JP7409920B2 - Image management system, image management method, server device, and program - Google Patents

Description

The present invention relates to a technology for managing images obtained by multiple vehicles.

Patent Document 1 discloses a system that acquires image data of a predetermined period of time before or after the occurrence of an accident from other vehicles that were traveling around the accident vehicle when the accident occurred.

Japanese Patent Application Publication No. 2010-72845

In the system described in Patent Document 1, even if other vehicles were traveling around the accident vehicle at the time of the accident, depending on the driving conditions (travel direction, vehicle speed, etc.), the image taken by the other vehicle may be affected by the accident. The scene may not be visible or the image may be unclear. If such image data is acquired, the amount of data communication will be unnecessarily large, and the data size to be managed will become enormous.

Therefore, an object of the present invention is to provide an advantageous technique for obtaining high-value and useful images while reducing the amount of data communication.

In order to achieve the above object, an image management system as one aspect of the present invention is an image management system that manages images, and includes a detection means for detecting the occurrence of an event, and a detection means for detecting the occurrence of the event by the detection means. a first acquisition means for acquiring photographing information regarding the state of the photographing means of the vehicle from each of a plurality of vehicles within a predetermined distance from the event occurrence place; a selection means for selecting a vehicle from among the plurality of vehicles based on which the image photographed by the photographing means is to be acquired preferentially; and a second acquisition for acquiring the image from the vehicle selected by the selection means. The predetermined distance is set to be shorter when the event occurs at night than when the event occurs during the day .

According to the present invention, it is possible to provide an advantageous technique for obtaining high-value and useful images while reducing the amount of data communication.

Block diagram showing the configuration of the image management system Diagram showing an example of the situation of multiple vehicles when an event occurs Sequence diagram showing processing performed between the server device and the vehicle in the first embodiment Flowchart showing image management processing Flowchart showing how to select target vehicles Diagram showing an example of setting priorities Diagram showing the relationship between vehicle speed and image blur Sequence diagram showing processing performed between the server device and the vehicle in the second embodiment

Embodiments of the present invention will be described below with reference to the drawings. The present invention is not limited to the following embodiments, but also includes changes and modifications of the configuration within the scope of the spirit of the present invention. Furthermore, not all combinations of features described in this embodiment are essential to the present invention.

<First embodiment>
A first embodiment according to the present invention will be described. FIG. 1 is a block diagram showing the configuration of an image management system 100 of this embodiment. The image management system 100 of this embodiment may include a server device 10 and a plurality of vehicles 20. The server device 10 and the plurality of vehicles 20 are communicably connected to each other via the network NTW. In the present embodiment, the vehicle 20 may be a four-wheeled vehicle, a straddle-type vehicle such as a motorcycle or a tricycle, or a large vehicle such as a truck or a bus.

First, a configuration example of the server device 10 will be described. The server device 10 is configured by, for example, a computer, and can include a processing section 11, a storage section 12 (database), and a communication section 13. The processing unit 11 includes a processor represented by a CPU, a storage device such as a semiconductor memory, an interface with an external device, and the like. The storage unit 12 stores programs executed by the processor and data used by the processor for processing, and the processing unit 11 reads the programs stored in the storage unit into a storage device such as a memory and executes them. I can do it. In the case of this embodiment, the storage unit 12 stores a program (image management program) for acquiring and managing images from a plurality of vehicles 20, and the processing unit 11 stores images stored in the storage unit. The management program can be read into a storage device such as a memory and executed. Further, the communication section 13 is a unit for communicating with each of the plurality of vehicles 20 via the network NTW.

Further, the processing unit 11 of this embodiment is provided with a detection unit 11a, a first acquisition unit 11b, a selection unit 11c, and a second acquisition unit 11d. The detection unit 11a detects the occurrence of an event. The first acquisition unit 11b acquires information regarding the state of the imaging unit 24 of the vehicle 20 (hereinafter sometimes referred to as imaging information) from each of the plurality of vehicles 20. The selection unit 11c selects a vehicle 20 from among the plurality of vehicles 20 to preferentially acquire an image photographed by the photographing unit 24 based on the photographing information acquired from each vehicle 20 by the first acquiring unit 11b. . The second acquisition unit 11d acquires an image from the vehicle 20 selected by the selection unit 11c.

Next, a configuration example of the vehicle 20 will be described. Although the example shown in FIG. 1 shows the configuration of one vehicle among the plurality of vehicles 20, other vehicles may have a similar configuration. Vehicle 20 may include, for example, a control section 21, a storage section 22, a communication section 23, a photographing section 24, a position sensor 25, a speed sensor 26, an acceleration sensor 27, and an angular velocity sensor 28. The control section 21 is, for example, an ECU (Electronic Control Unit), includes a processor represented by a CPU, a storage device such as a semiconductor memory, an interface with an external device, and controls each section of the vehicle 20. The storage unit 22 stores programs, data, etc. for controlling the vehicle 20, and the control unit 21 can read the programs stored in the storage unit 22 into a storage device such as a memory and execute them. . The communication unit 23 is a unit for communicating with the server device 10 via the network NTW.

The photographing unit 24 is, for example, a camera that photographs the surroundings of the vehicle 20, and is, for example, a drive recorder. In this embodiment, the photographing unit 24 will be described as a camera that photographs the front of the vehicle 20, but may include a camera that photographs the rear of the vehicle 20. Further, it is assumed that the photographing section 24 of this embodiment employs a constant recording method, and images (videos) of the surroundings of the vehicle photographed by the photographing section 24 are sequentially stored in the storage section 22. The images (videos) stored in the storage unit 22 may be overwritten as appropriate in the order of oldest images depending on the storage area (storage capacity) of the storage unit 22.

Position sensor 25 includes, for example, a GPS sensor, and detects the current position and attitude of vehicle 20. Further, the position sensor 25 can also detect the traveling direction of the vehicle 20 based on changes in the position of the vehicle 20 over time. Speed sensor 26 detects the speed of vehicle 20. The acceleration sensor 27 is also called a G sensor and detects the acceleration of the vehicle 20. The angular velocity sensor 28 includes a gyro sensor and detects the angular velocity (rotational motion) of the vehicle 20.

FIG. 2 shows an example of the situation of a plurality of vehicles 20 when an event occurs. In FIG. 2, vehicles 20a to 20j are illustrated as the plurality of vehicles 20, and the traveling direction of each vehicle 20 is represented by an arrow. Vehicles 20a to 20h are four-wheeled vehicles, vehicle 20i is a straddle-type vehicle (motorcycle), and vehicle 20j is a large vehicle (truck). Further, in the example shown in FIG. 2, an accident between the vehicle 20a and the vehicle 20b is illustrated as an "event". Hereinafter, the vehicle (20a, 20b) in which the event occurred may be referred to as a "specific vehicle." Events are not limited to accidents between vehicles (collisions, etc.), but include accidents between vehicles and obstacles (collisions, etc.), vehicle troubles and disasters (breakdowns, etc.), and preliminary events for disasters and accidents. (near miss), etc., or may include events (incidents) that are not related to the vehicle.

When an event (such as an accident) occurs in this way, an image taken of the event may be required in order to analyze the cause of the event. In this case, it is preferable to use an image photographed by the photographing unit 24 of the vehicle 20 that was traveling around the place where the event occurred when the event occurred. However, even if the vehicle 20 was traveling around the place where the event occurred, the place where the event occurred may not be reflected in the image photographed by the photographing unit 24 depending on the driving condition (travel direction, vehicle speed, etc.). The image may be unclear. If such images are transferred from the vehicle 20 to the server device 10, the amount of data communication will become unnecessarily large, and the data size of the images managed by the server device 10 will become enormous. Therefore, the server device 10 of this embodiment is configured to acquire and manage only images of high value and useful for analyzing the cause of an event from the vehicle 20.

FIG. 3 is a sequence diagram showing the processing performed between the server device 10 and the vehicle 20. In FIG. 3, the vehicles 20a, 20c, and 20d shown in FIG. 2 will be illustrated and explained. The vehicle 20a is a specific vehicle in which an event (accident) has occurred. Furthermore, the vehicle 20c and the vehicle 20d are vehicles that were traveling within a predetermined distance from the event occurrence location at the time of the event occurrence.

When the specific vehicle 20a detects the occurrence of an event such as an accident or a near-miss (S101), it transmits event occurrence information indicating that the event has occurred to the server device 10 (S102). For example, when the acceleration sensor 27 detects an acceleration equal to or greater than a threshold value, the specific vehicle 20a determines that an event has occurred and transmits event occurrence information to the server device 10. The event occurrence information includes information indicating the location where the event occurred (that is, current position information detected by the position sensor 25 of the specific vehicle 20a). Further, the event occurrence information may include an image (image data) photographed by the photographing unit 24 of the specific vehicle 20a.

The server device 10 can detect the occurrence of an event by receiving event occurrence information from the specific vehicle 20a (S103). The server device 10 that has detected the occurrence of the event requests photographic information from each of the plurality of vehicles 20 that were traveling within a predetermined distance from the place where the event occurred at the time the event occurred (S104). In the example shown in FIG. 3, a vehicle 20c and a vehicle 20d are illustrated as the plurality of vehicles 20 to which a request for photographing information is made. Here, the request for photographing information can be made, for example, by transmitting information on the time when the event occurred to each of the plurality of vehicles 20. Further, the photographing information is information regarding the state (photographing state) when the photographing section 24 of each vehicle 20 is photographing the surroundings at the time of occurrence of an event, and includes, for example, information regarding the traveling of the vehicle 20, information regarding the photographing section of the vehicle 20, etc. The information may include at least one of information indicating the installation height of the camera 24, information indicating the resolution of the imaging unit 24, and information indicating the lighting state of the headlights of the vehicle 20. The information regarding the running of the vehicle 20 is information indicating at least one of the position, traveling direction, and vehicle speed of the vehicle 20 when an event occurs.

Each of the plurality of vehicles 20 that received a request for photographing information from the server device 10 transmits the photographing information to the server device 10 (S105). The server device 10 acquires photographic information from each vehicle 20 (S106), and selects a target vehicle from which images photographed by the photographing unit 24 are to be preferentially acquired based on the acquired photographic information (S107). In the example shown in FIG. 3, the vehicle 20c is selected as the target vehicle, but the vehicle 20d is not selected as the target vehicle. Next, the server device 10 requests the vehicle 20c selected as the target vehicle for an image (image data) photographed by the photographing unit 24 when the event occurs. An image request is not made to a vehicle 20d that is not selected as a target vehicle. The vehicle 20c that has received the image request transmits an image of the event location to the server device 10 (S109). After acquiring the image from the vehicle 20c, the server device 10 stores the acquired image in the storage unit 12 (S110).

FIG. 4 is a flowchart showing image management processing for acquiring and managing images from a plurality of vehicles 20. The flowchart shown in FIG. 4 may be executed by the processing unit 11 of the server device 10 when the image management program is executed. Here, in this embodiment, an example is shown in which the processing unit 11 of the server device 10 performs the image management process, but the control unit 21 of the specific vehicle 20a may perform the image management process, for example. In this case, it is preferable to provide the control section 21 of the specific vehicle 20a with the functions of the processing section 11 of the server device 10, and to store the image management program in the storage section 22 of the specific vehicle 20a.

In S201, the processing unit 11 (detection unit 11a) determines whether or not the occurrence of an event has been detected. For example, when the processing unit 11 receives event occurrence information from the specific vehicle 20a as described above, it can determine that the event occurrence has been detected. Further, if a person at the event occurrence location notifies the server device 10 from a mobile terminal such as a smartphone, the processing unit 11 may detect the occurrence of the event based on the notification. The latter case is particularly useful when the event is not vehicle related.

In S202, the processing unit 11 requests photographing information from each of the plurality of vehicles 20 that were traveling within a predetermined distance from the place where the event occurred when the event occurred. For example, in the example shown in FIG. 2, since an event (accident) has occurred between vehicle 20a and vehicle 20b, vehicles 20c to 20j that were traveling within a predetermined distance from the event location at the time of the event occurrence A request for shooting information is made. Here, the predetermined distance can be set arbitrarily, but it is preferably set to a distance that can be recognized by a camera (drive recorder) commonly used as the photographing unit 24. Further, the distance that can be recognized by the photographing unit 24 tends to be shorter at night than during the day. Therefore, the predetermined distance may be set to be shorter when the event occurs at night than when the event occurs during the day. As an example, if the predetermined distance during the day is set to 100 m, the predetermined distance during the night may be set to 70 m.

In S203, the processing unit 11 (first acquisition unit 11b) acquires photographing information from each of the plurality of vehicles 20. As described above, the photographing information is information regarding the state of the photographing unit 24 at the time of occurrence of an event, and includes, for example, information regarding the traveling of the vehicle 20 (position, direction of travel, vehicle speed), and the installation height of the photographing unit 24 in the vehicle 20. , information indicating the resolution of the imaging unit 24 , and information indicating the lighting state of the headlights of the vehicle 20 .

In S204, the processing unit 11 (selection unit 11c) selects a target vehicle from which to preferentially acquire an image photographed by the photographing unit 24, based on the photographing information acquired from each vehicle 20 in S203. For example, the server device 10 sets a priority (priority level) for each vehicle 20 based on the photographic information acquired from each vehicle 20, and selects a predetermined number of vehicles 20 as target vehicles from the one with the highest set priority. do. A method for selecting a target vehicle will be described later.

In S205, the processing unit 11 requests the target vehicle selected in S204 for an image (image data) photographed by the photographing unit 24 when the event occurs. When requesting a video as an image, the processing unit 11 may specify the shooting time of the video. The shooting time is a time that indicates the length of a video as a video. The photographing time can be arbitrarily set, and preferably includes the event occurrence time, for example. It is preferable that the shooting time is set to be longer when the event occurs at night than when the event occurs during the day. This is because there is less traffic at night than during the day, making it difficult to obtain useful images.

In S206, the processing unit 11 (second acquisition unit 11d) acquires an image from the target vehicle selected in S204. Then, in S207, the processing unit 11 stores and manages the image acquired in S206 in the storage unit 12 (database). Images acquired in this way are highly likely to clearly show the location where the event occurred at the time of the event, and are valuable for analyzing the cause of the event, so they are used by police, insurance companies, etc. can be provided.

Next, details of S204 in the flowchart of FIG. 4 will be explained with reference to FIGS. 5 and 6. FIG. 5 is a flowchart showing a method for selecting a target vehicle in S204, and FIG. 6 is a diagram showing an example of priority setting. Steps S301 to S306 in the flowchart in FIG. 5 are steps for setting priority (priority level) as an index for selecting a target vehicle, and can be performed individually for each of the plurality of vehicles 20.

In S301, the processing unit 11 changes the priority according to the distance between the event occurrence location (position of the specific vehicle 20a) and the vehicle 20 at the time of the event occurrence. The shorter the distance between the event occurrence location and the vehicle 20, the higher the possibility that the event occurrence location will be clearly reflected in the image photographed by the imaging unit 24. Therefore, the processing unit 11 sets a higher priority to the vehicle 20 that is closer to the event location at the time of event occurrence. As an example, as shown in FIG. 6, when the threshold values (threshold values D1 to D2) of the distance between the event occurrence location and the vehicle 20 are set in stages, the processing unit 11 determines that the distance d from the event occurrence location is For vehicles 20 whose distance d is less than the threshold D1 (for example, 20c to 20f in FIG. 2), the priority is increased by "+2", and for vehicles 20 whose distance d from the event occurrence place is greater than or equal to the threshold D1 and less than the threshold D2 (for example, 20g to 20j) in FIG. 2, the priority is increased by "+1". Note that the number of threshold values is not limited to two, but may be one or three or more, or the priority may be changed using a mathematical formula without setting a threshold.

In S302, the processing unit 11 changes the priority depending on the direction of travel of the vehicle 20 at the time the event occurs. Depending on the direction of travel of the vehicle 20, the event occurrence location may not be visible in the image photographed by the photographing unit 24. Therefore, the processing unit 11 sets a high priority to the vehicle 20 in which the event occurrence location falls within the photographing range (photographing area) of the photographing unit 24 . As an example, as shown in FIG. 6, the processing unit 11 gives priority to the vehicle 20 (for example, 20c, 20e, 20h to 20j in FIG. 2) in which the event occurrence location falls within the photographing range of the photographing unit 24. Increases degree by +5. Here, depending on the traveling direction of the vehicle 20, it may be affected by backlight. Therefore, the processing unit 11 may set a high priority to the vehicle 20 that is less likely to be affected by backlight, based on the sun position information at the event occurrence time.

In S303, the processing unit 11 changes the priority according to the speed (vehicle speed) of the vehicle 20 at the time the event occurs. As shown in FIG. 7, as the speed of the vehicle 20 is faster, image blur tends to occur in the image photographed by the photographing section 24. Therefore, the processing unit 11 sets a higher priority to the slower the vehicle 20 when the event occurs. As an example, as shown in FIG. 6, when the threshold value (threshold value V1 to V2) of the vehicle speed at the time of event occurrence is set in stages, the processing unit 11 determines that the vehicle speed v at the time of event occurrence is less than the threshold value V1. The priority level is increased by "+2" for the vehicle 20, and the priority level is increased by "+1" for the vehicle 20 whose vehicle speed v at the time of event occurrence is greater than or equal to the threshold value V1 and less than the threshold value V2. Note that the number of threshold values is not limited to two, but may be one or three or more, or the priority may be changed using a mathematical formula without setting a threshold.

In S304, the processing unit 11 changes the priority according to the installation height of the imaging unit 24 (camera) in the vehicle 20. The higher the installation height of the photographing unit 24 is, the more the event occurrence place can be photographed from a bird's-eye view, and the value of the photographed image becomes higher. Therefore, the processing section 11 sets a higher priority for the vehicle 20 in which the photographing section 24 is installed at a higher height. As an example, as shown in FIG. 6, when the threshold values (threshold values H1 to H2) of the installation height of the imaging unit 24 are set in stages, the processing unit 11 determines that the installation height h of the imaging unit 24 is set to the threshold value. For vehicles 20 (for example, 20c to 20h in FIG. 2) whose height is H1 or higher and lower than the threshold H2, the priority is increased by "+1", and if the vehicle 20 whose installation height h of the imaging unit 24 is at least the threshold H2 (for example, 20c to 20h in FIG. 2) is For 20j) in FIG. 2, the priority is increased by "+2". The priority level is not increased for vehicles whose installation height h is less than the threshold value H1 (for example, 20i in FIG. 2). Note that the number of threshold values is not limited to two, but may be one or three or more, or the priority may be changed using a mathematical formula without setting a threshold.

In S305, the processing unit 11 changes the priority according to the resolution of the imaging unit 24 (camera). The higher the resolution of the photographing unit 24, the more valuable the image photographed by it. Therefore, the processing unit 11 sets a higher priority for the vehicle 20 whose imaging unit 24 has a higher resolution. As an example, as shown in FIG. 6, when the resolution thresholds (thresholds R1 to R2) of the imaging unit 24 are set in stages, the processing unit 11 determines that when the resolution r of the imaging unit 24 is equal to or higher than the threshold R1, the processing unit 11 For vehicles 20 whose resolution r is less than R2, the priority is increased by "+2", and for vehicles 20 whose resolution r of the imaging unit 24 is greater than or equal to threshold R2, the priority is increased by "+4". Note that the number of threshold values is not limited to two, but may be one or three or more, or the priority may be changed using a mathematical formula without setting a threshold.

In S306, the processing unit 11 changes the priority depending on the lighting state of the headlights of the vehicle 20. For example, at dusk, a vehicle 20 with its headlights on tends to have higher image quality and clarity of images captured by the imaging unit 24 than a vehicle 20 without its headlights on. be. Therefore, the processing unit 11 sets a higher priority for the vehicle 20 whose headlights are turned on. As an example, as shown in FIG. 6, the processing unit 11 increases the priority by "+3" for the vehicle 20 whose headlights are on. Through the above steps S301 to S306, the priority level is set (determined) for each of the plurality of vehicles 20.

In S307, the processing unit 11 selects a predetermined number of vehicles 20 from among the plurality of vehicles 20, starting from the one with the highest priority, based on the priority of each vehicle 20 set in S301 to S306, as the target vehicle for image acquisition. Select as. Here, the predetermined number can be set arbitrarily, but is preferably set according to the scale and importance of the event. As an example, the predetermined number may be set to be smaller when the event is an accident involving a single vehicle than when the event is an accident between vehicles. Further, the predetermined number may be set to be larger when the event occurs at night than when the event occurs during the day. This is because there is less traffic at night than during the day, making it difficult to obtain useful images.

As described above, in the image management system 100 of the present embodiment, the server device 10 acquires photographic information from each of the plurality of vehicles 20 that were traveling within a predetermined distance from the event location when the event occurred. Based on the photographing information, a target vehicle is selected from among the plurality of vehicles 20, from which images photographed by the photographing section 24 are to be preferentially acquired. Then, an image is acquired from the selected target vehicle. As a result, it is possible to obtain high-value and useful images for elucidating the cause of an event while reducing the amount of data communication (particularly for the vehicle 20). Furthermore, the size of data managed by the server device 10 can also be reduced.

<Second embodiment>
A second embodiment according to the present invention will be described. In the first embodiment, an example has been described in which an image (video) of the event site at the time of event occurrence is acquired. On the other hand, there are cases where it is desired to grasp the situation at the event site after the event has occurred. Therefore, in the present embodiment, an example will be described in which an image (video) of the event site after the event occurrence is acquired. Note that this embodiment basically inherits the first embodiment, and unless otherwise mentioned below, the system configuration, device configuration, processing flow, etc. are the same as the first embodiment.

FIG. 8 is a sequence diagram showing the processing performed between the server device 10 and the vehicle 20 in this embodiment. In FIG. 8, similarly to FIG. 3, vehicles 20a, 20c, and 20d shown in FIG. The vehicle is

S401 to S403 in FIG. 8 are the same processes as S101 to S103 in FIG. 3. The server device 10 that has detected the occurrence of the event requests photographic information from each of the plurality of vehicles 20 that are traveling within a predetermined distance from the event occurrence location at the current time (S404). In the case of the present embodiment, the photographing information is information regarding the state of the photographing unit 24 of each vehicle 20 at the current time, and for example, regarding the traveling (at least one of the position, traveling direction, and vehicle speed) of the vehicle 20 at the current time. May contain information. Next, each of the plurality of vehicles 20 that received the request for photographing information transmits the photographing information at the current time to the server device 10 (S405). The server device 10 acquires photographic information from each vehicle 20 (S406), and selects a target vehicle from which to preferentially acquire images photographed by the photographing unit 24 based on the acquired photographic information (S407). That is, the server device 10 selects a target vehicle from among the plurality of vehicles 20 for which the photographing unit 24 is to photograph the event occurrence location based on the photographing information of each vehicle 20.

The server device 10 requests the vehicle 20c selected as the target vehicle to photograph the event occurrence location by the photographing unit 24 (S408). The vehicle 20c that has received the photographing request uses the photographing unit 24 to photograph the event occurrence location (S409), and transmits the image (video) obtained by the photographing to the server device 10 (S410). After acquiring the image from the vehicle 20c, the server device 10 stores the acquired image in the storage unit 12 (S411).

Next, changes in the case where the flowcharts shown in FIGS. 4 and 5 are applied to this embodiment will be described. In the first embodiment, "information at the time of event occurrence" was used, whereas in this embodiment, "information about the current time" is used.
Regarding the flowchart shown in FIG. 4, the processes of S202, S205, and S206 may be changed. Specifically, in S202, the processing unit 11 requests shooting information at the current time from each of the plurality of vehicles 20 that are traveling within a predetermined distance from the event occurrence location at the current time. In S205, the processing unit 11 requests the photographing unit 24 to photograph the event location for the target vehicle selected in S204. Further, in S206, the processing unit 11 acquires an image of the event occurrence location taken by the imaging unit 24 from the target vehicle selected in S204.

Regarding the flowchart shown in FIG. 5, the processes of S301 to S303 may be changed. Specifically, in S301, the processing unit 11 changes the priority according to the distance between the event occurrence location and the vehicle 20 at the current time. In S302, the processing unit 11 changes the priority according to the traveling direction of the vehicle 20 at the current time. Furthermore, in S303, the processing unit 11 changes the priority according to the speed (vehicle speed) of the vehicle 20 at the current time.

According to this embodiment, the server device 10 can acquire an image of the event location after the event has occurred. In this case as well, it is possible to reduce the amount of data communication (particularly for the vehicle 20) and to obtain images that are highly valuable and useful for elucidating the cause of the occurrence of an event. Furthermore, the size of data managed by the server device 10 can also be reduced.

<Summary of embodiments>
1. The image management system of the above embodiment includes:
An image management system (for example, 100) that manages images,
a detection means (for example 11a) for detecting the occurrence of an event;
When the event occurrence is detected by the detection means, a step of acquiring photographic information regarding the state of the vehicle photographing means (for example, 24) from each of a plurality of vehicles (for example, 20) within a predetermined distance from the event occurrence location. 1 acquisition means (for example 11b),
Selection means (for example, 11c) for selecting a vehicle from among the plurality of vehicles to preferentially acquire an image photographed by the photographing means, based on the photographing information acquired by the first acquiring means;
and second acquisition means (for example, 11d) that acquires the image from the vehicle selected by the selection means.
According to this configuration, since the images to be transmitted and received (acquired) are carefully selected, the amount of data communication (especially for vehicles) can be reduced and the load on the network can be suppressed. In addition, it is possible to obtain images that are highly valuable and useful for elucidating the cause of an event, and to reduce the size of data to be managed.

2. In the above embodiment,
The photographing information includes information indicating the position of the vehicle,
The selection means preferentially selects a vehicle that is close to the event location based on the photographic information.
According to this configuration, it is possible to carefully select and acquire images in which the event occurrence location is photographed more clearly.

3. In the above embodiment,
The photographing information includes information indicating a traveling direction of the vehicle,
The selection means preferentially selects, based on the photographing information, a vehicle whose traveling direction includes the event occurrence location within a photographing range of the photographing means.
According to this configuration, it is possible to carefully select and acquire images that show the location where the event occurred.

4. In the above embodiment,
The selection means selectively selects a vehicle that is less likely to be affected by backlight on the photographing means, based on the photographing information.
According to this configuration, it is possible to carefully select and acquire images that are relatively less affected by backlight.

5. In the above embodiment,
The photographing information includes information indicating the speed of the vehicle,
The selection means preferentially selects a slow vehicle based on the photographic information.
According to this configuration, it is possible to carefully select and acquire images in which image blur is suppressed.

6. In the above embodiment,
The photographing information includes information indicating the installation height of the photographing means in the vehicle,
The selection means preferentially selects a vehicle in which the photographing means is installed at a high height, based on the photographing information.
According to this configuration, it is possible to carefully select and acquire images in which the event occurrence location is photographed from a bird's-eye view.

7. In the above embodiment,
The photographing information includes information indicating the resolution of the photographing means,
The selection means preferentially selects a vehicle whose resolution of the photographing means is high based on the photographing information.
According to this configuration, images with higher quality can be carefully selected and acquired.

8. In the above embodiment,
The photographing information includes information indicating a lighting state of a headlight of the vehicle,
The selection means preferentially selects a vehicle whose headlights are turned on based on the photographic information.
According to this configuration, vehicles with their headlights on tend to have higher quality and clarity of images captured by the camera than vehicles without their headlights on. , it is possible to carefully select and acquire higher quality and clearer images.

9. In the above embodiment,
The predetermined distance is set to be shorter when the event occurs at night than when it occurs during the day.
According to this configuration, the distance that can be recognized by the photographing means tends to be shorter at night than during the day, and images taken in dark conditions at night may not clearly show the location of the event. The acquisition of such images can be reduced.

10. In the above embodiment,
The second acquisition means acquires a video photographed by the photographing means at a predetermined photographing time as the image,
The photographing time is set to be longer when the event occurs at night than when it occurs during the day.
According to this configuration, there is less traffic at night than during the day, making it difficult to obtain useful images. Therefore, by setting the shooting time to be longer at night than during the day, it is possible to Images (videos) can be acquired.

11. In the above embodiment,
The number of vehicles selected by the selection means is set to be larger when the event occurs at night than when it occurs during the day.
According to this configuration, there is less traffic at night than during the day, making it difficult to obtain useful images. , useful images can be obtained even at night.

12. In the above embodiment,
The first acquisition means acquires the photographing information at the time of event occurrence,
The second acquisition means acquires an image photographed by the photographing means when an event occurs.
According to this configuration, it is possible to obtain an image of the event location at the time the event occurs.

13. In the above embodiment,
The first acquisition means acquires the photographing information after the event occurs,
The second acquisition means acquires an image photographed by the photographing means after an event occurs.
According to this configuration, an image of the event location after the event occurrence can be acquired.

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

10: server device, 11: processing unit, 11a: detection unit, 11b: first acquisition unit, 11c: selection unit, 11d: second acquisition unit, 20: vehicle, 24: photographing unit, 100: image management system

Claims (24)

An image management system for managing images,
a detection means for detecting the occurrence of an event;
a first acquisition means for acquiring photographic information regarding a state of a photographing means of a vehicle from each of a plurality of vehicles within a predetermined distance from a location where the event occurs when the event occurrence is detected by the detecting means;
Selection means for selecting a vehicle from among the plurality of vehicles to preferentially acquire an image photographed by the photographing means, based on the photographing information acquired by the first acquiring means;
second acquisition means for acquiring the image from the vehicle selected by the selection means;
Equipped with
The image management system is characterized in that the predetermined distance is set to be shorter when the event occurs at night than when the event occurs during the day . The photographing information includes information indicating the position of the vehicle,
The image management system according to claim 1, wherein the selection means preferentially selects a vehicle that is close to the event location based on the photographic information. The photographing information includes information indicating a traveling direction of the vehicle,
3. The selecting means preferentially selects, based on the photographing information, a vehicle whose traveling direction includes the event occurrence location within the photographing range of the photographing means. Image management system. 4. The image management system according to claim 3, wherein the selection means selectively selects a vehicle that is less likely to be affected by backlight in the photographing means, based on the photographing information. The photographing information includes information indicating the speed of the vehicle,
The image management system according to any one of claims 1 to 4, wherein the selection means preferentially selects a slow vehicle based on the photographic information. The photographing information includes information indicating the installation height of the photographing means in the vehicle,
The image management system according to any one of claims 1 to 5, wherein the selection means preferentially selects a vehicle in which the photographing means is installed at a high height, based on the photographing information. . The photographing information includes information indicating the resolution of the photographing means,
7. The image management system according to claim 1, wherein the selection means preferentially selects a vehicle whose resolution of the photographing means is high based on the photographing information. The photographing information includes information indicating a lighting state of a headlight of the vehicle,
8. The image management system according to claim 1, wherein the selection means preferentially selects a vehicle whose headlights are turned on based on the photographic information. The second acquisition means acquires a video photographed by the photographing means at a predetermined photographing time as the image,
The image according to any one of claims 1 to 8 , wherein the photographing time is set to be longer when the event occurs at night than when the event occurs during the day. management system. The number of vehicles selected by the selection means is set to be larger when the event occurs at night than when the event occurs during the day. The image management system according to item 1. The first acquisition means acquires the photographing information at the time of event occurrence,
11. The image management system according to claim 1, wherein the second acquisition means acquires an image photographed by the photographing means when an event occurs. The first acquisition means acquires the photographing information after the event occurs,
11. The image management system according to claim 1, wherein the second acquisition means acquires an image photographed by the photographing means after an event occurs. An image management system for managing images,
a detection means for detecting the occurrence of an event;
a first acquisition means for acquiring photographic information regarding a state of a photographing means of a vehicle from each of a plurality of vehicles within a predetermined distance from a location where the event occurs when the event occurrence is detected by the detecting means;
Selection means for selecting a vehicle from among the plurality of vehicles to preferentially acquire an image photographed by the photographing means, based on the photographing information acquired by the first acquiring means;
second acquisition means for acquiring the image from the vehicle selected by the selection means;
Equipped with
The photographing information includes information indicating a lighting state of a headlight of the vehicle,
The image management system is characterized in that the selection means preferentially selects vehicles whose headlights are turned on based on the photographic information. An image management system for managing images,
a detection means for detecting the occurrence of an event;
a first acquisition means for acquiring photographic information regarding a state of a photographing means of a vehicle from each of a plurality of vehicles within a predetermined distance from a location where the event occurs when the event occurrence is detected by the detecting means;
Selection means for selecting a vehicle from among the plurality of vehicles to preferentially acquire an image photographed by the photographing means, based on the photographing information acquired by the first acquiring means;
second acquisition means for acquiring the image from the vehicle selected by the selection means;
Equipped with
The second acquisition means acquires a video photographed by the photographing means at a predetermined photographing time as the image,
The image management system is characterized in that the photographing time is set to be longer when the event occurs at night than when the event occurs during the day. An image management system for managing images,
a detection means for detecting the occurrence of an event;
a first acquisition means for acquiring photographic information regarding a state of a photographing means of a vehicle from each of a plurality of vehicles within a predetermined distance from a location where the event occurs when the event occurrence is detected by the detecting means;
Selection means for selecting a vehicle from among the plurality of vehicles to preferentially acquire an image photographed by the photographing means, based on the photographing information acquired by the first acquiring means;
second acquisition means for acquiring the image from the vehicle selected by the selection means;
Equipped with
The image management system is characterized in that the number of vehicles selected by the selection means is set to be larger when the event occurs at night than when the event occurs during the day. A program for causing a computer to function as each means of the image management system according to any one of claims 1 to 15 . An image management method in which a server device manages images, the method comprising:
a detection step of detecting the occurrence of an event;
When the event occurrence is detected in the detection step, a first acquisition step of acquiring photographic information regarding the state of the photographing means of the vehicle from each of a plurality of vehicles within a predetermined distance from the event occurrence location;
a selection step of selecting a vehicle from among the plurality of vehicles to preferentially acquire an image photographed by the photographing means, based on the photographic information acquired in the first acquisition step;
a second acquisition step of acquiring the image from the vehicle selected in the selection step;
including;
The image management method is characterized in that the predetermined distance is set to be shorter when the event occurs at night than when the event occurs during the day . An image management method in which a server device manages images, the method comprising:
a detection step for detecting the occurrence of an event;
When the event occurrence is detected in the detection step, a first acquisition step of acquiring photographic information regarding the state of the photographing means of the vehicle from each of a plurality of vehicles within a predetermined distance from the event occurrence location;
a selection step of selecting a vehicle from among the plurality of vehicles to preferentially acquire an image photographed by the photographing means, based on the photographic information acquired in the first acquisition step;
a second acquisition step of acquiring the image from the vehicle selected in the selection step;
including;
The photographing information includes information indicating a lighting state of a headlight of the vehicle,
The image management method is characterized in that, in the selection step, vehicles whose headlights are turned on are selected preferentially based on the photographic information. An image management method in which a server device manages images, the method comprising:
a detection step of detecting the occurrence of an event;
When the event occurrence is detected in the detection step, a first acquisition step of acquiring photographic information regarding the state of the photographing means of the vehicle from each of a plurality of vehicles within a predetermined distance from the event occurrence location;
a selection step of selecting a vehicle from among the plurality of vehicles to preferentially acquire an image photographed by the photographing means, based on the photographic information acquired in the first acquisition step;
a second acquisition step of acquiring the image from the vehicle selected in the selection step;
including;
In the second acquisition step, a video photographed by the photographing means at a predetermined photographing time is acquired as the image;
The image management method is characterized in that the photographing time is set to be longer when the event occurs at night than when the event occurs during the day. An image management method in which a server device manages images, the method comprising:
a detection step of detecting the occurrence of an event;
When the event occurrence is detected in the detection step, a first acquisition step of acquiring photographic information regarding the state of the photographing means of the vehicle from each of a plurality of vehicles within a predetermined distance from the event occurrence location;
a selection step of selecting a vehicle from among the plurality of vehicles to preferentially acquire an image photographed by the photographing means, based on the photographic information acquired in the first acquisition step;
a second acquisition step of acquiring the image from the vehicle selected in the selection step;
including;
An image management method characterized in that the number of vehicles selected in the selection step is set to be larger when the event occurs at night than when the event occurs during the day. A server device that manages images,
a detection means for detecting the occurrence of an event;
a first acquisition means for acquiring photographic information regarding a state of a photographing means of a vehicle from each of a plurality of vehicles within a predetermined distance from a location where the event occurs when the event occurrence is detected by the detecting means;
Selection means for selecting a vehicle from among the plurality of vehicles to preferentially acquire an image photographed by the photographing means, based on the photographing information acquired by the first acquiring means;
second acquisition means for acquiring the image from the vehicle selected by the selection means;
Equipped with
The server device is characterized in that the predetermined distance is set to be shorter when the event occurs at night than when the event occurs during the day . A server device that manages images,
a detection means for detecting the occurrence of an event;
a first acquisition means for acquiring photographic information regarding a state of a photographing means of a vehicle from each of a plurality of vehicles within a predetermined distance from a location where the event occurs when the event occurrence is detected by the detecting means;
Selection means for selecting a vehicle from among the plurality of vehicles to preferentially acquire an image photographed by the photographing means, based on the photographing information acquired by the first acquiring means;
second acquisition means for acquiring the image from the vehicle selected by the selection means;
Equipped with
The photographing information includes information indicating a lighting state of a headlight of the vehicle,
The server device is characterized in that the selection means preferentially selects a vehicle whose headlights are turned on based on the photographic information. A server device that manages images,
a detection means for detecting the occurrence of an event;
a first acquisition means for acquiring photographic information regarding a state of a photographing means of a vehicle from each of a plurality of vehicles within a predetermined distance from a location where the event occurs when the event occurrence is detected by the detecting means;
Selection means for selecting a vehicle from among the plurality of vehicles to preferentially acquire an image photographed by the photographing means, based on the photographing information acquired by the first acquiring means;
second acquisition means for acquiring the image from the vehicle selected by the selection means;
Equipped with
The second acquisition means acquires a video photographed by the photographing means at a predetermined photographing time as the image,
The server device according to claim 1, wherein the photographing time is set to be longer when the event occurs at night than when the event occurs during the day. A server device that manages images,
a detection means for detecting the occurrence of an event;
a first acquisition means for acquiring photographic information regarding a state of a photographing means of a vehicle from each of a plurality of vehicles within a predetermined distance from a place where the event occurs when the event occurrence is detected by the detecting means;
Selection means for selecting a vehicle from among the plurality of vehicles to preferentially acquire an image photographed by the photographing means, based on the photographing information acquired by the first acquiring means;
second acquisition means for acquiring the image from the vehicle selected by the selection means;
Equipped with
The server device according to claim 1, wherein the number of vehicles selected by the selection means is set to be larger when the event occurs at night than when the event occurs during the day.