selection unit, 112 information generation unit, 114 time specification unit, 120 value setting unit , 184 priority table, 200 vehicle, 202 imaging device, 300 communication terminal, 1000 computer, 1010 CPU, 1020 ROM, 1030 RAM, 1040 communication I / F, 1050 hard disk drive, 1080 input / output chip, 1085 graphic controller, 1092 host Controller, 1094 I / O controller

Claims (16)

  1. 　複数の車両のそれぞれに搭載された複数の撮像装置によって撮像された複数の画像を取得する画像取得部と、
    　前記画像取得部によって取得された前記複数の画像のそれぞれに予め定められた対象が含まれるか否かを判断する判断部と、
    　前記対象を含む前記画像の内、予め定められた条件を満たす画像を選択する画像選択部と、
    　前記画像選択部によって選択された前記画像に対応する前記対象を識別可能な対象情報を生成する情報生成部と
    　を備える情報生成装置。     An image acquisition unit that acquires a plurality of images captured by a plurality of imaging devices mounted on each of a plurality of vehicles;
    A determination unit that determines whether a predetermined target is included in each of the plurality of images acquired by the image acquisition unit;
    An image selection unit that selects an image satisfying a predetermined condition among the images including the target;
    An information generation device comprising: an information generation unit that generates target information that can identify the target corresponding to the image selected by the image selection unit.
  2. 　前記情報生成部は、前記画像選択部によって選択された前記画像が撮像された位置を含む前記対象情報を生成する、請求項１に記載の情報生成装置。 The information generation apparatus according to claim 1, wherein the information generation unit generates the target information including a position where the image selected by the image selection unit is captured.
  3. 　前記情報生成部は、前記対象の種類を含む前記対象情報を生成する、請求項１又は２に記載の情報生成装置。 The information generation device according to claim 1, wherein the information generation unit generates the target information including the type of the target.
  4. 　前記画像選択部は、前記画像取得部によって取得された前記複数の画像のうち、異なる時間に撮像された同一の対象を含む複数の画像に基づいて判定した当該対象の変化が、予め定められた条件を満たす画像を選択する、請求項１から３のいずれか一項に記載の情報生成装置。 The change of the target determined based on a plurality of images including the same target captured at different times among the plurality of images acquired by the image acquisition unit is predetermined. The information generation apparatus according to claim 1, wherein an image satisfying a condition is selected.
  5. 　前記画像選択部は、前記予め定められた対象がメンテナンスを必要とする画像を選択する、請求項１から４のいずれか一項に記載の情報生成装置。 The information generation apparatus according to any one of claims 1 to 4, wherein the image selection unit selects an image for which the predetermined target requires maintenance.
  6. 　前記画像取得部によって取得された前記複数の画像のうち、異なる時間に撮像された同一の対象を含む複数の画像に基づいて、当該対象がメンテナンスを必要とする時期を特定する時期特定部
    　をさらに備え、
    　前記情報生成部は、前記時期特定部によって特定された時期を含む前記対象情報を生成する、請求項１から５のいずれか一項に記載の情報生成装置。     A time specifying unit that specifies a time when the target needs maintenance based on a plurality of images including the same target captured at different times among the plurality of images acquired by the image acquiring unit; Prepared,
    The information generation device according to any one of claims 1 to 5, wherein the information generation unit generates the target information including the time specified by the time specification unit.
  7. 　前記時期特定部は、前記画像取得部によって取得された前記複数の画像のうち、異なる時間に撮像された同一の対象を含む前記複数の画像に基づいて、当該対象の状態の変化の速度を判定し、判定結果に基づいて、当該対象がメンテナンスを必要とする時期を特定する、請求項６に記載の情報生成装置。 The time specifying unit determines a change speed of a state of the target based on the plurality of images including the same target captured at different times among the plurality of images acquired by the image acquiring unit. The information generation device according to claim 6, wherein the time when the target requires maintenance is specified based on the determination result.
  8. 　前記時期特定部は、前記画像取得部によって取得された前記複数の画像のうち、異なる時間に撮像された同一の対象を含む前記複数の画像から、当該対象がメンテナンスされる前後の画像を特定し、当該前後の画像から、当該対象がどのような状態になったらメンテナンスされるのかを判定し、当該対象の現在の状態と、判定した前記変化の速度とから、どのくらいの時間が経過すると当該対象がメンテナンスを必要とする状態になるかを判定することにより、当該対象がメンテナンスを必要とする時期を特定する、請求項７に記載の情報生成装置。 The time specifying unit specifies an image before and after the target is maintained from the plurality of images including the same target captured at different times among the plurality of images acquired by the image acquiring unit. From the previous and next images, it is determined what state the target is to be maintained, and how long it takes from the current state of the target and the determined speed of the change. The information generation apparatus according to claim 7, wherein the time when the target needs maintenance is determined by determining whether the target needs maintenance.
  9. 　前記時期特定部は、前記画像取得部によって取得された前記複数の画像のうち、異なる時間に撮像された同一の対象を含む前記複数の画像から、当該対象がメンテナンスされる前後の画像を特定し、当該前後の画像から、当該対象がどのような状態になったらメンテナンスされるのかを判定し、判定結果に基づいて、当該対象がメンテナンスを必要とする時期を特定する、請求項６に記載の情報生成装置。 The time specifying unit specifies an image before and after the target is maintained from the plurality of images including the same target captured at different times among the plurality of images acquired by the image acquiring unit. The determination according to claim 6, wherein a state in which the target is maintained is determined from the previous and subsequent images, and a time when the target needs maintenance is determined based on the determination result. Information generator.
  10. 　前記画像取得部によって取得された前記複数の画像を格納する画像格納部と、
    　前記対象を示す検索条件を取得する検索条件取得部と
    　を備え、
    　前記判断部は、前記画像格納部に格納されている画像のそれぞれが前記検索条件を満たすか否かを判断する、請求項１から９のいずれか一項に記載の情報生成装置。     An image storage unit for storing the plurality of images acquired by the image acquisition unit;
    A search condition acquisition unit for acquiring a search condition indicating the target,
    The information generation apparatus according to claim 1, wherein the determination unit determines whether each of the images stored in the image storage unit satisfies the search condition.
  11. 　前記画像取得部が前記画像を取得したことに対する対価を設定する対価設定部
    　を備え、
    　前記対価設定部は、前記検索条件取得部が取得した検索条件を満たす画像の対価を、前記検索条件取得部が取得した検索条件を満たさない画像の対価よりも高く設定する、請求項１０に記載の情報生成装置。     A consideration setting unit for setting a consideration for the image acquisition unit acquiring the image,
    The said consideration setting part sets the consideration of the image which satisfy | fills the search conditions which the said search condition acquisition part acquired higher than the consideration of the image which does not satisfy the search conditions which the said search condition acquisition part acquired. Information generator.
  12. 　前記画像取得部が前記画像を取得したことに対する対価を設定する対価設定部
    　を備え、
    　前記対価設定部は、対象の種類毎に異なる対価を設定する、請求項１０に記載の情報生成装置。     A consideration setting unit for setting a consideration for the image acquisition unit acquiring the image,
    The information generation apparatus according to claim 10, wherein the consideration setting unit sets a different consideration for each target type.
  13. 　前記画像取得部が前記画像を取得したことに対する対価を設定する対価設定部
    　を備え、
    　前記対価設定部は、対象毎の優先度に基づいて、対象毎に異なる対価を設定する、請求項１０に記載の情報生成装置。     A consideration setting unit for setting a consideration for the image acquisition unit acquiring the image,
    The information generation apparatus according to claim 10, wherein the price setting unit sets a different price for each target based on a priority for each target.
  14. 　前記対価設定部は、複数の対象のそれぞれについて、対象が検索条件として指定された回数が多いほど高い優先度を決定する、請求項１３に記載の情報生成装置。 The information generation apparatus according to claim 13, wherein the consideration setting unit determines a higher priority for each of a plurality of objects as the number of times the object is designated as a search condition increases.
  15. 　前記対価設定部は、前記対象の優先度を決定又は更新するタイミングにおいて、検索条件として指定されている対象の優先度を、検索条件として指定されていない対象の優先度よりも高く設定する、請求項１３に記載の情報生成装置。 The consideration setting unit sets the priority of the target specified as the search condition higher than the priority of the target not specified as the search condition at the timing of determining or updating the priority of the target. Item 14. The information generation device according to Item 13.
  16. 　コンピュータを、請求項１から１５のいずれか一項に記載の情報生成装置として機能させるためのプログラム。 A program for causing a computer to function as the information generation device according to any one of claims 1 to 15.
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