Information processing device, information processing method, and information processing program

Abstract

To provide an information processing device, an information processing method, and an information processing program, capable of classifying an image.SOLUTION: The information processing device includes a first acquisition part for acquiring a plurality of pieces of image information which are generated by imaging a subject and on which an imaging time and an imaging position are recorded, a second acquisition part for acquiring the interval of the imaging time among the plurality of pieces of image information acquired by the first acquisition part, a third acquisition part for acquiring the distance of the imaging position among the plurality of pieces of image information acquired by the first acquisition part, and a classification part for performing classification so that the captured image is classified to a first classification destination, when the interval of the imaging time acquired by the second acquisition part is relatively short and the distance of the imaging position acquired by the third acquisition part is relatively short.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present disclosure relates to an information processing device, an information processing method, and an information processing program. [Background technology]

[0002] Conventionally, when an icon recorded in map information is clicked, information such as a photo corresponding to the icon is displayed. Meanwhile, in Patent Document 1, an image captured by a mobile phone (image with location information) is transmitted to an image management device. Furthermore, the image management device registers the image and location information in a database, and when a map image delivery request is received, an icon is generated in relation to the image, and the icon is delivered superimposed on the coordinates on the map image corresponding to the shooting location. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2004-266636 A Summary of the Invention [Problem to be solved by the invention]

[0004] The device described in the above-mentioned Patent Document 1 only registers captured images in map information. However, when creating road maps or taking images for various tasks such as at work sites, a large number of images may be taken. Even when a large number of images are taken, one or more images selected from the large number of images may be used when making a specified report. For this reason, in order to relatively shorten the work time and efficiently select images, for example, it is preferable to classify the large number of images in advance according to predetermined conditions.

[0005] The present disclosure provides an information processing device, an information processing method, and an information processing program capable of classifying images. [Means for solving the problem]

[0006] An information processing device of one embodiment includes a first acquisition unit that acquires multiple image information generated by capturing images of a subject and in which image capture times and image capture positions are recorded, a second acquisition unit that acquires the interval between the image capture times between the multiple image information acquired by the first acquisition unit, a third acquisition unit that acquires the distance between the image capture positions between the multiple image information acquired by the first acquisition unit, and a classification unit that classifies the captured image to be a first classification destination when the interval between the image capture times acquired by the second acquisition unit is relatively short and the distance between the image capture positions acquired by the third acquisition unit is relatively short. Effect of the Invention

[0007] The information processing device, the information processing method, and the information processing program disclosed herein can classify images. [Brief description of the drawings]

[0008] [Figure 1] FIG. 1 is a diagram illustrating an information processing device according to an embodiment. [Diagram 2] FIG. 1 is a block diagram illustrating an information processing device according to an embodiment. [Diagram 3] 1A and 1B are diagrams for explaining an example of performing imaging a plurality of times in a series of imaging processes (imaging sessions), in which (A) is a diagram showing a series of imaging processes (imaging sessions) in chronological order, and (B) is a diagram showing the positional relationship of imaging positions. [Figure 4] FIG. 1 is a diagram showing image information 1 to 3 of a series of imaging processes (photographing sessions) in chronological order. [Diagram 5] FIG. 13 is a diagram for explaining an example of classification for each series of imaging processes (photographing sessions). [Figure 6] 1 is a flowchart illustrating an information processing method according to an embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] An embodiment will be described below.

[0010] [Overview of information processing device 100] First, an overview of an information processing device 100 according to an embodiment will be described. FIG. 1 is a diagram illustrating an information processing device 100 according to an embodiment.

[0011] The information processing device 100 may be configured as an image classification device that classifies one or a plurality of images according to a predetermined condition, etc. The information processing device 100 is not limited to the above-mentioned example device, and may be configured as various devices, etc. The information processing device 100 may be a computer such as a server, a desktop, a laptop, a tablet, or a smartphone.

[0012] The information processing device 100 acquires a plurality of pieces of image information. That is, the information processing device 100 may acquire the image information from the imaging unit 131, for example. The information processing device 100 acquires the interval between the image capturing times of the plurality of pieces of image information based on the time information. 1 and the imaging time t 2 Distance t 12 Get the. In addition, the information processing device 100 acquires the distance between the imaging positions of the plurality of pieces of image information based on the position information. 1 and the imaging position p of the second image information. 2 Distance p 12 Get the. The information processing device 100 detects the interval t 12 is relatively short, and the distance p 12is relatively short, the captured images (for example, the first image information and the second image information) are classified as the first classification destination. The information processing device 100 may classify the captured images according to the difference between the multiple folders in which the captured images are stored. The "classification destination" such as the first classification destination is a place where image information is stored, and may be called a "folder" as an example. Note that the first classification destination may be, for example, a place where the most recently captured image information is stored.

[0013] [Details of the information processing device 100] Next, the information processing device 100 according to an embodiment will be described in detail. FIG. 2 is a block diagram illustrating the information processing device 100 according to an embodiment.

[0014] The information processing device 100 includes, for example, a communication unit 121, a storage unit 122, a display unit 123, an imaging unit 131, and a control unit 110. The communication unit 121, the storage unit 122, and the display unit 123 may be an embodiment of an output unit. The control unit 110 includes, for example, a first acquisition unit 111, a second acquisition unit 112, a third acquisition unit 113, a classification unit 114, a comparison unit 115, and an output control unit 116. The control unit 110 may be configured, for example, by an arithmetic processing device of the information processing device 100. The control unit 110 (for example, an arithmetic processing device) may realize the functions of each unit (the first acquisition unit 111, the second acquisition unit 112, the third acquisition unit 113, the classification unit 114, the comparison unit 115, and the output control unit 116) by, for example, appropriately reading and executing various programs stored in the storage unit 122.

[0015] The communication unit 121 is, for example, a communication interface capable of transmitting and receiving various information to and from a device (external device) (not shown) outside the information processing device 100. The external device may be a server, a user terminal, etc. The user terminal may be, for example, a desktop, a laptop, a tablet, a smartphone, etc.

[0016] The storage unit 122 may store, for example, various information and programs. Examples of the storage unit 122 may be a memory, a solid state drive, a hard disk drive, etc. Note that the storage unit 122 may be, for example, a storage area and a server on a cloud.

[0017] The display unit 123 is, for example, a display capable of displaying various characters, symbols, images, and the like.

[0018] The imaging unit 131 may be a camera that generates image information by capturing an image of a subject. The imaging unit 131 may be a camera (for example, a built-in camera) that is attached to the information processing device 100, or an external camera that is externally attached (connected) to the outside of the information processing device 100. The imaging unit 131 may record, for example, the imaging time and imaging position when capturing an image of the subject in the image information.

[0019] The first acquisition unit 111 acquires a plurality of pieces of image information that are generated by capturing an image of a subject and in which the image capturing time and the image capturing position are recorded. That is, the first acquisition unit 111 acquires the image information generated by the image capturing unit 131.

[0020] For example, when the imaging unit 131 is an external camera, the first acquisition unit 111 may acquire image information from the imaging unit 131 (external camera) via the communication unit 121. Furthermore, for example, when the imaging unit 131 is an external camera, the first acquisition unit 111 may acquire image information from an external memory connected to the imaging unit 131 (external camera) if the image information is recorded in the external memory connected to the imaging unit 131 (external camera) and the external memory is then connected to an interface of the information processing device 100.

[0021] Here, the imaging unit 131 generates image information by capturing an image of a subject. At that time, the imaging unit 131 may record, for example, the time when the subject is captured (capture time) in the image information. In addition, the imaging unit 131 may record, for example, position information (information on the position where the subject is captured) acquired using GNSS or the like in the image information.

[0022] The first acquisition unit 111 may acquire image information generated by capturing an image of an object relatively close to the road as a subject. The subject may be various objects, and may be, for example, an object relatively close to the road. Examples of the subject (object) may include a traffic light, a sign, a road (for example, an intersection), a lane on the road (for example, an intersection), a building, a facility, a feature, and the like.

[0023] The second acquisition unit 112 acquires the imaging time intervals between the multiple pieces of image information acquired by the first acquisition unit 111 . As an example, the second acquisition unit 112 may acquire the interval between the time (imaging time) when the first image was captured after the camera function was activated (after the start of a series of image capture processes described later) and each of the times (imaging times) when one or more images were captured thereafter. That is, the second acquisition unit 112 may acquire the interval between the imaging time of the image information obtained by the first imaging and each of the imaging times of the image information obtained by the subsequent imaging.

[0024] Alternatively, as an example, the second acquisition unit 112 may acquire the interval from the time when the camera function is activated (when a series of imaging processes described below is started) as a reference (start time) to the time when an image is captured thereafter (imaging time). That is, the second acquisition unit 112 may acquire the interval between the start time and each of the imaging times of image information acquired by imaging. In this case, acquisition of "the imaging time interval between a plurality of image information" by the second acquisition unit 112 may include acquisition of "the interval between the start time and each of the imaging times of image information acquired by imaging."

[0025] Alternatively, as an example, when the plurality of pieces of image information include a first piece of image information and a second piece of image information captured after the first piece of image information, the second acquisition unit 112 acquires the image capture time t 1 and the imaging time t 2 The time interval between 12In this case, the second acquisition unit 112 may acquire, for example, two pieces of image information immediately preceding (or following) the imaging time as a reference, that is, the interval between the imaging times of two consecutive pieces of image information among two or more pieces of image information arranged in chronological order. The second acquisition section 112 may acquire the interval between the imaging times of two or more pieces of non-consecutive image information (for example, one or more pieces of image information spaced apart) among two or more pieces of image information arranged in chronological order based on the imaging times.

[0026] The third acquisition unit 113 acquires the distance between the imaging positions of the multiple pieces of image information acquired by the first acquisition unit 111 . As an example, the third acquisition unit 113 may acquire the distance from the position (imaging position) where the first image was captured after the camera function was activated (after the start of a series of image capturing processes described later) to each of the positions (imaging positions) where images were captured one or more times thereafter. That is, the second acquisition unit 112 may acquire the distance between the imaging position of the image information obtained by the first image capturing and each of the imaging positions of the image information obtained by the subsequent image capturing.

[0027] Alternatively, as an example, the third acquisition unit 113 may acquire the distance from the position where the camera function was activated (the position where a series of imaging processes described below is started) as a reference (start position) to the position where an image was subsequently captured (imaging position). That is, the third acquisition unit 113 may acquire the distance between the start position and each of the imaging positions of image information acquired by imaging. In this case, the acquisition of "the distance between the imaging positions of a plurality of image information" by the third acquisition unit 113 may include the acquisition of "the distance between the start position and each of the imaging positions of image information acquired by imaging."

[0028] In the above case, the "position where the first image was taken (imaging position)" and the "start position" may be the position (or the center position, etc.) of a characteristic point on the road adjacent to the imaging position and the start position. The characteristic point on the road may be, for example, an intersection, an entrance and exit of a motorway, a tunnel, a parking lot, a point where the number of lanes decreases, a point where the number of lanes increases, a building, a facility, a feature, etc. In this case, the third acquisition unit 113 may, for example, refer to map information (e.g., a road map, etc.) stored in the memory unit 122 to identify the position where the first image was captured (imaging position) and the position of a characteristic point on the road that is relatively close (e.g., closest, etc.) to the starting position.

[0029] Alternatively, as an example, when the plurality of pieces of image information include a first piece of image information and a second piece of image information captured after the first piece of image information, the third acquisition unit 113 acquires the imaging position p 1 and the imaging position p of the second image information. 2 Distance p 12 Get the. In this case, the third acquisition unit 113 may acquire, for example, the distance between the imaging positions of two pieces of image information that are immediately preceding (or following) the imaging time, i.e., two or more pieces of consecutive image information that are arranged in chronological order. The third acquisition section 113 may acquire the distance between the imaging positions of two or more pieces of non-consecutive image information (e.g., one or more pieces of image information spaced apart) among two or more pieces of image information arranged in chronological order based on the shooting time.

[0030] The classification unit 114 classifies the captured image (image information) to be the first classification destination when the interval between the imaging times acquired by the second acquisition unit 112 is relatively short and the distance between the imaging positions acquired by the third acquisition unit 113 is relatively short. That is, the classification unit 114 may change the classification destination of the image information according to the interval between the imaging times and the distance between the imaging positions. For example, when the interval between the imaging times of a plurality of image information is equal to or less than a first threshold and the distance between the imaging positions of the plurality of image information is equal to or less than a second threshold, the classification unit 114 may store the plurality of image information in the first classification destination (for example, a first folder, etc.). In addition, the classification unit 114 may classify the multiple image information into a third classification destination (e.g., a third folder, etc.) different from the first classification destination (and the second classification destination described later) when, for example, the interval between the imaging times of the multiple image information exceeds a first threshold value and / or when the distance between the imaging positions of the multiple image information exceeds a second threshold value.

[0031] The first threshold and the second threshold are set to values ​​for estimating that one or more pieces of image information were captured at the same (or substantially the same, etc.) location, i.e., the same location. For example, the first threshold and the second threshold may be changed depending on the size of the same location and the location.

[0032] 3A and 3B are diagrams for explaining an example of performing imaging multiple times in a series of imaging processes (imaging sessions). Fig. 3A is a diagram showing a series of imaging processes (imaging sessions) in chronological order, and Fig. 3B is a diagram showing the positional relationship of imaging positions.

[0033] As a specific example, the classification unit 114 may change the classification destination depending on, for example, the elapsed time after the start of a series of imaging processes (photographing session) described below and the imaging range (distance between imaging points) of the series of imaging processes (photographing session). That is, the classification unit 114 classifies the time t 0 , or the time (imaging time) t when the first image was captured in a series of imaging processes (imaging sessions) 1 It is also possible to identify one or more image information (image information 1, 2) captured within a predetermined time (less than or equal to a first threshold) based on the reference (reference time), and one or more image information (image information 3) captured after the predetermined time (greater than the first threshold) (see Figure 3 (A)). The classification unit 114 also classifies the position p 0 , or the position (reference position) p at which the first image was captured in a series of image capture processes (photographing sessions) 1It is also possible to identify one or more image information (image information 1, 2) captured within a predetermined distance L (less than or equal to the second threshold) from the center, and one or more image information (image information 3) captured outside the predetermined distance L (exceeding the second threshold) (see Figures 3(A) and 3(B)). In this case, the classification unit 114 classifies the reference time (time t 0 Or time t 1 ) within a predetermined time and at the reference position (position p 0 Alternatively, each of a plurality of pieces of image information (image information 1, 2) captured within a predetermined distance from position p1 may be classified into the same first classification destination (for example, a first folder, etc.). In this case, the classification unit 114 may classify each of one or more pieces of image information (image information 3) captured outside the predetermined time into another classification destination (e.g., a folder, etc.) (third classification destination) different from the first classification destination (e.g., the first folder, etc.). Similarly, the classification unit 114 may classify each of one or more pieces of image information (image information 3) captured outside the predetermined distance into another classification destination (e.g., a folder, etc.) (third classification destination) different from the first classification destination (e.g., the first folder, etc.).

[0034] FIG. 4 is a diagram showing image information 1 to 3 of a series of imaging processes (photographing sessions) in chronological order.

[0035] Alternatively, as an example, the classification unit 114 may classify the image capturing time interval t 12 is equal to or smaller than a first threshold value set in advance, and the distance p 12 is equal to or smaller than a preset second threshold, the plurality of image information (first image information (image information 1) and second image information (image information 2)) may be classified into a first classification destination (see FIG. 4). As a specific example, the classification unit 114 may store the plurality of image information (first image information and second image information) in the first classification destination (first folder).

[0036] Here, when there are first to third image information (image information 1 to 3) as the multiple image information, the image capturing time t 1 and the imaging time t of the second image information (image information 2). 2 Distance t 12 , and the imaging time t of the second image information (image information 2) 2 and the imaging time t of the third image information (image information 3). 3 Distance t 23 Each is relatively short (the interval t 12 ,t 23 Both are equal to or smaller than the first threshold value, and the imaging position p 1 and the imaging position p of the second image information (image information 2). 2 Distance p 12 , and the imaging position p of the second image information (image information 2) 2 and the imaging position p of the third image information (image information 3). 3 Distance p 23 Each is relatively short (the distance p 12 , p 23 If both of the first to third image information (image information 1 to 3) are equal to or smaller than the second threshold value, the classification section 114 may classify the first to third image information (image information 1 to 3) into the same first classification destination (for example, the first folder, etc.).

[0037] For example, if there are three or more pieces of image information in which the interval between the imaging times of two chronologically consecutive (adjacent) pieces of image information is equal to or less than a first threshold value and furthermore the distance between the imaging positions is equal to or less than a second threshold value, the classification unit 114 may classify the multiple pieces of image information together into the same first classification destination (e.g., a first folder, etc.). As a specific example, as illustrated in FIG. 4, when there are three or more pieces of image information, 1st to nth image information (image information 1 to n) arranged in chronological order of imaging time, the classification unit 114 classifies the interval t 12 ,t 23 ,t 34 …t (n-2)(n-1) The distance p between the imaging positions of the image information (image information 1 to (n-1)) that are adjacent in time series is equal to or less than the first threshold value. 12,p 23 ,p 34 …p (n-2)(n-1) While each of them is equal to or less than the second threshold, the image capturing times t (n-1) ,t n Interval t (n-1)n exceeds the first threshold value, or the imaging positions p (n-1) ,p n Distance p (n-1)n exceeds the second threshold, the first to (n-1) image information (image information 1 to (n-1)) are classified into the same first classification destination (for example, the first folder, etc.).

[0038] As an example of this case, the classification unit 114 classifies the time t n Subsequent image information (for example, subsequent image information including the n-th image information (image information n~ (see FIG. 4))) may be classified into a classification destination (for example, a folder, etc.) different from the first classification destination (for example, a first folder, etc.). That is, in at least one of the cases where the interval between the imaging times acquired by the second acquisition section 112 is relatively long and the distance between the imaging positions acquired by the third acquisition section 113 is relatively long, the classification section 114 may classify the captured images into a third classification destination different from the first classification destination (and a second classification destination described later).

[0039] FIG. 5 is a diagram for explaining an example of classification for each series of imaging processes (photographing sessions).

[0040] When a series of imaging processes is performed multiple times when an object is imaged once or multiple times, and there are a first and a second imaging process, the classification unit 114 may classify the image information from the second imaging process as a first classification destination and the image information from the first imaging process as a second classification destination different from the first classification destination (see FIG. 5). A series of imaging processes may be called, for example, a "photography session." A series of imaging processes (photography sessions) may be, for example, from the start of a camera (or the start of an imaging application) when imaging a subject to the stop of the camera (or the end of the imaging application). Or, a series of imaging processes (photography sessions) may be, for example, from the start of a camera (or the start of an imaging application) when imaging a subject to the transmission of image information to an external device under the control of the output control unit 116 described later. In a series of imaging processes (photography sessions), for example, it is possible to image a subject once or multiple times using a camera function. Also, the imaging unit 131 can perform imaging processes (photography sessions) once or multiple times. The imaging unit 131 may perform imaging processes (photography sessions) for each subject, or for each location where one or multiple subjects are present. Here, the location may be, for example, a location with a group such as an intersection, an entrance or exit of a motorway, a tunnel, a parking lot, a building, or a facility. That is, the location may be, for example, the location of various features on a road, a road map, traffic, or the like.

[0041] When a series of photographing processes (photographing sessions) is performed multiple times, the classification unit 114 may classify the images into different classification destinations (e.g., folders, etc.) for each series of photographing processes (photographing sessions). As a specific example, the classification unit 114 may classify one or more pieces of image information captured in a first photographing process (photographing session) into a second classification destination (e.g., first folder, etc.) and classify one or more pieces of image information captured in a second photographing process (photographing session) into the first classification destination (e.g., second folder, etc.). The classification unit may increase the classification destination number when the series of photographing processes is older, and may generate a newer classification destination (with a smaller number value) when the series of photographing processes is more recent. This makes it possible to identify image information generated by more recent imaging, depending on the size of the classification destination number.

[0042] In addition, even if a series of imaging processes (photographing sessions) is performed multiple times, for example, if the interval between the imaging times of at least one piece of image information captured in a first series of imaging processes (photographing sessions) and at least one piece of image information captured in a second series of imaging processes (photographing sessions) is less than or equal to a first threshold value and the distance between the imaging positions is less than or equal to a second threshold value, the classification unit 114 may group the image information captured in each of the first series of imaging processes (photographing sessions) and the second series of imaging processes (photographing sessions) into one group and store the image information in a classification destination (e.g., a folder, etc.) in units of groups generated by the grouping.

[0043] The classification unit 114 may group a plurality of image information pieces estimated to have been captured within the same location based on the image capture process, the interval between image capture times, and the distance between image capture positions, and change the classification destination for each group generated by the grouping. It is considered that one subject or a plurality of subjects within the same location are captured in one series of image capture processes (image capture session). In addition, when the interval between the image capture times of adjacent pieces of image information pieces in the chronological order of the image capture times is relatively short (for example, when the interval is equal to or less than a first threshold value), it is considered that one or a plurality of subjects are captured within the same location. In addition, when the distance between the image capture positions of adjacent pieces of image information pieces in the chronological order of the image capture times is relatively short (for example, when the interval is equal to or less than a second threshold value), it is considered that one or a plurality of subjects are captured within the same location.

[0044] The range of the same point may be, for example, within a predetermined distance from a certain point. The certain point may be set arbitrarily. The point may be, for example, an intersection, an entrance or exit of a motorway, a tunnel, a parking lot, a building, a facility, etc., as described above. As a specific example, when the point is an intersection, it may be within a predetermined distance from the center of the intersection. Moreover, the range of the same point may be within a predetermined distance from the imaging position of the image information generated by performing the first imaging.

[0045] The classification unit 114 may group one or more pieces of image information that are presumed to have been captured within the range of the same point into one group, and store each group (on a group basis) in a different classification destination (for example, a folder, etc.).

[0046] The comparison unit 115 may compare a plurality of pieces of image information after being classified by the classification unit 114. That is, the comparison unit 115 may compare a plurality of pieces of image information stored in the same or different classification destinations (e.g., folders, etc.), for example.

[0047] The comparison unit 115 may compare the Exif information of the multiple pieces of image information. For example, the image capture time (time information) and the image capture position (position information) are recorded in the Exif information. Therefore, the comparison unit 115 may compare the time information and position information recorded in each of the multiple pieces of image information. For example, the comparison unit 115 may estimate whether the time information and position information recorded in each of the multiple pieces of image information are the same (or approximately the same). Approximately the same may mean, for example, within a predetermined time or within a predetermined distance.

[0048] Furthermore, the comparison unit 115 may compare the subjects recorded in each of the multiple pieces of image information as the comparison. As an example, the comparison unit 115 may recognize the subject using a known image recognition technology and compare the subjects recorded in the multiple pieces of image information. For example, the comparison unit 115 may estimate whether the subjects recorded in each of the multiple pieces of image information are the same.

[0049] The comparison unit 115 may determine that the similarity of each of the multiple image information (e.g., similarity of images and subjects) is relatively high when at least one of the cases where it is estimated that the time information and the position information recorded in each of the multiple image information are the same (or approximately the same) and when it is estimated that the subjects recorded in each of the multiple image information are the same. The comparison unit 115 may leave at least one image information for multiple image information (a group of multiple image information) with a relatively high similarity among the multiple image information, and exclude the remaining image information so that it is not selected by the user of the information processing device 100. In other words, the comparison unit 115 may make at least one of the remaining image information selectable by the user for multiple image information (a group of multiple image information) with a relatively high similarity.

[0050] The output control unit 116 controls the image information selected from the plurality of pieces of image information classified by the classification unit 114 to be output to an external device. The output control unit 116 may control the communication unit 121 to transmit, for example, one or more pieces of image information selected from one or more pieces of image information classified into one classification destination (for example, a folder, etc.) to an external device. That is, when the output control unit 116 receives a selection of image information in response to an input unit (not shown) such as a keyboard and a mouse being operated by a user of the information processing device 100, the output control unit 116 may control the output unit to output the selected image information. The output unit may be, for example, the communication unit 121, the storage unit 122, the display unit 123, etc. That is, the output control unit 116 may, for example, control the communication unit 121 to transmit the selected image information to an external device (not shown). The external device may be a server, a management terminal, or the like. The management terminal may be, for example, a terminal used by a company. Examples of the management terminal may be a desktop, a laptop, a tablet, or the like. The output control unit 116 may, for example, control the storage unit 122 to store the selected image information. The output control unit 116 may, for example, control the display unit 123 to display an image based on the selected image information.

[0051] [Information processing method] Next, an information processing method according to an embodiment will be described. FIG. 6 is a flowchart illustrating an information processing method according to an embodiment.

[0052] In step ST101, the first acquisition unit 111 acquires a plurality of pieces of image information that are generated by capturing an image of a subject and in which an image capturing time and an image capturing position are recorded. The first acquisition unit 111 may acquire image information that is generated by capturing an image of an object that is relatively close to a road as the subject.

[0053] In step ST102, the second acquisition section 112 acquires the imaging time intervals between the multiple pieces of image information acquired in step ST101.

[0054] In step ST103, the third acquisition section 113 acquires the distance between the imaging positions of the plurality of pieces of image information acquired in step ST101.

[0055] In step ST104, if the interval between the imaging times acquired in step ST102 is relatively short and the distance between the imaging positions acquired in step ST103 is relatively short, the classification unit 114 classifies the captured image (image information) into the first classification destination.

[0056] In step ST105, when a series of imaging processes (photographing sessions) is performed multiple times, the classification unit 114 may change the classification destination for each imaging process (photographing session). As an example, when a series of imaging processes (photographing sessions) is performed multiple times when an object is imaged once or multiple times, and the imaging processes include a first and second times, the classification unit 114 may classify the image information during the second imaging process (photographing session) as a first classification destination and the image information during the first imaging process (photographing session) as a second classification destination different from the first classification destination.

[0057] In step ST106, the classification unit 114 may classify the captured image into a third classification destination different from the first classification destination and the second classification destination when at least one of the following cases is true: the interval between the imaging times obtained in step ST102 is relatively long; and the distance between the imaging positions obtained in step ST103 is relatively long.

[0058] In step ST107, the classification unit 114 may group together a plurality of pieces of image information that are estimated to have been captured within the same range based on the imaging process (imaging session), the interval between imaging times, and the distance between imaging positions, and change the classification destination for each group generated by the grouping.

[0059] The number of classification destinations is not limited to three, the first to third classification destinations, as described above, but may be two, or may be four or more. The classification unit 114 may change the classification destination according to various conditions including a series of imaging processes (imaging session), imaging time, imaging position, and the like.

[0060] [Functions and circuits] Next, the functions and circuits of the above-mentioned information processing device 100 will be described. Each unit of the information processing device 100 may be realized as a function of a computer's arithmetic processing device or the like. That is, the first acquisition unit 111, the second acquisition unit 112, the third acquisition unit 113, the classification unit 114, the comparison unit 115, and the output control unit 116 (control unit 110) of the information processing device 100 may be realized as a first acquisition function, a second acquisition function, a third acquisition function, a classification function, a comparison function, and an output control function (control function) by the computer's arithmetic processing device or the like, respectively. The information processing program can cause a computer to realize each of the above-mentioned functions. The information processing program may be recorded in a non-transitory computer-readable recording medium, such as a memory, a solid-state drive, a hard disk drive, or an optical disk. The recording medium may be referred to as a non-transitory computer-readable medium, for example. As described above, each unit of the information processing device 100 may be realized by an arithmetic processing device of a computer or the like. The arithmetic processing device or the like is configured by, for example, an integrated circuit or the like. Therefore, each unit of the information processing device 100 may be realized as a circuit constituting the arithmetic processing device or the like. That is, the first acquisition unit 111, the second acquisition unit 112, the third acquisition unit 113, the classification unit 114, the comparison unit 115, and the output control unit 116 (control unit 110) of the information processing device 100 may be realized as a first acquisition circuit, a second acquisition circuit, a third acquisition circuit, a classification circuit, a comparison circuit, and an output control circuit (control circuit) constituting the arithmetic processing device of a computer or the like. The communication unit 121, the storage unit 122, and the display unit 123 (output unit) of the information processing device 100, and the imaging unit 131 may be realized as, for example, a communication function, a storage function, and a display function (output function) including the functions of an arithmetic processing device, and an imaging function. The communication unit 121, the storage unit 122, and the display unit 123 (output unit) of the information processing device 100, and the imaging unit 131 may be realized as, for example, a communication circuit, a storage circuit, and a display circuit (output circuit), and an imaging circuit by being configured by an integrated circuit, etc. The communication unit 121, the storage unit 122, and the display unit 123 (output unit) of the information processing device 100, and the imaging unit 131 may be realized as, for example, a communication device, a storage device, and a display device (output device), and an imaging device by being configured by a plurality of devices.

[0061] The information processing device 100 can combine one or any two or more of the above-mentioned units. In this disclosure, the term "information" is used, but the term "information" can be replaced with "data" and the term "data" can be replaced with "information."

[0062] [Aspects and Effects of the Present Embodiment] Next, one aspect of this embodiment and the effects of each aspect will be described. Note that each aspect described below is an example at the time of filing, and this embodiment is not limited to the aspects described below. In other words, this embodiment is not limited to each aspect described below, and may be realized by appropriately combining each of the above-mentioned parts. In addition, a lower aspect may be able to cite any of the higher aspects. The effects described below are merely examples, and the effects of each aspect are not limited to those described below. Each aspect may, for example, have at least one of the effects described below.

[0063] (Aspect 1) An information processing device of one embodiment includes a first acquisition unit that acquires multiple image information generated by capturing images of a subject and in which image capture times and image capture positions are recorded, a second acquisition unit that acquires the interval between the image capture times between the multiple image information acquired by the first acquisition unit, a third acquisition unit that acquires the distance between the image capture positions between the multiple image information acquired by the first acquisition unit, and a classification unit that classifies the captured image to be a first classification destination when the interval between the image capture times acquired by the second acquisition unit is relatively short and the distance between the image capture positions acquired by the third acquisition unit is relatively short. This allows the information processing device to classify the image information. Also, by classifying the image information according to the timing of shooting, the information processing device makes it easier to specify the timing at which the image was shot even when there is a large amount of image information, and makes it easier for the user to select image information with the shooting timing required.

[0064] For example, a field survey may be conducted when preparing a road map. A field survey may be conducted by a professional company, but may also be conducted simply by employees of the company that prepares the road map. A simple survey may be conducted, for example, when an employee notices an increase in the number of lanes on a road or improvements to an intersection early on and takes a still image or the like to report the change to the company. By obtaining information on changes in the field early on, the company can improve the convenience of users of the road map by quickly preparing the road map or conducting a detailed field survey. On the other hand, when employees conduct simple surveys, many images are often stored in one classification destination (folder), so when selecting images to report to the company from the many images, they may be unsure which images to select.In addition, even when simple surveys are conducted at multiple sites at different times, many images are stored in one classification destination (folder), so when selecting images that are the result of a simple survey of one site, there is a risk that images from simple surveys of a different site will be selected. For this reason, there is a need to classify captured images appropriately. In this regard, the information processing device of this embodiment estimates that the images were taken at the same location when the interval between the image capture times and the distance between the image capture positions are relatively short based on the image capture times and image capture positions, and stores multiple pieces of image information in the same classification destination (e.g., folder) or the like. Therefore, when reporting a simple investigation, an employee can easily understand that the image information was taken at the same location by checking the image information stored in the classification destination (e.g., a folder, etc.), and the possibility of selecting image information taken at a different location can be reduced. Therefore, the information processing device can improve the convenience of employees, etc., increase the accuracy of the simple investigation, and also enable employees, etc. to continue to perform simple investigations due to the ease of selecting image information.

[0065] (Aspect 2) In one embodiment of the information processing device, the classification unit may classify image information from the second imaging process as a first classification destination and image information from the first imaging process as a second classification destination different from the first classification destination when a series of imaging processes is performed multiple times when an image of a subject is captured once or multiple times, and there is a first and second imaging process. This allows the information processing device to classify each imaging process (photographing session) into a different classification destination, making it easier for the user to identify the imaging process (photographing session) that they require from among multiple imaging processes (photographing sessions).

[0066] (Aspect 3) In one embodiment of the information processing device, the classification unit may classify the captured image into a third classification destination different from the first classification destination and the second classification destination when at least one of the following cases is true: the interval between the imaging times acquired by the second acquisition unit is relatively long, and the distance between the imaging positions acquired by the third acquisition unit is relatively long. Thereby, the information processing device can estimate whether the image information was captured at the same point or different points based on at least one of the interval between the shooting times and the distance between the shooting positions, and can classify the image information captured at the same point into the same classification destination and the image information captured at different points into different classification destinations. In other words, the classification unit can classify the image information captured at different points into the same classification destination by grouping the different points.

[0067] (Aspect 4) In one embodiment of the information processing device, the classification unit may group together multiple pieces of image information that are estimated to have been captured within the same range based on the imaging process, the interval between imaging times, and the distance between imaging positions, and change the classification destination for each group generated by the grouping. This allows the information processing device to group image information that is estimated to have been taken at the same location into one group and classify each group into a different classification destination, making it easier to identify image information taken at the same location and reducing the possibility of selecting image information taken at a different location.

[0068] (Aspect 5) In one embodiment of the information processing device, the first acquisition unit may acquire image information generated by capturing an image of an object that is relatively close to the road as a subject, and may include an output control unit that controls the output of image information selected from the multiple image information classified by the classification unit to an external device. In this manner, the information processing device can select image information for each classification destination, and can reduce the possibility of selecting image information from a different classification destination. The information processing device can transmit the selected image information to an external device.

[0069] (Aspect 6) In one aspect of the information processing method, a computer executes a first acquisition step of acquiring multiple image information generated by capturing an image of a subject and in which the image capturing time and the image capturing position are recorded, a second acquisition step of acquiring the interval between the image capturing times between the multiple image information acquired by the first acquisition step, a third acquisition step of acquiring the distance between the image capturing positions between the multiple image information acquired by the first acquisition step, and a classification step of classifying the captured image to be the first classification destination when the interval between the image capturing times acquired by the second acquisition step is relatively short and the distance between the image capturing positions acquired by the third acquisition step is relatively short. As a result, the information processing method can achieve the same effects as the information processing device according to the above-described aspect.

[0070] (Aspect 7) An information processing program of one embodiment causes a computer to realize a first acquisition function that acquires multiple image information generated by capturing an image of a subject and in which the image capturing time and image capturing position are recorded, a second acquisition function that acquires the interval between the image capturing times between the multiple image information acquired by the first acquisition function, a third acquisition function that acquires the distance between the image capturing positions between the multiple image information acquired by the first acquisition function, and a classification function that classifies the captured image to be the first classification destination when the interval between the image capturing times acquired by the second acquisition function is relatively short and the distance between the image capturing positions acquired by the third acquisition function is relatively short. As a result, the information processing program can achieve the same effects as the information processing device according to the above-described aspect. [Explanation of symbols]

[0071] 100 Information processing device 110 Control section 111 First acquisition part 112 Second Acquisition Department 113 Third Acquisition Department 114 Classification Department 115 Comparison Section 116 Output control section 121 Communications Department 122 Storage section 123 Display section 131 Imaging unit

Claims

1. a first acquisition unit that acquires a plurality of pieces of image information generated by capturing an image of a subject and in which an image capturing time and an image capturing position are recorded; a second acquisition unit that acquires an interval between image capture times of the plurality of pieces of image information acquired by the first acquisition unit; a third acquisition unit that acquires a distance between imaging positions of the plurality of pieces of image information acquired by the first acquisition unit; a classification unit that classifies the captured image into a first classification destination when the interval between the image capturing times acquired by the second acquisition unit is relatively short and the distance between the image capturing positions acquired by the third acquisition unit is relatively short; An information processing device comprising:

2. The classification unit classifies image information during the second imaging process as a first classification destination and image information during the first imaging process as a second classification destination different from the first classification destination when a series of imaging processes is performed multiple times when an object is imaged once or multiple times and the imaging processes include a first and second times. The information processing device according to claim 1 .

3. The classification unit classifies the captured image into a third classification destination different from the first classification destination and the second classification destination when at least one of an interval between the imaging times acquired by the second acquisition unit is relatively long and a distance between the imaging positions acquired by the third acquisition unit is relatively long. The information processing device according to claim 2 .

4. The classification unit groups together a plurality of pieces of image information that are estimated to have been captured within a range of the same point based on the image capture process, the interval between image capture times, and the distance between image capture positions, and changes the classification destination for each group generated by the grouping.

4. The information processing device according to claim 2 or 3.

5. The first acquisition unit acquires image information generated by capturing an image of an object that is relatively close to a road as a subject, an output control unit that controls so that image information selected from the plurality of image information classified by the classification unit is output to an external device; The information processing device according to claim 4.

6. The computer a first acquisition step of acquiring a plurality of pieces of image information generated by capturing an image of a subject, the image information including a capture time and a capture position; a second acquisition step of acquiring an interval between image capturing times of the plurality of pieces of image information acquired by the first acquisition step; a third acquisition step of acquiring distances between imaging positions of the plurality of pieces of image information acquired by the first acquisition step; a classification step of classifying the captured image into a first classification when the interval between the imaging times acquired in the second acquisition step is relatively short and the distance between the imaging positions acquired in the third acquisition step is relatively short; An information processing method for performing the above.

7. On the computer, a first acquisition function for acquiring a plurality of pieces of image information generated by capturing an image of a subject and in which a capture time and a capture position are recorded; a second acquisition function that acquires an interval between image capture times of the plurality of pieces of image information acquired by the first acquisition function; a third acquisition function that acquires distances between imaging positions of a plurality of pieces of image information acquired by the first acquisition function; a classification function that classifies the captured image into a first classification destination when the interval between the image capturing times acquired by the second acquisition function is relatively short and the distance between the image capturing positions acquired by the third acquisition function is relatively short; An information processing program that realizes this.

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