CN111886589A - Information generating device and program - Google Patents
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Abstract
The present invention provides an information generating device, comprising: the image processing apparatus includes an image acquisition unit that acquires a plurality of images captured by a plurality of imaging devices mounted on a plurality of vehicles, a determination unit that determines whether or not each of the plurality of images acquired by the image acquisition unit includes a predetermined object, an image selection unit that selects an image satisfying a predetermined condition from among the images including the object, and an information generation unit that generates object information capable of identifying the object corresponding to the image selected by the image selection unit.
Description
Technical Field
The present invention relates to an information generating apparatus and a program.
Background
A system is known that collects a captured image of the periphery of a vehicle from an imaging device mounted on the vehicle (see, for example, patent document 1).
Patent document 1: japanese laid-open patent publication No. 2006-221537
Disclosure of Invention
It is desirable to provide a technique for providing useful information using a captured image collected from a camera mounted on a vehicle.
According to a first aspect of the present invention, an information generating apparatus is provided. The information generating device may include an image acquiring unit that acquires a plurality of images captured by a plurality of imaging devices mounted on a plurality of vehicles, respectively. The information generating apparatus may include a determination unit configured to determine whether or not a preset object is included in each of the plurality of images acquired by the image acquisition unit. The information generating apparatus may include an image selecting unit that selects an image satisfying a predetermined condition from among images including the object. The information generating device may include an information generating unit that generates object information that can identify the object corresponding to the image selected by the image selecting unit.
The information generating unit may generate the object information including a position at which the image selected by the image selecting unit is captured. The image selecting unit may select an image in which a change of the object, which is determined based on a plurality of images including the same object captured at different times among the plurality of images acquired by the image acquiring unit, satisfies a predetermined condition. The image selecting unit may select an image of the preset object requiring maintenance. The information generating apparatus may further include a timing determining unit configured to determine a timing at which the object needs maintenance based on a plurality of images of the same object captured at different times included in the plurality of images acquired by the image acquiring unit, and the information generating unit may generate the object information including the timing determined by the timing determining unit.
The information generating apparatus may include an image storage unit configured to store the plurality of images acquired by the image acquiring unit, and a search condition acquiring unit configured to acquire a search condition indicating the object, and the determining unit may determine whether each of the images stored by the image storage unit satisfies the search condition. The information generating apparatus may further include a price setting unit configured to set a price for the image acquired by the image acquiring unit, and the price setting unit may set a price for an image satisfying the search condition acquired by the search condition acquiring unit to be higher than a price for an image not satisfying the search condition acquired by the search condition acquiring unit. The information generating apparatus may further include a price setting unit configured to set a price for the image acquired by the image acquiring unit, and the price setting unit may set a price differently for each type of object.
According to a second aspect of the present invention, there is provided a program for causing a computer to function as the information generating apparatus.
In addition, the summary of the present invention does not exemplify all the technical features of the present invention. In addition, sub-combinations of these feature sets may also be inventions.
Drawings
Fig. 1 schematically shows an example of a communication environment of the image management apparatus 100.
Fig. 2 schematically shows an example of a flow of processing by the image management apparatus 100.
Fig. 3 schematically shows an example of the condition of each object.
Fig. 4 schematically shows another example of the flow of the processing by the image management apparatus 100.
Fig. 5 schematically shows an example of the functional configuration of the image management apparatus 100.
Fig. 6 schematically shows an example of the priority table 184.
Fig. 7 schematically shows an example of a computer 1000 functioning as the image management apparatus 100.
Detailed Description
The present invention will be described below with reference to embodiments thereof, but the following embodiments do not limit the invention according to the claims. In addition, a combination of all the features described in the embodiments is not necessarily essential to the means for solving the problems of the present invention.
Fig. 1 schematically shows an example of a communication environment of the image management apparatus 100. The image management apparatus 100 according to the present embodiment manages images captured by each of the plurality of imaging apparatuses 202 mounted on each of the plurality of vehicles 200. The image captured by the image capturing device 202 is an image captured around the vehicle 200. The camera 202 is, for example, a car recorder.
The image management apparatus 100 collects images captured by each of the plurality of imaging apparatuses 202 mounted on the plurality of vehicles 200 via the network 10. The network 10 may be any network. For example, the network 10 may include at least one of the internet, a mobile phone network such as a so-called 3G (3rd Generation), lte (long Term evolution), 4G (4th Generation), and 5G (5th Generation), a public Area network (local Area network), and a private 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 also be connected wirelessly. The network 10 and the vehicle 200 may be wirelessly connected. The network 10 and the vehicle 200 may also be wired.
The image management apparatus 100 receives an image from, for example, the vehicle 200 via the network 10. The image management apparatus 100 receives an image from a reading apparatus that reads an image from a recording medium such as a hard disk provided in the vehicle 200 via the network 10. The image management apparatus 100 receives and stores images captured at respective times at respective positions by the plurality of imaging apparatuses 202.
The image management apparatus 100 determines whether each of the plurality of stored images includes a predetermined object, selects an image satisfying a predetermined condition from among the images including the object, and generates object information capable of identifying the object corresponding to the selected image. The image management apparatus 100 may generate object information including a position at which the selected image is captured. The image management apparatus 100 may generate object information including the type of the object. The image management apparatus 100 receives data specifying a predetermined object and a predetermined condition from the communication terminal 300, for example, and transmits the generated object information to the communication terminal 300. The image management apparatus 100 may be an example of an information generating apparatus.
For example, when the user 30 of the communication terminal 300 is a garden design worker and transmits data specifying a target garden and specifying a grass length longer than a threshold as a condition to the image management apparatus 100, the image management apparatus 100 determines whether or not the garden is included in each of the plurality of images stored, and selects an image satisfying the condition that the grass length is longer than the threshold. Next, the image management apparatus 100 generates object information indicating that the object is a garden and is disposed at a position on the map corresponding to the position where each image is captured. Then, the image management apparatus 100 transmits the generated object information to the communication terminal 300. This enables the user 30 to grasp the position of the garden requiring maintenance and the state of the garden.
Fig. 2 schematically shows an example of a flow of processing by the image management apparatus 100. Here, a flow of processing in which the image management apparatus 100 acquires a search condition indicating an object, generates object information, and transmits the object information will be described. The processing shown in fig. 2 is executed mainly by the control unit provided in the image management apparatus 100.
In step (step may be abbreviated as S.) 102, image management apparatus 100 acquires a search condition indicating an object. The image management apparatus 100 can receive the search condition from the communication terminal 300, for example.
In S104, the image management apparatus 100 searches for an image including the object indicated by the search condition acquired in S102. In S106, the image management apparatus 100 selects an image satisfying a predetermined condition from the images retrieved in S104.
In S108, the image management apparatus 100 generates object information that can identify the object corresponding to the image selected in S106. The image management apparatus 100 generates object information including, for example, the position at which the image selected in S106 was captured and the type of object indicated by the search condition acquired in S102. In S110, the image management apparatus 100 transmits the object information generated in S108 to the communication terminal 300. Then, the process is ended.
Fig. 3 shows an example of the preset conditions for each object. In fig. 3, a condition of "the length of grass is longer than the threshold value" is exemplified as a condition corresponding to "garden". At this time, the image management apparatus 100 selects an image satisfying the condition that "the length of grass is longer than the threshold value" from among the images including the garden among the stored images.
The image management apparatus 100 may select an image satisfying the condition by any method. For example, the image management apparatus 100 analyzes an image to determine the length of grass in the image, and compares the length with a threshold to determine whether or not a condition is satisfied. For example, the image management apparatus 100 stores at least one of an image of grass having a length shorter than a threshold value and an image of grass having a length longer than the threshold value, and compares the image including a garden with the stored image to determine whether or not the condition is satisfied. Further, the image management apparatus 100 may collect a plurality of images of a garden having a grass length longer than a threshold value and a plurality of images of a garden having a grass length shorter than the threshold value, perform machine learning on the images, generate learning data capable of determining whether or not the grass length of the obtained image of the garden is longer than the threshold value, and perform determination using the learning data.
The image management apparatus 100 may generate object information including a position where the selected image is photographed and a kind of the object, and transmit the object information to the communication terminal 300. This enables the user 30 to grasp the position and state of the garden requiring maintenance due to grass growth.
In fig. 3, a condition of "at least a part of the wall" is illustrated as a condition corresponding to the "wall". At this time, the image management apparatus 100 selects an image satisfying the condition of "at least partially broken" 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 broken by analyzing the image, for example. Further, the image management apparatus 100 may perform machine learning on a plurality of images of undamaged walls and at least a portion of the damaged walls, generate learning data that enables determination as to whether or not at least a portion of the damaged walls is present with respect to the obtained images of the walls, and perform the determination using the learning data.
The image management apparatus 100 may generate object information including a position where the selected image is photographed and a kind of the object, and transmit the object information to the communication terminal 300. This enables the user 30 to grasp the position and state of the wall that needs maintenance due to at least partial breakage.
In fig. 3, a condition of "the depth of the groove is shallower than the threshold value" is exemplified as a condition corresponding to "the tire of the automobile". At this time, the image management apparatus 100 selects an image satisfying the condition that "the depth of the groove is shallower than the threshold value" from among the stored images including the tires of the automobile.
The image management apparatus 100 determines the depth of the groove of the tire by analyzing the image, and determines whether or not the condition is satisfied by comparing the depth with a threshold value. For example, the image management apparatus 100 stores at least one of an image of a tire having a groove depth deeper than a threshold value and an image of a tire having a groove depth shallower than the threshold value, and compares the image including a tire of an automobile with the image to determine whether or not the condition is satisfied. Further, the image management device 100 may collect images of tires in which the groove depth is deeper than the threshold value and images of tires in which the groove depth is shallower than the threshold value, perform machine learning on them, generate learning data that can determine whether or not the groove depth of the obtained images of tires is deeper than the threshold value, and perform determination using the learning data.
The image management apparatus 100 generates object information using the selected image. Here, the image management apparatus 100 may generate object information containing information capable of specifying an object. For example, the image management apparatus 100 generates object information including a position where an image is captured, a case where an object is a tire of an automobile, and a license plate number of the automobile. The image management apparatus 100 can determine the license plate number of the automobile by, for example, performing symbol recognition on the image.
The image management apparatus 100 may transmit the generated object information to the communication terminal 300. This enables the user 30 to recognize the license plate number of the automobile having the tire that needs maintenance or replacement because the groove of the tire becomes shallow.
Fig. 4 schematically shows another example of the flow of the processing by the image management apparatus 100. The processing shown in fig. 4 is executed mainly by the control unit provided in the image management apparatus 100.
In S202, the image management apparatus 100 acquires a search condition indicating an object. The image management apparatus 100 receives the search condition from the communication terminal 300, for example. In S204, the image management apparatus 100 searches for an image including the object indicated by the search condition acquired in S202.
In S206, the image management apparatus 100 groups the images retrieved in S204 for each object. Each group has images that contain the same object.
In S208, the image management apparatus 100 determines one group of the plurality of groups grouped in S206. In S210, the image management apparatus 100 calculates a change over time of the object based on the plurality of images within the group determined in S208. For example, in the case of a group of images having a landscape, the image management apparatus 100 calculates the amount of change in the length of grass over time from a plurality of images taken at different times. Alternatively, the image management apparatus 100 may calculate the speed of grass growth. Further, the image management apparatus 100 may determine how much the length of the grass is to be maintained from the images before and after the grass is maintained and trimmed.
In S212, the image management apparatus 100 determines whether or not the change calculated in S210 satisfies a preset condition. The image management apparatus 100 determines that the condition is satisfied when it is determined that the current grass is in a maintenance-required state using information, for example, that the length of the grass is to a degree that maintenance is performed on the grass, which is determined in S210. If it is determined that the condition is satisfied, the process proceeds to S214, and 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 determined in S208.
In S216, the image management apparatus 100 determines whether or not to determine the end for all the groups grouped in S206. If it is determined that the termination is not performed, the process returns to S208, and if it is determined that the termination is performed, the process proceeds to S218.
In S218, the image management apparatus 100 generates object information for each group selected in S214. The image management apparatus 100 generates object information including an image, a position where the image is captured, and information indicating that the object is a garden and the current grass is in a state requiring maintenance, for example, for a group determined that the current grass is in the state requiring maintenance. In S220, the image management apparatus 100 transmits the object 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 device 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. The image management apparatus 100 does not necessarily have all of these configurations.
The image acquisition unit 102 acquires a plurality of images captured by a plurality of imaging devices 202 mounted on a plurality of vehicles 200, respectively. The image acquisition section 102 may receive an image from the vehicle 200 via the network 10. The image acquisition unit 102 may receive an image from a reading device that reads an image from a recording medium provided in the vehicle 200 via the network 10. 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 an object. The search condition acquisition unit 106 receives a search condition from the communication terminal 300, for example. The search condition acquisition unit 106 may acquire a search condition in any manner. The search condition acquisition unit 106 acquires search conditions in, for example, a keyword search, an image search, a concept search, and the like. Specifically, the search condition acquisition unit 106 acquires search conditions in the form of a keyword, an image, a natural language, and the like.
The determination unit 108 determines whether or not each of the images stored in the image storage unit 104 includes a preset object. The determination unit 108 determines, for example, an image satisfying the search condition acquired by the search condition acquisition unit 106 as an image including the target.
The image selecting unit 110 selects an image satisfying a predetermined condition from among images including an object. The image selecting unit 110 selects, for example, an image in which a change in the object determined based on a plurality of images including the same object captured at different times satisfies a predetermined condition. The image selecting unit 110 selects, for example, an image whose object is set in advance and needs maintenance. Specifically, the image selecting unit 110 determines the amount of change in the length of grass based on a plurality of images including the same garden captured at different times, and selects an image satisfying a condition that the length of grass is longer than a threshold value in several days.
The information generating unit 112 generates object information based on the image selected by the image selecting unit 110. The information generating unit 112 may generate object information that can identify the object corresponding to the image selected by the image selecting unit 110. The information generating unit 112 generates object information including, for example, the position at which the image selected by the image selecting unit 110 is captured and the type of an object set in advance. The object information may include the image selected by the image selecting unit 110.
For example, when the image selection unit 110 selects an image satisfying a condition that the length of the image is longer than the threshold value for several days, the information generation unit 112 may generate object information including a position where the image is captured, information indicating that the object is a grass, and information indicating that the grass needs to be maintained for several days.
The timing determination unit 114 determines a timing at which maintenance is required for the object based on the plurality of images captured at different times determined by the determination unit 108 to include the same object. For example, the timing determination unit 114 determines the speed of change in the state of the object based on a plurality of images captured at different times. The timing determination unit 114 determines what state the object is in is to be maintained, based on the images before and after the object is maintained. Then, the timing determination unit 114 determines how long the object is in the maintenance-required state based on the current state of the object and the speed of change of the determination, and thereby determines the timing at which the object requires maintenance.
The timing determination section 114 may transmit the determined timing to the information generation section 112. The information generating unit 112 may generate the object information further including the time determined by the time determining unit 114.
The price setting unit 120 sets a price for the case where the image acquisition unit 102 has acquired the image. That is, the price setting unit 120 sets a price for the case where the image is provided to the image management apparatus 100, for the vehicle 200 or the owner of the vehicle 200.
The price setting unit 120 may set the price of the image satisfying the search condition acquired by the search condition acquisition unit 106 to be higher than the price of the image not satisfying the search condition acquired by the search condition acquisition unit 106. This can contribute to an increase in the collection amount of images including an object of interest to an arbitrary user 30 by setting a high price for images including an object of interest to an arbitrary user 30.
The price setting unit 120 may set different prices for each type of object. For example, the price setting unit 120 sets a priority for each type of object, and sets a higher price as the priority is higher.
Fig. 6 shows an example of the priority table 184 indicating the priority of each object. In the priority table 184 shown in fig. 6, the case where the priority of the tires of the garden and the automobile is 5, the priority of the wall is 4, and the priority of the bicycle is 1 is exemplified.
The priority is determined, for example, according to the number of times each object is specified as a search condition. The greater the number of times designated as the search condition, the higher the priority the image management apparatus 100 can decide. The priority may be determined according to whether or not the search condition is specified at each time. The image management apparatus 100 may set the priority of the object specified as the search condition to be higher at the time of determining or updating the priority.
The image management apparatus 100 may transmit the priority table 184 to the vehicle 200. The vehicle 200 may store the image captured by the imaging device 202 in a recording medium such as a hard disk, and may transmit the image including the object with higher priority shown in the priority table 184 to the image management device 100 with higher priority. For example, in the case of receiving the priority table 184 illustrated in fig. 6, the vehicle 200 first transmits an image including tires of a garden or a car among the images captured by the imaging device 202 to the image management device 100. Then, the vehicle 200 transmits the image including the wall to the image management apparatus 100.
Fig. 7 schematically shows an example of a computer 1000 functioning as the image management apparatus 100. The computer 1000 according to the present embodiment includes: a CPU peripheral portion having a CPU1010, a RAM1030, and a graphics controller 1085 connected to each other via a main controller 1092, and an input/output portion having a ROM1020, a communication I/F1040, a hard disk drive 1050, and an input/output chip 1080 connected to the main controller 1092 via an input/output controller 1094.
The CPU1010 controls each unit based on the operation of programs stored in the ROM1020 and the RAM 1030. The graphic controller 1085 acquires image data generated on a frame buffer provided in the RAM1030 by the CPU1010 or the like, and displays the image data on a display. Instead, the graphics controller 1085 may include a frame buffer that stores image data generated by the CPU1010 or the like therein.
The communication I/F1040 communicates with other devices via a network by wire or wirelessly. The communication I/F1040 functions as hardware for performing communication. The hard disk drive 1050 stores programs and data used by the CPU 1010.
The ROM1020 stores a boot program executed when the computer 1000 is started, a program dependent on 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 supplied to the hard disk drive 1050 via the RAM1030 is stored in a recording medium such as an IC card and supplied by a user. The program is read out from the recording medium, installed to the hard disk drive 1050 via the RAM1030, and executed in the CPU 1010.
The program installed in the computer 1000 and causing the computer 1000 to function as the image management apparatus 100 may cause the CPU1010 and the like to operate so that the computer 1000 functions as each unit of the image management apparatus 100. The information processing described in these programs is read into the computer 1000, and functions as specific means for cooperating software with the various hardware resources described above, namely, the image acquisition unit 102, the image storage unit 104, the search condition acquisition unit 106, the determination unit 108, the image selection unit 110, the information generation unit 112, the time determination unit 114, and the consideration setting unit 120. By these specific means, calculation or processing of information corresponding to the purpose of use of the computer 1000 in the present embodiment is realized, and thereby the unique image management apparatus 100 corresponding to the purpose of use is constructed.
The present invention has been described above with reference to the embodiments, but the technical scope of the present invention is not limited to the scope described in the above embodiments. It will be apparent to those skilled in the art that various changes and modifications can be made in the above embodiments. It is apparent from the description of the claims that such modifications and improvements can be made within the technical scope of the present invention.
Note that the order of execution of the respective processes such as the operation, flow, step, and stage in the device, system, program, and method shown in the claims, the specification, and the drawings is not particularly explicitly indicated as "preceding" or "preceding", and may be realized in any order as long as the output of the preceding process is not used in the subsequent process. Even if the description is made using "first", "next", and the like for convenience in the operation flows in the claims, the description, and the drawings, it does not mean that the operations are necessarily performed in this order.
Description of the reference numerals
10 network, 30 users, 100 image management device, 102 image acquisition part, 104 image storage part, 106 search condition acquisition part, 108 judgment part, 110 image selection part, 112 information generation part, 114 time determination part, 120 price setting part, 184 priority table, 200 vehicle, 202 shooting device, 300 communication terminal, 1000 computer, 1010CPU, 1020ROM, 1030RAM, 1040 communication I/F, 1050 hard disk drive, 1080 input/output chip, 1085 image controller, 1092 main controller, 1094 controller input/output controller.
The claims (modification according to treaty clause 19)
1. An information generating apparatus includes:
an image acquisition unit that acquires a plurality of images captured by a plurality of imaging devices mounted on a plurality of vehicles, respectively;
a determination unit that determines whether or not a preset object 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 from the images including the object;
an information generating unit that generates object information that can identify the object corresponding to the image selected by the image selecting unit; and
a time determination unit that determines a speed of change in a state of the object based on the plurality of images including the same object captured at different times among the plurality of images acquired by the image acquisition unit, and determines a time at which maintenance is required for the object based on a result of the determination,
the information generating unit generates the object information including the time determined by the time determining unit.
2. The information generating apparatus according to claim 1,
the time determination unit determines images before and after the object is maintained, from among the plurality of images acquired by the image acquisition unit, including the same object captured at different times, determines what state the object is in and is to be maintained, based on the images before and after, and determines how much time the object is in a state requiring maintenance, based on the current state of the object and the determined change speed, thereby determining the time at which the object needs maintenance.
3. An information generating apparatus includes:
an image acquisition unit that acquires a plurality of images captured by a plurality of imaging devices mounted on a plurality of vehicles, respectively;
an image storage unit that stores the plurality of images acquired by the image acquisition unit;
a search condition acquisition unit for acquiring a search condition indicating a preset object,
a determination unit that determines whether or not a predetermined object is included in each of the plurality of images acquired by the image acquisition unit, and determines whether or not each of the images stored in the image storage unit satisfies the search condition;
an image selection unit that selects an image satisfying a predetermined condition from the images including the object;
an information generating unit that generates object information that can identify the object corresponding to the image selected by the image selecting unit; and
a price setting unit that sets a price for the case where the image acquisition unit has acquired the image,
the price setting unit sets the price of the image that satisfies the search condition acquired by the search condition acquisition unit to be higher than the price of the image that does not satisfy the search condition acquired by the search condition acquisition unit.
4. An information generating apparatus includes:
an image acquisition unit that acquires a plurality of images captured by a plurality of imaging devices mounted on a plurality of vehicles, respectively;
an image storage unit that stores the plurality of images acquired by the image acquisition unit;
a search condition acquisition unit for acquiring a search condition indicating a preset object,
a determination unit that determines whether or not a predetermined object is included in each of the plurality of images acquired by the image acquisition unit, and determines whether or not each of the images stored in the image storage unit satisfies the search condition;
an image selection unit that selects an image satisfying a predetermined condition from the images including the object;
an information generating unit that generates object information that can identify the object corresponding to the image selected by the image selecting unit; and
a price setting unit that sets a price for a case where the image acquisition unit has acquired the image,
the price setting unit sets different prices for each type of object.
5. An information generating apparatus includes:
an image acquisition unit that acquires a plurality of images captured by a plurality of imaging devices mounted on a plurality of vehicles, respectively;
an image storage unit that stores the plurality of images acquired by the image acquisition unit;
a search condition acquisition unit for acquiring a search condition indicating a preset object,
a determination unit that determines whether or not a predetermined object is included in each of the plurality of images acquired by the image acquisition unit, and determines whether or not each of the images stored in the image storage unit satisfies the search condition;
an image selection unit that selects an image satisfying a predetermined condition from the images including the object;
an information generating unit that generates object information that can identify the object corresponding to the image selected by the image selecting unit; and
a price setting unit that sets a price for the case where the image acquisition unit has acquired the image,
the price setting unit sets a different price for each object based on the priority of each object.
6. The information generating apparatus according to claim 5,
the price setting unit determines a higher priority for each of the plurality of objects as the number of times the object is specified as the search condition increases.
7. The information generating apparatus according to claim 5,
the price setting unit sets the priority of the object designated as the search condition to be higher than the priority of the object not designated as the search condition when determining or updating the priority of the object.
8. The information generating apparatus according to any one of claim 1 to claim 7,
the information generating unit generates the object information including a position at which the image selected by the image selecting unit is captured.
9. The information generating apparatus according to any one of claim 1 to claim 8,
the information generating unit generates the object information including a type of the object.
10. The information generating apparatus according to any one of claim 1 to claim 9,
the image selecting unit selects an image in which a change in the object, which is determined based on a plurality of images of the same object captured at different times among the plurality of images acquired by the image acquiring unit, satisfies a predetermined condition.
11. The information generating apparatus according to any one of claims 1 to 10,
the image selecting unit selects an image to be maintained for the preset object.
12. A program for causing a computer to function as the information generating apparatus according to any one of claims 1 to 11.
Claims (16)
1. An information generating apparatus includes:
an image acquisition unit that acquires a plurality of images captured by a plurality of imaging devices mounted on a plurality of vehicles, respectively;
a determination unit that determines whether or not a preset object 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 from the images including the object; and
an information generating unit that generates object information capable of identifying the object corresponding to the image selected by the image selecting unit.
2. The information generating apparatus according to claim 1,
the information generating unit generates the object information including a position at which the image selected by the image selecting unit is captured.
3. The information generating apparatus according to claim 1 or 2,
the information generating unit generates the object information including a type of the object.
4. The information generating apparatus according to any one of claims 1 to 3,
the image selecting unit selects an image in which a change in the object, which is determined based on a plurality of images of the same object captured at different times among the plurality of images acquired by the image acquiring unit, satisfies a predetermined condition.
5. The information generating apparatus according to any one of claims 1 to 4,
the image selecting unit selects an image to be maintained for the preset object.
6. The information generating apparatus according to any one of claims 1 to 5,
further comprising a timing determination unit that determines a timing at which maintenance is required for the object based on a plurality of images of the same object captured at different times among the plurality of images acquired by the image acquisition unit,
the information generating unit generates the object information including the time determined by the time determining unit.
7. The information generating apparatus according to claim 6,
the time determination unit determines a speed of change in the state of the object based on the plurality of images including the same object captured at different times among the plurality of images acquired by the image acquisition unit, and determines a time at which maintenance is required for the object based on the determination result.
8. The information generating apparatus according to claim 7,
the time determination unit determines images before and after the object is maintained, from among the plurality of images acquired by the image acquisition unit, including the same object captured at different times, determines what state the object is in and is to be maintained, based on the images before and after, and determines how much time the object is in a state requiring maintenance, based on the current state of the object and the determined change speed, thereby determining the time at which the object needs maintenance.
9. The information generating apparatus according to claim 6,
the timing determination unit determines images before and after the maintenance of the object from among the plurality of images acquired by the image acquisition unit, the plurality of images including the same object captured at different times, determines what state the object is in and will be maintained from the images before and after the maintenance, and determines a timing at which the object needs to be maintained based on the determination result.
10. The information generating apparatus according to any one of claims 1 to 9, comprising:
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 object,
the determination unit determines whether or not each of the images stored in the image storage unit satisfies the search condition.
11. The information generating apparatus according to claim 10,
a price setting unit that sets a price for the case where the image acquisition unit has acquired the image,
the price setting unit sets the price of the image that satisfies the search condition acquired by the search condition acquisition unit to be higher than the price of the image that does not satisfy the search condition acquired by the search condition acquisition unit.
12. The information generating apparatus according to claim 10,
a price setting unit that sets a price for the case where the image acquisition unit has acquired the image,
the price setting unit sets different prices for each type of object.
13. The information generating apparatus according to claim 10,
a price setting unit that sets a price for the case where the image acquisition unit has acquired the image,
the price setting unit sets a different price for each object based on the priority of each object.
14. The information generating apparatus according to claim 13,
the price setting unit determines a higher priority for each of the plurality of objects as the number of times the object is specified as the search condition increases.
15. The information generating apparatus according to claim 13,
the price setting unit sets the priority of the object designated as the search condition to be higher than the priority of the object not designated as the search condition when determining or updating the priority of the object.
16. A program for causing a computer to function as the information generating apparatus according to any one of claims 1 to 15.
Applications Claiming Priority (3)
| Application Number | Priority Date | Filing Date | Title |
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| JP2018-045809 | 2018-03-13 | ||
| JP2018045809 | 2018-03-13 | ||
| PCT/JP2019/009111 WO2019176728A1 (en) | 2018-03-13 | 2019-03-07 | Information generation device and program |
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| Publication Number | Publication Date |
|---|---|
| CN111886589A true CN111886589A (en) | 2020-11-03 |
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| CN201980018682.XA Pending CN111886589A (en) | 2018-03-13 | 2019-03-07 | Information generating device and program |
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| JP (1) | JP6940682B2 (en) |
| CN (1) | CN111886589A (en) |
| WO (1) | WO2019176728A1 (en) |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2010081070A (en) * | 2008-09-24 | 2010-04-08 | Fuji Xerox Co Ltd | Image transmission apparatus, image transmission program, image transmission system, and image communication system |
| WO2011111129A1 (en) * | 2010-03-08 | 2011-09-15 | 株式会社日立国際電気 | Image-search apparatus |
| CN102741900A (en) * | 2010-03-03 | 2012-10-17 | 松下电器产业株式会社 | Road condition management system and road condition management method |
| CN104751668A (en) * | 2013-12-20 | 2015-07-01 | 矢崎能源系统公司 | A traffic information management system |
| JP2017069917A (en) * | 2015-10-02 | 2017-04-06 | 株式会社東芝 | Communication processing device, on-vehicle device, and communication processing method |
| CN206900303U (en) * | 2017-04-21 | 2018-01-19 | 宝沃汽车（中国）有限公司 | A kind of windshield wiper changes system for prompting and vehicle |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2003030201A (en) * | 2001-07-19 | 2003-01-31 | Matsushita Electric Ind Co Ltd | Device for managing image and method for distributing video |
| JP6728897B2 (en) * | 2016-03-31 | 2020-07-22 | 日本電気株式会社 | Image collecting device, image collecting system, image collecting method and program |
-
2019
- 2019-03-07 CN CN201980018682.XA patent/CN111886589A/en active Pending
- 2019-03-07 JP JP2020506451A patent/JP6940682B2/en active Active
- 2019-03-07 WO PCT/JP2019/009111 patent/WO2019176728A1/en active Application Filing
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2010081070A (en) * | 2008-09-24 | 2010-04-08 | Fuji Xerox Co Ltd | Image transmission apparatus, image transmission program, image transmission system, and image communication system |
| CN102741900A (en) * | 2010-03-03 | 2012-10-17 | 松下电器产业株式会社 | Road condition management system and road condition management method |
| WO2011111129A1 (en) * | 2010-03-08 | 2011-09-15 | 株式会社日立国際電気 | Image-search apparatus |
| CN104751668A (en) * | 2013-12-20 | 2015-07-01 | 矢崎能源系统公司 | A traffic information management system |
| JP2017069917A (en) * | 2015-10-02 | 2017-04-06 | 株式会社東芝 | Communication processing device, on-vehicle device, and communication processing method |
| CN206900303U (en) * | 2017-04-21 | 2018-01-19 | 宝沃汽车（中国）有限公司 | A kind of windshield wiper changes system for prompting and vehicle |
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| Publication number | Publication date |
|---|---|
| JPWO2019176728A1 (en) | 2021-02-04 |
| WO2019176728A1 (en) | 2019-09-19 |
| JP6940682B2 (en) | 2021-09-29 |
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