JP7305461B2 - IMAGE PROVIDING SYSTEM, IMAGE PROVIDING DEVICE, CONTROL METHOD THEREOF, AND PROGRAM - Google Patents

Description

The present invention relates to an image providing system, an image providing device, a control method thereof, and a program.

There is a demand for photographing users having fun at sports games and tourist facilities. Japanese Patent Application Laid-Open No. 2004-100001 discloses that when a user sitting in the audience seats inputs a photographing request such as a photographing area and photographing time, a camera photographs the area where the spectators are located based on the inputted photographing request.

JP 2007-142896 A

In the method of Patent Document 1, when there are spectators at different positions, there is a possibility that the request for photographing of each spectator cannot be met. On the other hand, when trying to meet the demands of all the spectators, the amount of image data increases, and there is a possibility that images cannot be provided quickly. SUMMARY OF THE INVENTION In view of such problems, it is an object of the present invention to provide images to more spectators quickly.

An image providing system according to the present invention includes acquisition means for acquiring information about a seat to be photographed among a plurality of seats, and instruction means for instructing an image pickup device to photograph an image including the plurality of seats in the angle of view range. , providing means for providing the image, and control means for controlling an imaging interval at which the imaging device is caused to take images based on the information obtained by the obtaining means.

According to the present invention, images can be quickly provided to a larger number of spectators.

It is a figure which shows the example of facility arrangement|positioning in the image provision system in this embodiment. It is a figure which shows the system configuration example of the image provision system in this embodiment. 1 is a diagram illustrating a configuration example of an image processing apparatus according to an embodiment; FIG. FIG. 5 is a diagram showing an example of setting trimming positions for each seat in this embodiment. FIG. 5 is a diagram showing an example of setting trimming positions for each seat in this embodiment. It is a figure which shows the example of the data structure in this embodiment. It is a flow chart which shows an example of ticket purchase processing in this embodiment. It is a flow chart which shows an example of processing of pre-match setting in this embodiment. It is a flowchart which shows the example of the process after the game start in this embodiment. 6 is a flow chart showing an example of trimming processing according to the embodiment; It is a figure which shows the example of seat arrangement according to the number of people of the group in this embodiment. It is a figure which shows the relationship of the seat in seat arrangement in this embodiment. It is a figure which shows the example of a data structure which stored the calculation method of the trimming position in this embodiment. It is a figure which shows the example of a data structure which stored the calculation method of the trimming position in this embodiment. It is a figure which shows the calculation example of the trimming position in this embodiment. It is a figure which shows the example of a system configuration|structure in the case of providing an image after the completion|finish of a game in this embodiment. It is a figure which shows the example of a system configuration|structure in the case of providing an image after the completion|finish of a game in this embodiment. 6 is a flow chart showing an example of a series of photographing processes according to the present embodiment; 6 is a flow chart showing an example of a series of photographing processes during a game in this embodiment. 9 is a flow chart showing another example of a series of photographing processes during a match in this embodiment. 9 is a flow chart showing another example of a series of photographing processes during a match in this embodiment.

BEST MODE FOR CARRYING OUT THE INVENTION An embodiment of the present invention will be described below with reference to the drawings. However, the components described in the embodiments shown below are merely examples, and the scope of the present invention is not intended to be limited to them.

FIG. 1 is a diagram showing an example of facility layout for performing remote control imaging in an image providing system according to this embodiment. In FIG. 1, a baseball stadium is used as an example for convenience of explanation, but it is applicable to facilities where many spectators can view from fixed positions, such as stadiums for sports competitions and arenas for concerts.

In the example of the baseball field shown in FIGS. 1A, 1B, and 1C, the photographing instruction unit 101 simultaneously instructs the cameras 102 to 105 for photographing the spectator seats on the first base side. In this example, the number of cameras is assumed to be four for the sake of simplicity of explanation, but the number of cameras is arbitrary as long as it is physically possible to simultaneously issue shooting instructions.

When shooting from the upper row of the audience seats on the opposite side of a stadium, etc., the distance to the audience (subject) is long. Therefore, even if a telephoto lens with a large focal length is used, a certain number of spectators will fit within one frame, so trimming processing for each seat and each group is required. Also, telephoto lenses with long focal lengths are expensive, so if you try to reduce investment, you cannot increase the focal length, and the number of people who can fit in one frame increases, so the need for trimming increases. become.

As for the photographing instruction, there are provided two means for performing interval photographing for periodic photographing (for example, issuing a release instruction once every 10 seconds, etc.) and manual photographing according to the operator's intention of photographing.

In addition, depending on the facility, a higher price may be set for a position where it is easy to see a game or event, and a lower price may be set for a position where it is difficult to see, and there are usually multiple types of tickets. FIGS. 1(a), (b), and (c) show an example in which there are an area 1 near the ground, an area 2 with the largest number of seats, and an area 3, each of which is a separated space. Area 1 is for spectators who want to watch the game closer, and because the number of seats is limited, it is an area where a small number of people, such as families, often watch the game on special occasions, rather than in units of dozens of people. is. Therefore, providing a memorable image only by the members who came together leads to an improvement in the audience's satisfaction. Area 2 is an area where many fans who come to watch the game with high frequency are watching the game, and enthusiastic fans are sitting together. In Area 2, there are various types of spectators, such as spectators who have come to watch the game as an experience, and spectators who are not very enthusiastic about the game itself. Therefore, it is an area where some spectators want images of the game while others consider it unnecessary, and providing images according to the spectators' intentions improves the satisfaction of the spectators. Area 3 improves customer satisfaction by providing images of spectators enjoying watching games in the space and images of specific spectators making good expressions. As mentioned above, the needs of the audience differ depending on the area. In order to meet the needs of all spectators, it is necessary to prepare shot images according to various patterns. There is also the issue of Also, by providing images while the spectators are watching the game, the spectators' level of satisfaction with the game can be further improved. If you try to process the data as well, the processing will take a long time, and it will take time to provide the image.

Since it can be determined that the spectators in areas 1 and 3 are likely to purchase the photographed images, in FIG. , and in FIG. 1B, area 1 is covered by two cameras 104 and 105 as well. As a result, the number of people who can fit in the image is reduced, and the audience appears larger, so the resolution of the trimmed image is increased, and an image with higher commercial value can be obtained, which leads to purchase. In area 3, the resolution of the trimmed image is further increased by photographing a range narrower than area 1 with two cameras. In area 3, a trimmed image with higher resolution can be obtained, so image analysis of the captured image is also possible. In Area 3, there are often multiple spaces including the viewing space due to its structure. , etc., it is possible to obtain an image with higher marketability than area 1. Alternatively, in Area 1, since the spectators are not always in a position where they can be photographed by the cameras, it is possible to observe multiple partitioned spaces with a single camera and photograph the spectators using a pan head. You may shoot a specific space according to the situation.

FIG. 1(c) shows a configuration diagram for giving a photographing instruction from the photographing instruction device 101 to each camera group. The photographing instruction device 101 can issue photographing instructions to a plurality of camera groups A to D as shown in FIG. 1(c). In the example shown in FIG. 1(c), camera group C covers a wide outfield seat area 4 with four cameras, and camera group D covers a wide outfield seat area 5 with four cameras.

The cameras 102 to 105 are camera units each composed of an imaging device (imaging sensor) composed of a CCD, a CMOS device, or the like that converts an optical image into an electric signal. A camera consists of a lens group (shooting lens) including a zoom lens and a focus lens, a shutter with an aperture function, an image sensor, an A/D converter that converts the analog signal output from the image sensor into a digital signal, and an imaging system. Includes a barrier to cover and prevent dirt and damage. An image processing unit in the camera performs resizing processing such as predetermined pixel interpolation and reduction, and color conversion processing on data acquired by imaging with the camera. A CPU in the camera performs exposure control, distance measurement control, AWB (auto white balance) processing, etc. based on the calculation results obtained by the image processing unit.

The image data for display imaged by the camera and image-processed by the image processing unit is displayed on the display 04 of a PC (personal computer), which will be described later. A digital signal captured by a camera, A/D converted by an A/D converter, and stored in a RAM is converted to analog by a D/A converter, transferred sequentially to the display 04, and displayed as a live view display. (LV display) can be performed. The live view can be displayed in a still image shooting standby state, a moving image shooting standby state, or when recording a moving image, and the imaged subject image is displayed almost in real time.

The CPU controls the camera and image processing so as to start operations such as AF (autofocus) processing, AE (automatic exposure) processing, AWB processing, etc., in response to shooting preparation instructions based on user operations performed with the input device 06. control the department. The CPU on the camera side performs main exposure in response to a photographing instruction, reads the signal from the image sensor, processes the captured image in the image processing section to generate an image file, and records the image in an external storage. control the operation of a series of shooting processes (actual shooting). The shooting instruction can be given by a user operation on the input device 06 of the PC 201a or by pressing the shutter button on the camera side. The camera is capable of taking still images and moving images.

Depending on the facility, the shooting distance and illuminance differ depending on the location of the camera to be shot and the area of the seat. Sometimes it comes. Therefore, the price may be changed or the number of sheets provided may be increased according to the image quality. Also, instead of simply setting a high price for seats that are close to the ground and close to the camera, there are cases where high prices are set for seats with better image quality depending on conditions such as brightness and the number of cameras. There is also

FIG. 2 is a diagram showing a system configuration example of an image providing system according to this embodiment. The image processing apparatus 201 has a shooting instruction unit 101 , a PC (personal computer) 201 a , an image transfer reception unit 201 b , a trimming unit 202 , a selection/upload unit 203 , and storages 204 and 205 . In FIG. 2, the processing units 101, 201a, 201b, 202, and 203 are shown in one image processing device 201, but they may be physically separate processing devices. are not intended to limit the invention.

The photographing instruction unit 101 issues photographing instructions to the cameras 102 to 105 at the same time as in FIG. As for the photographing instruction, there are provided two means for performing interval photographing for periodic photographing (for example, issuing a release instruction once every 10 seconds) and manual photographing according to the operator's intention of photographing.

The image transfer reception unit 201b records in the storage 204 the image data of the images captured by the cameras 102 to 105, which are transferred from the camera side. FTP (File Transfer Protocol) or the like is used as a protocol for transmitting and receiving image data.

The trimming unit 202 performs trimming processing on each image data with the transfer of the image data from the cameras 102 to 105 to the storage 204 as a trigger, and records the trimmed image and the seat number in the storage 205 . When performing the trimming process, information such as the number of people in the group purchased in advance, the seat number, and the seating arrangement is obtained from the ticket purchase unit 206, which will be described later, and the trimming process is performed based on the information. will be described later with reference to FIGS. 10 to 15. FIG. Although the storages 204 and 205 are shown as separate storages in this example, they may be physically the same.

The selection/upload unit 203 uploads the trimmed image data, the seat number, and the date and time information of the event stored in the storage 205 to the distribution unit (distribution server) 207 . When the shooting instruction unit 101 performs interval shooting during a competition or an event, a large number of trimmed images are created. 207 for uploading. As for the selection method, for example, the target image may be visually selected from a list of images, or the data for that time may be extracted by inputting a specific time. not something to do. When the photographing instruction unit 101 only performs manual photographing by the operator, the photographing instruction is normally given in a scene where the audience is excited.

The ticket purchase unit 206 is a mechanism for a user to purchase a ticket, and the processing at the time of purchase will be described later with reference to FIG. The user inputs the desired date and number of seats and pays the price, thereby obtaining the desired number of seat numbers.

Based on the event date and seat number input by the user, the distribution unit 207 presents the user with the image data group of the relevant seat number on the relevant date. As for input by the user, the user may manually input by looking at the ticket, or may print a QR code (registered trademark) on the ticket, read it with a smartphone, and recognize it. The input method does not limit the invention. In addition, the image data group may be presented to the user by a smart phone application, or by a web application accessed through a browser. do not have.

FIG. 3 shows an example configuration of a PC 201a (personal computer) in the image processing apparatus 201 as an example of an apparatus to which the present invention can be applied. The image processing apparatus 201 may be composed of a plurality of electronic devices, or may be composed of a single PC.

3, a CPU 01, a ROM 02, a RAM 03, a display 04, a HDD (hard disk drive) 05, an input device 06, a media drive 07, and an I/F (interface) 08 are connected to an internal bus 09. FIG. Each unit connected to the internal bus 09 can exchange data with each other via the internal bus 09 .

The CPU 01 uses the RAM 03 as a work memory to control each part of the PC 201a according to a program stored in the ROM 02, for example. The ROM 02 stores image data, audio data, other data, various programs for the operation of the CPU 01, and the like. The ROM02 is composed of a non-volatile memory such as a ROM, for example. The RAM 03 is, for example, a RAM (a volatile memory using a semiconductor element, etc.).

The display 04 displays an image, a GUI screen constituting a GUI (Graphical User Interface), etc., under the control of the CPU 01 . The CPU 01 controls each part of the PC 201 a to generate a display control signal according to a program, generate a video signal to be displayed on the display 04 , and output the video signal to the display 04 . A display 04 displays an image based on the output image signal. The configuration of the PC 201a itself includes an interface for outputting a video signal to be displayed on the display 04, and the display 04 may be configured by an external monitor (television, etc.).

The HDD 105 stores various programs, data, and the like. The input device 06 is an input device for accepting user operations, including character information input devices such as keyboards, pointing devices such as mice and touch panels, buttons, dials, joysticks, touch sensors, and touch pads. It should be noted that the touch panel is an input device that is laid flat on the display 04 and outputs coordinate information corresponding to the touched position. The media drive 07 drives and controls, for example, a removable storage medium. The I/F 08 is an interface for communicating with an external device of the PC 201a.

4 and 5 are diagrams showing examples of setting the trimming position for each seat in this embodiment. FIG. 4 shows an example of setting the trimming position for an image captured by a camera almost in front of the audience. As shown in FIG. 4A, a rectangle of the trimming position is defined for each seat, and the horizontal direction is defined as the X axis and the vertical direction is defined as the Y axis. is stored as a data structure shown in FIG. 6, which will be described later. By performing this operation for each seat included in the photographed image, the trimming positions of all seats are designated as shown in FIG. 4(b). Here, the rectangle at the trimming position is exemplified as a rectangular rectangle, but any rectangle that can be expressed in a coordinate system, such as a polygonal or elliptical rectangle definition, can be used, and the shape of the rectangle limits the present invention. not a thing

FIG. 5 shows an example of setting the trimming position for an image captured by a camera slightly obliquely above the audience. Similarly to the example shown in FIG. 4, by defining a rectangle of the trimming position for each seat and defining the coordinate system of the X-axis and Y-axis, even if the seat position is slanted, the upper left vertex position 501 and The coordinates of the lower right vertex position 502 can be stored as a data structure shown in FIG. 6, which will be described later.

FIG. 6 is a diagram showing an example of a data structure that stores the trimming position of each seat in the embodiment of the invention. The data structure for storing the trimming position of each seat includes a row number 601, a seat number 602, a camera number 603, an X coordinate 604 of the upper left vertex, a Y coordinate 605 of the upper left vertex, and an X coordinate of the lower right vertex. 606 and the Y coordinate 607 of the lower right vertex. In the data structure 600, the X coordinate and the Y coordinate are managed in separate columns, but they may be managed in one column as list information such as (X, Y). Also, although the row number 601 and the seat number 602 are numerical data in FIG. 6, they may be character string data such as alphabets. Coordinate information 604 to 607 record numerical data representing pixel positions.

In the present embodiment, it will be described that an image is provided by taking photographs of spectators watching a baseball game as users and trimming the images of the spectators formed into a group. However, the example of the baseball game described in this embodiment is just an example, and the present invention can be applied to other sports games, sightseeing spots, theater performances, and the like.

Ticket purchase processing in this embodiment will be described with reference to FIG. FIG. 7 is a flow chart showing an example of processing when a user purchases a ticket in an application or Internet site for purchasing a ticket. This processing is realized by developing a program recorded in a ROM (non-volatile memory) 02 or the like in a RAM (system memory) 03 and executing it by the CPU 01 .

In S701, the CPU 01 receives an input of the number of purchased tickets from the user.
In S702, the CPU 01 receives an input as to whether or not the user intends to purchase the image. The input in this S702 may allow the user to select whether or not to purchase the image directly on the purchase screen, or the ticket and image purchase are set, and the ticket purchase and image purchase can be selected. You can do it all at once. Also, some seats may be set with image purchase without the user's selection, and the user may have an intention to purchase the image when the target seat is selected.

In S703, the CPU 01 determines whether or not there is an intention to purchase the image in the input in S702. If it is determined that the user intends to purchase the image, the process advances to S704; otherwise, the process advances to S706.

In S704, the CPU01 selects the seat designated by the user. At this time, the user may select one representative seat to present a plurality of patterns of seat positions corresponding to the number of tickets purchased in S701, thereby allowing the user to easily select a seat. Further, in the image trimming process, which will be described later with reference to FIG. 10, the trimming range is changed according to the designation of the seat position by the user.

In S705, the CPU01 generates group information based on the information received in S704. The group information is information that associates the representative seat with the seat positions of the simultaneously purchased tickets input in S701. Even if there is only one user, in S705 information is generated in association with the seat as group information. As for the group information, other seats may be added to the same group by inputting the information described on the tickets that were not purchased at the same time through an application or Internet site. However, it is desirable that the seats forming the group are adjacent vertically or horizontally. This is because, when trimming, there is a possibility that the images of the distant seats may not be captured by a single trimming range because they may be captured by different cameras. Also, if the trimmed image includes many other seats that are not included in the group, the size of each person is reduced.
In S706, the CPU01 selects the seat designated by the user.

Next, referring to FIG. 8, the setting process before the start of the game in this embodiment will be described. FIG. 8 is a flow chart showing an example of the pre-game setting process according to the present embodiment. This processing indicates processing performed by the image processing device 201 before the start of the match. In this process, the power of the image processing device 201 is turned on before the game, and an instruction is given from the system operator to start preparations for the target game, or before a predetermined time such as three hours before the game or the day before the game. will start. This processing is realized by developing a program recorded in a ROM (non-volatile memory) 02 or the like in a RAM (system memory) 03 and executing it by the CPU 01 .

In S<b>801 , the CPU 01 connects with the distribution unit 207 and the ticket purchase unit 206 .
In S<b>802 , the CPU 01 acquires the ticket information of the target match from the ticket purchase unit 206 . The ticket information includes information on the number of purchased tickets of a group purchased at the same time, the seat position, and the seat arrangement necessary for the trimming process. In addition, in order to select images with higher commercial value, information on the type of seat, information on the area such as infield, outfield, VIP, information on whether the seat is in the area to be photographed, non-reserved seat or a reserved seat. Furthermore, information on whether or not the user frequently watches matches, information on whether or not the user is a member of a fan club, etc., may also be included.

In S803, the CPU 01 calculates the trimming range based on the information acquired in S802. The CPU 01 acquires the trimming position calculation method for each pattern and the number of people defined in FIGS. 13 and 14, which will be described later, using the number of people in the group and the layout pattern acquired in S802, and calculates the trimming range. The trimming range here refers to a rectangular rectangle surrounded by the two vertices as the X and Y coordinates of the upper left vertex of the rectangle to be trimmed and the X and Y coordinates of the lower right vertex. point to Here, a rectangle defined by two vertices is used, but any rectangle that can be represented by a coordinate system, such as a polygon or an ellipse, can be used. not something to do.

13 and 14 are diagrams showing an example of a data structure storing a trimming range calculation method according to this embodiment. FIG. 13 shows an example of definition for an image taken almost from the front of the audience as shown in FIG. 4, and FIG. It shows an example definition for

As shown in FIGS. 13 and 14, the group number 1301 and seat arrangement pattern 1302 are managed. In addition, the X coordinate calculation method 1303 of the upper left vertex position, the Y coordinate calculation method 1304 of the upper left vertex position, the X coordinate calculation method of the lower right vertex position 1305, the Y coordinate calculation method of the lower right vertex position 1306, and the information 1307 of the outside group seat. to manage.

The group number 1301 and seat arrangement pattern 1302 match the purchased group number and seat arrangement acquired in advance from the ticket purchase unit 206, respectively. In the examples shown in FIGS. 13 and 14, the coordinate calculation methods 1303 to 1306 use the trimming position information of any seat position within the group. I don't mind. The out-of-group seat information 1307 defines information on seat positions that are not purchased as seats within the group, but which fit inside the rectangle in the seating arrangement pattern.

In S804, the CPU 01 prepares face data. Based on the information acquired in S802, face data is prepared for users who frequently watch matches, that is, spectators whose faces have been detected many times in the past, and spectators who are members of fan clubs. Keep As a result, when there is a spectator whose face is determined to match the face in the prepared face data in the captured image, the images of the specific spectator are linked and collected as data, and collectively provided to the specific spectator. can do. In addition, spectators who have joined the fan club will be able to look back on the game after the match season is over, as the images will be collected automatically, even if they do not indicate their intention to purchase images each time they purchase a ticket. Depending on the spectator, the frequency with which they watch the game varies greatly, so there may be spectators who want multiple images in one game, and spectators who want images from all the games they have watched, although one image per game is sufficient. have a nature. Therefore, by preparing the face data as described above, the image can be provided without requiring the spectators who frequently watch the game to indicate their intention to purchase the image each time. Also, images can be provided even if the user forgets to indicate his or her intention to purchase the images. Furthermore, even if you sit in a non-reserved seat where you do not know the seat position, you can collect images of a specific spectator. It should be noted that, instead of the information obtained at the time of ticket purchase acquired in S802, a plan for the spectator to purchase the image separately from the purchase of the spectator ticket is provided. It may also be possible to provide an image of how the game was watched each time. In the above cases, by preparing face data, it is possible to smoothly provide images to spectators during a game.

In S805, the CPU 01 sets the clock.
In S806, the CPU 01 inputs shooting factors. The shooting factor may be a period of interval shooting such as 10 seconds or 20 seconds, or may be based on detection such as when the cheers of the audience exceed a predetermined level. In addition, we have prepared a control unit that analyzes the state of the game that has been filmed and analyzes the game data. , may be switched to video shooting. Alternatively, the interval shooting may be stopped during the break time and started when an event such as a cheering battle or a quiz occurs during the break time. Needless to say, manual shooting instructions may be combined.

In S807, as a system test, the CPU 01 actually activates the camera to perform shooting and trimming. Based on the captured image, you can set the shooting conditions according to the brightness and lighting conditions of the day, and crop the target seat when trimming the captured image based on the coordinates associated with the seat. You can check if it is possible. It is also possible to place a subject on the side of the seat as an index point and check whether or not the subject in the image captured by the camera is at predetermined coordinates.
In S808, the CPU 01 sets imaging conditions based on the system test in S807.

Next, processing after the game starts will be described with reference to FIGS. 9(a) to 9(c). FIGS. 9A to 9C are flowcharts showing an example of processing after the start of a match in this embodiment. 9A shows processing of the image processing apparatus 201, FIG. 9B shows processing related to shooting, and FIG. 9C shows processing for trimming and distributing an image. Each process is started before the match starts or before the start of shooting before the start of the match. This processing is realized by developing a program recorded in ROM (non-volatile memory) 02 in RAM (system memory) 03 and executing it by CPU 01 .

In S901, the CPU 01 acquires intermediate ticket information. The midway ticket information is information about tickets purchased after the start of the game or after the process of S802 in FIG. This information may be obtained from the ticket purchase unit 206, or may be notified from the ticket purchase unit 206 to the image processing apparatus 201 periodically or each time there is an update.

In S902, the CPU01 acquires information about the camera corresponding to camera c=1. In S902, information about the imaging range of the camera c=1 and the target seat is acquired.
In S903, the CPU 01 determines whether or not the number of cameras c currently being processed is greater than the total number K of cameras. Otherwise, the process proceeds to S904.

In S<b>904 , the CPU 01 acquires trimming information in the range of seats to be photographed from the position of the target camera c.
In S905, the CPU 01 acquires the shooting factor in the range of the seat to shoot from the position of the target camera c. For example, when team A and team B are playing against each other, it may be better to change the shooting interval period depending on the timing of offense and defense. Also, depending on the type of seat, it may be better to shoot more frequently. Therefore, by acquiring the photographing factors according to the seats included in the photographing range of the camera, it is possible not to photograph many images that are highly likely not to be provided to the audience, and to avoid missing photographing opportunities. Note that the shooting factors in S905 may be the same for all cameras.

When a new ticket is purchased or a new image purchase intention is indicated by the spectator, that is, when a new trimming group is generated, the processing of S803 and S804 in FIG. 8 is performed in S904 and S905.
In S906, the CPU 01 sets camera c=c+1 as in S902, and acquires information about the next camera.

In S907, the CPU 01 determines whether or not a predetermined time has passed. The predetermined time is the time from S901 when the determination in S907 is performed for the first time after the process of FIG. 9 is started, and the time after the previous determination of YES in S907 when the determination is made for the second time or later. S907 is for obtaining intermediate ticket information at predetermined time intervals. If the determination in S907 is YES, the process proceeds to S901; otherwise, the process proceeds to S908.

In S908, the CPU 01 determines whether or not there was a shooting factor for shooting in S905. If the determination in S908 is YES, the process proceeds to S909; otherwise, the process proceeds to S907.
In S909, the CPU 01 notifies the camera of an instruction to shoot.
In S910, the CPU 01 notifies the trimming unit 202 of the trimming information. Since the trimming information and the information about shooting factors are updated at predetermined time intervals, even spectators who purchased tickets in the middle of the match can obtain trimmed images from the middle of the match.

In S911, the CPU 01 determines whether to end the process, that is, whether to end the game and end the shooting. If it is to end, the process proceeds to S912; otherwise, the process proceeds to S901.
In S912, the CPU 01 notifies the camera of turning off the power.

As described above, in the processing shown in FIG. 9A, the trimming information is sent to the trimming unit 202 almost at the same time as the photographing instruction, so the registered trimming processing can be quickly performed after photographing. When the image is sent from the camera side to the storage 204, the trimming part 202 grasps the group to be trimmed and calculates the trimming range, so that the trimming process is quickly performed and the image can be confirmed by the audience.

Next, processing related to photographing in FIG. 9B will be described. The processing in FIG. 9B is processing performed in each camera.
In S930, the CPU 01 causes the camera side to acquire the shooting conditions.
In S931, the camera determines whether or not a photographing instruction has been issued. If a photographing instruction has been issued, the process advances to S932, and if not, the camera waits for a photographing instruction.

In S932, the camera performs shooting under the set shooting conditions.
In S933, the CPU 01 controls to transfer the image from the camera to the image transfer reception unit 201b. The transferred image data is stored in the storage 204 . Alternatively, the images captured by the camera are sequentially transferred to the storage 204 .
In S934, the CPU 01 determines whether or not to end the processing of FIG. 9B. The determination in S934 is YES when an instruction to turn off the power of the camera is received in S912 of FIG. 9A. If it is determined in S934 that the process of FIG. 9B is to be ended, the process of FIG. 9B is ended; otherwise, the process proceeds to S931.

Next, processing for trimming and distributing the image in FIG. 9C will be described.
In S951, the CPU 01 determines whether an instruction to acquire an image has been issued. An instruction to acquire an image is an event time such as the time of a home run or the time of a fine play in the case of baseball, based on the clock time set in S805 of FIG. This is an instruction to acquire an image taken at . It is assumed that an image acquisition instruction is issued in response to occurrence of an event time. It should be noted that even if it is not the event time, for example, the game may be analyzed, and the CPU 01 may simultaneously issue an image shooting instruction and an image acquisition instruction in response to the occurrence of an event.

In S<b>952 , the CPU 01 acquires the target image from the storage 204 .
In S953, the trimming unit 202 acquires trimming information.

In the processing after S954, the trimming processing is started.
In S954, the trimming unit 202 acquires the information of n=1 seats. Let m be the number of seats in the shooting range of the camera that shot the image to be trimmed. In the present embodiment, the seat numbers are set from n=1 to m for simplicity, but not limited to this, all seats that are photographed by one camera and are subject to trimming are covered. If so, it may be linked to the seats actually used in the ballpark. In order to cover the seats of the audience with a plurality of cameras, the photographing range and the photographing range of the other cameras may overlap. Even if the spectator is photographed by two cameras, an image trimmed from the image photographed by one of the cameras is provided. Therefore, the photographing range of the camera and the trimming range may differ. In S954, the number of seats in all trimming ranges is acquired as m. The trimming range may be variable during the game, or may be determined in advance by the stadium side.

In S955, the CPU 01 determines whether or not the seat is in the trimming area. In a stadium, there may be areas where cameras are blind spots due to nets, poles, roofs, etc., or where photography is prohibited. Also, in areas such as unreserved seats where the positions of the spectators are unknown, trimming corresponding to the positions of the seats is not performed in the first place. Therefore, in such a case, the determination in S955 is NO. As will be described later, even in non-reserved seats, trimming based on face detection and trimming over a wider range can be performed. If the determination in S955 is YES, the process proceeds to S956; otherwise, the process proceeds to S963. It should be noted that it is possible to indicate to the spectators when purchasing tickets or near the seats that images cannot be purchased in the area.

In S956, the CPU 01 determines whether or not the number of seats n for which it is currently being determined whether or not to be trimmed is smaller than the number of seats m within the trimming range. That is, it is confirmed whether or not the determination of whether or not trimming is to be performed has been completed for all seats in the trimming range. If the determination in S956 is YES, the process proceeds to S957; otherwise, the process proceeds to S965.

In S957, the CPU 01 determines whether the seat n is a seat to be trimmed. Whether or not the seat is to be trimmed is determined depending on whether or not the spectator indicates the intention to purchase the image in FIG. That is, the determination in S955 is YES if the seat is included in the trimming group, and NO otherwise.

In S958, the CPU 01 selects a trimmed image, which is the original image to be trimmed from the image acquired in S952. As for the selection of the trimmed image, depending on the state of the audience in the trimming group of the currently targeted seat n, it is possible to select the one with the best expression or the one with greater movement compared to the images before and after. good. Alternatively, an image may be manually selected without changing the selected image for each trimming group, or the movement of the spectator within the trimming range may be quantified and the image with the largest movement may be selected.

In S959, the CPU01 executes trimming processing. The trimming process will be described later with reference to FIG. 10 .
In S960, the CPU01 sets seat n=n+1. If the seat n is included in the trimming group for which the trimming process has already been performed, the number of seats is set to n+1, and a seat that has not yet been determined in S957 is searched for.

The processing performed in S961 and S962 when the group trimming of the audience at seat n is not performed will be described. In this embodiment, area trimming is performed in association with seat numbers so that spectators can obtain images after the match. That is, unlike group trimming, the trimming range is determined so that the spectators who purchase at the same time enter and the other spectators do not enter, but trimming is performed with a predetermined number of people such as 30 or 50 people. This makes it possible to reduce the amount of time and data required for trimming, so that images can be quickly provided to spectators who are subject to group trimming, while images can be provided later to spectators who are not. I have to.

In S961, the CPU01 selects a trimmed image as in S958. In the case of area trimming, the trimmed image is not stored according to the audience at each seat, so the trimmed image is not selected according to the audience at seat n. In the case of area trimming, an image may be selected manually, or the movement of the spectators in the trimming range may be quantified and the image with the largest numerical value of movement may be selected. Alternatively, an image with a good facial expression or a large movement of the audience whose face data is prepared in advance may be selected. In this way, even for spectators who are not targeted for group trimming, by selecting images with good facial expressions or large movements of spectators who are likely to purchase images, they will purchase images in the future. It can meet the satisfaction of more audiences. Storing images with good facial expressions of each spectator increases the amount of data, which leads to an increase in cost, and takes time to retrieve the data. By giving priority to spectators who watch the game frequently and who are likely to purchase the images, the images can be provided at a lower cost and more quickly. For the spectators whose faces have been detected, the images of the target spectators may be collectively notified to the spectators after a predetermined number of games, such as 10 or 5 games, for example. may be notified of images and encouraged to purchase. In addition, by presenting the images taken in the previous game to the spectators when purchasing tickets for the next game, the spectators can grasp what kind of images will be taken and decide whether to purchase the images. Make it easier to make decisions.

In S962, the CPU 01 performs area trimming. As described above, area trimming is performed by trimming an image divided by a predetermined number of people. If the seat n is already included in the image that has been area-trimmed in the processing for another seat n, the data amount of the image is reduced without performing area trimming again.

In S963 and S964, the same processing as in S961 and S962 is executed. If it is a non-reserved seat that is not a trimming target seat, processing based on face detection may be performed, and if the trimming target seat is not a spectator within the group trimming range, area trimming may not be performed. In addition, a wide range of area trimming may be provided in the seats where some enthusiastic fans are concentrated or groups are sitting. For example, users wearing clothes of the same color may be set as the trimming range. As a result, groups wearing the uniform of the team they support can be included in one sheet.

In S965, the CPU 01 determines whether face data is present in the trimmed image. If there is face data, proceed to S966; otherwise, proceed to S967.
In S966, the CPU 01 associates the ID of each spectator with the image, and turns ON the image flag for the match being watched by the spectator. If the image flag is ON, it is possible to present to the spectators which games have images taken.

In S<b>967 , the CPU 01 uploads the trimmed image to the distribution unit 207 so that the audience targeted for group trimming can view the image. It should be noted that the trimmed image may be presented even to the spectators who are not the target of the group trimming. At this time, the spectators who are not subject to group trimming are watermarked with characters such as samples. Note that image data that has not been uploaded is deleted from the storage 204 or recorded with reduced image quality, thereby reducing the capacity of the image and leading to cost reduction. However, after the game, the images themselves selected in S958, S961, and S963 may be stored for a predetermined period of time, or the images may be notified to each spectator before deletion.

FIG. 10 is a flowchart showing an example of trimming processing in this embodiment. This processing is realized by developing a program recorded in ROM (non-volatile memory) 02 in RAM (system memory) 03 and executing it by CPU 01 .

The CPU 01 reads information on the number of people in the group, the seat number, and the seat arrangement previously acquired from the ticket purchase unit 206 (S1001).
FIG. 11 is a diagram showing an example of seating arrangements according to the number of people in a group according to this embodiment. FIG. 11A shows an example of the seating arrangement of a group of four people. In pattern (1), four people are lined up side by side, and in pattern (2), two people are lined up in front and back. The pattern is merely an example, and the combination of the shape of the pattern and the number of people does not limit the present invention. Similarly, FIG. 11(b) is an example of seating arrangement for a group of 5 persons, and FIG. 11(c) is an example of seating arrangement for a group of 6 persons.

FIG. 12 is a diagram showing the relationship of seats in the seat arrangement in this embodiment. Based on the lower left seat position within the group, the horizontal seat position is expressed as "number", and the vertical seat position is expressed as "column". The "column" number is incremented upwards. FIG. 12 shows a specific example of the seating arrangement in pattern (2) of FIG. 11(b). There are no users in the group in columns X+2 and Y, but they are necessary as data for trimming the rectangle, so they are defined as seats outside the group in the data structures of FIGS.

Returning to the description of FIG.
The CPU 01 acquires the trimming range and group outside seat information (S1002). Note that the trimming range may be calculated in S1001 without calculating the trimming range in advance.

When the group information acquired in S1002 includes information on seats outside the group (YES in S1003), the CPU 01 fills in the trimming range of the seat positions defined for seats outside the group with a single gray color (S1004). . If information on seats outside the group does not exist (NO in S1003), the process of S1004 is skipped.

In S1004, if the entire range of the trimming positions of the seats outside the group is painted, the trimming positions of the seats in the upper and lower groups may partially overlap. is desirable. This is a process for preventing spectators outside the group from appearing in the picture, but the filling method is not limited to this name. Also, if there is no particular problem with portrait rights, and there is no problem even if a person outside the group is photographed as the user's intention, there is a case where the processing of S1004 is not necessary.

The CPU 01 determines the trimming position according to the trimming position calculation method of 1303 to 1306 acquired in S1002 (S1005).
FIG. 15 is a diagram showing a calculation example of the trimming position in this embodiment. FIG. 15(a) is an example of a calculation method for an image taken almost from the front of the audience as shown in FIG. 4, and FIG. It is an example of a calculation method for a photographed image. In FIG. 15A, the upper left vertex of the upper left seat and the lower right vertex of the lower right seat are simply used as the vertices of the overall trimming position. In FIG. 15(b), since the upper and lower rows are slightly misaligned,
Upper left vertex X coordinate = X coordinate of upper left vertex of lower left seat Y coordinate = Y coordinate of upper left vertex of upper left seat Lower right vertex X coordinate = X coordinate of lower right vertex of upper right seat Y coordinate = Lower right vertex of lower right seat A Y coordinate is defined, and the coordinate positions of the upper left vertex and lower right vertex are obtained using this calculation method.

Returning to the description of FIG.
In accordance with the trimming position determined in S1005, the CPU 01 generates a trimmed image cut out from the entire image taken by the camera at the trimming position according to the corresponding number of people and seat arrangement, and stores it in the storage 205 together with the shooting date and seat number information. (S1006).

In the above-described embodiment, the system may be operated as follows so that the audience can acquire images more easily.
・The viewing request to the delivery server is made to read the QR code of the ticket.
・Although group information is acquired in advance, it may be acquired each time processing is performed. In this case, the ticket purchase system also needs to recreate the group information all the time, and each time it is acquired from the trimming unit 202, the processing of the system as a whole increases. However, for example, in the case of baseball, the proportion of same-day ticket sales is high, and this is effective when a large amount of group information is created after the start of a game.

Next, a case where the spectator did not indicate the intention to purchase the image in advance, but intends to purchase the image after the game is over will be described with reference to FIGS. 16 and 17. FIG.

FIG. 16 is a diagram showing another example of the system configuration of the image providing system according to this embodiment. The image processing apparatus 201 has a photographing instruction section 101 , cameras 102 to 105 , an image transfer reception section 201 b , a selection/upload section 203 and a storage 204 . In FIG. 16, the processing units 101, 201b, 203, and 204 are shown in one image processing apparatus 201, but they may be physically separate processing units, and the configuration of the processing units is the same as in the present invention. It is not intended to limit the invention. Similarly, the distribution unit 207 and the trimming unit 202 may be physically separate processing devices.
The photographing processing unit 101, the cameras 102 to 105, the camera image transfer receiving unit 201b, and the ticket purchasing unit 206 are the same as those described in FIG. 2, and therefore are omitted.

Triggered by the fact that the captured image data is stored in the storage 204, the selection/upload unit 203 uploads the captured image data to the distribution unit 207 together with the date and time information of the event and the trimming position information for each seat. The captured image data here is untrimmed, high-resolution data, so if the number of shots increases due to interval shooting, etc., or if the number of cameras increases, a large amount of data will be sent to the distribution unit. 207 will be uploaded. If you later try to group trim, the system will have to hold more data.

Although the trimming position information for each seat is uploaded from the image processing apparatus 201 to the distribution unit 207 here, the distribution unit 207 and the trimming unit 202 may have the information. However, since the trimming position information is only position information for the images captured by the cameras 102 to 105, it needs to be updated every time the mounting positions or the angles of view of the cameras 102 to 105 on the image processing apparatus 201 side are changed. necessary. Therefore, the system of the image processing apparatus 201, the distribution unit 207, and the trimming unit 202 needs to work together more.

The distribution unit 207 transmits the thumbnail position information and the seat number acquired from the selection/upload unit to the trimming unit 202 based on the event date and seat number input by the user, instructs trimming processing, and trims the acquired trimming. Present the finished image to the user. As for input by the user, the user may manually input by looking at the ticket as in FIG. If the ticket information is unknown, face detection may be used. The input method is not limited to the method described above. In addition, presentation to the user may be in the form of a smartphone application or a Web application that can be accessed using a browser, and the presentation method is not limited to the present invention.

The processing itself of the trimming unit 202 is the same as in FIG. However, the trimmed image is generated every time the user wishes to purchase, and the trimming time is included in the time it takes for the user to obtain the trimmed image. I can't. In addition, in order to perform image processing quickly, an environment is required in which image processing can be performed at a higher speed.

Next, referring to FIG. 17, the case where image data is stored in the storage 204 will be described. Unlike FIG. 16, in the process of FIG. 17, a large amount of image data is not transmitted to the distribution unit 207, but after receiving a trigger to purchase an image from the user, the image processing apparatus 201 receives the image data shot by the target camera. request and upload the image. Therefore, it takes longer than in FIG. 16 to acquire the image, and it takes even longer for the user to acquire the trimmed image data.
FIG. 17 has the same configuration as FIG.

In this embodiment, it is assumed that the user has purchased a ticket, and the process starts from the point where an image purchase instruction is sent to the distribution unit 207 (step 1). The distribution unit 207 requests the image of the target camera from the image processing device 201 (step 2), and the image is requested from the storage 204 within the image processing device 201 (step 3). After that, the selection/upload section 203 transmits the image data to the distribution section 207 (step 4). At this time, since the image data includes date information, trimming position information for each seat, and image data before trimming, the amount of data increases. When the distribution unit 207 issues a trimming instruction to the trimming unit 202 (step 5), the trimming unit 202 performs trimming, and the trimmed image data is distributed to the distribution unit 207 (step 6). After that, the trimmed image is distributed to the spectators who purchased the image from the distribution unit (step 7).

Thus, with the method of FIG. 17, even if the audience does not show an intention to purchase the image in advance, it is possible to provide the audience with the trimmed image targeted for the trimming group. However, there are many exchanges within the system and within the device, and there is a possibility that it will take longer to provide the image than the spectator who intends to purchase the image in advance. In addition, when providing images to spectators, the seat information is also linked and provided to the spectators, so that when the spectators upload the images to SNS, the images can be viewed in any position according to the seat position of the person viewing the image. can recognize whether is taken. In addition, by performing image processing related to brightness according to the position of the seat and providing appropriate images for dark and bright areas, it is possible to capture a wide range of spectators within the same angle of view. can provide better images. If the brightness changes more than a predetermined amount within the same angle of view, a RAW image may be acquired to facilitate image processing later.

Next, a series of photographing processes according to this embodiment will be described with reference to FIG. 18 . The series of photographing processes are processes for changing the frequency of photographing according to the vacant seat status of the audience seats. This processing is realized by developing a program recorded in ROM (non-volatile memory) 02 in RAM (system memory) 03 and executing it by CPU 01 . This process should be done before the start of the match, when the spectator information has been collected. let it start. Alternatively, it may start immediately after the start of the match.

In S1801, the CPU 01 acquires an image when the shooting range of each camera is empty. An image taken in advance may be obtained when the shooting range is empty, or may be taken at each match.
In S1802, the CPU 01 acquires spectator information who has an image purchase intention in advance. A spectator who intends to purchase an image is a spectator who indicates an intention to purchase a trimmed image in the ticket purchase process shown in FIG.

In S1803, the CPU 01 acquires information about the arrangement of the cameras, and acquires information on seats within the shooting range of the cameras. The seat type of the seat is also acquired at this time.
In S1804, the CPU 01 calculates the shooting target ratio indicating how many spectators are shooting targets from the information acquired in S1803 and the audience information acquired in S1802. The rate of filming targets is the number of spectators who intend to purchase filming divided by the number of seats. In S1804, the shooting target ratio of each camera is calculated.

In S1805, the CPU 01 acquires the ratio of the imaging target of the camera n=1 calculated in S1804.
In S1806, the CPU 01 determines whether or not there is an audience member who intends to purchase the image captured by the camera n, that is, the image captured by the camera n. If it is determined that there is an object to be photographed by camera n, the process advances to S1807; otherwise, the process advances to S1809.

In S1807, the CPU 01 determines an imaging interval according to the calculated imaging target ratio. For example, if 50% or more of the spectators intend to purchase images, the shooting interval is set to T=5 seconds, and if 30% or more, the shooting interval is set to T=10 seconds. As the number of shots increases, the number of images stored in the storage 204 increases, and there is a possibility that the speed of providing images to the audience will slow down. Therefore, the number of images to be stored in the storage 204, that is, the number of images to be photographed is determined with respect to the number of images that may be provided to the audience so as not to reduce the image providing speed. can do.
In S1808, the CPU 01 sets the shooting interval T so that the camera n performs shooting at the set shooting interval.

In S1809, the CPU 01 changes the shooting settings of the camera n. If there is no object to be photographed, the camera n may be used not for photographing spectators, but for example, as a camera for photographing the scene of a game, or for photographing fireworks or a scoreboard. Alternatively, shooting may not be performed. As a result, the number of images stored in the storage 204 can be reduced.

In S1810, the CPU 01 determines whether the settings in S1808 or S1809 have been made for all cameras. If it is determined that shooting has been set for all cameras, the process advances to S1811; otherwise, the ratio of shooting targets for camera n=n+1 is acquired, and the process advances to S1806.
In S1811, the CPU 01 executes a series of shooting processes during the game. A series of photographing processes during a match will be described with reference to FIG. 19 .

Next, a series of photographing processes during a match will be described with reference to FIG. 19 . The flowchart shown in FIG. 19 starts when the process proceeds to S1811 in FIG. The processing shown in FIG. 19 may be performed after the shooting interval for each camera n is set in S1808 (S1809) even if it is not during the game. FIG. 19 shows processing for updating the photographing interval set in FIG. 18 immediately before. Before the game, we know the information at the time of ticket purchase, but after the game starts, we know how many spectators are actually seated. This processing is realized by developing a program recorded in ROM (non-volatile memory) 02 in RAM (system memory) 03 and executing it by CPU 01 .

In S1901, the CPU 01 acquires camera arrangement information, shooting range information, and information on spectators who intend to purchase an image for the camera n=1.
In S1902, the CPU 01 acquires the image of the camera n captured immediately before.
In S1903, the CPU 01 compares the image of empty seats acquired in S1801 with the image acquired in S1902, and determines the area where the audience is seated.
In S1904, the CPU 01 calculates the proportion of the human area.

In S1905, the CPU 01 changes the shooting interval T according to the increase in the number of people. For example, according to the ticket purchase information, 30% of the seats were scheduled to be filled. Change the interval T from 10 seconds to 7 seconds. There is a high possibility that the spectators who purchased tickets before and after the match did not perform the processing regarding the intention to purchase the images described with reference to FIG. 7 . Therefore, the photographing interval T set in S1808 is changed according to the rate of increase or decrease in the number of people. In S1905, the photographing interval T may be changed according to the ratio of the area of the audience calculated in S1904. The shooting interval T may be set based on the ratio.

In S1906, the CPU 01 determines whether or not the settings in S1905 have been made for all cameras. If it is determined that the processing of S1905 has been performed for all cameras, the process advances to S1907. If not, the camera arrangement information, shooting range information, and information on spectators who intend to purchase images are acquired for camera n=n+1. and proceed to S1902.

In S1907, the CPU 01 determines whether or not a predetermined time has passed. The predetermined time is, for example, 20 minutes or 30 minutes, and is an interval for updating the imaging interval T in S1905. If it is determined that the predetermined time has passed, the process advances to S1901; otherwise, the process advances to S1908.
In S1908, the CPU 01 determines whether or not to end the processing of FIG. If it is determined to end the processing in FIG. 19, the processing ends, and if not, the process advances to S1907. The processing in FIG. 19 ends when the shooting ends.

According to the above-described embodiment, the photographing interval T is changed based on the information of vacant seats, so that the amount of image data can be reduced, and when there are many spectators, images can be provided without missing a photographing opportunity. be able to. Since the shooting opportunities differ depending on each group and the audience, the shooting opportunities increase as the number of the audience filmed in one shooting increases. Therefore, by determining the photographing interval T according to the number of spectators, when the number of spectators increases, the possibility of photographing each spectator without missing a photographing opportunity is improved. Also, when the number of spectators decreases, the amount of data can be reduced.

20 and 21, a modified example of the series of photographing processes during a game explained with reference to FIG. 19 will be explained. 20 and 21 are started when proceeding to S1811 shown in FIG. 18, similarly to the flowchart shown in FIG. This processing is realized by developing a program recorded in ROM (non-volatile memory) 02 in RAM (system memory) 03 and executing it by CPU 01 .

FIG. 20 illustrates a modification in which the photographing interval is changed based on face detection information.
In S2001, the CPU 01 detects the face of the audience from the image captured by the camera n. In the face detection of S2001, the face of the spectator who has indicated the purchase intention of the image in advance is detected.
In S2002, the CPU 01 counts the number of people whose faces have been detected.
In S2003, the CPU 01 calculates the ratio of the number of spectators who indicated their intention to purchase the image in advance and the number of face-detected people counted in S2002. As a result, it is possible to know how many spectators who have indicated their intention to purchase the image in advance are actually sitting among the spectators in the photographing range of the camera n.

In S2004, the CPU 01 designates a specific subject representing a subject such as team colors, flags, and goods. The specific subject may be specified by the spectator who has indicated the purchase intention, or may be specified by the person who provides the image.
In S2005, CUP01 detects a specific subject from the image acquired in S2001.

In S2006, the CPU 01 changes the shooting interval T according to the ratio of the number of faces detected in S2003, or changes the shooting interval T according to the number of specific subjects detected in S2005. Whether the photographing interval T is to be changed according to the number of people for face detection or the number of specific subjects may be selected by the spectator who has indicated the purchase intention, or the image provider side. You can also set it with For example, if the number of face-detected people is 50%, the photographing interval T set in S1808 of FIG. 18 may be doubled. In addition, for example, when there are many spectators wearing team-colored uniforms, there is a high possibility that the spectators will be very excited. can.

In S2007, the CPU 01 changes the coordinates for focus and the zoom amount based on the result of face detection in S2001. This makes it possible to provide a more focused image to spectators who are willing to purchase the image based on the position of the detected face.
According to the embodiments described above, the photographing interval T is changed according to the detected face, so the amount of images stored in the storage 204 can be reduced. Note that the processing in FIG. 20 is performed for each camera.

Next, in FIG. 21, the photographing conditions are changed based on the vacant seat rate so that photographing can be performed under photographing conditions suitable for a larger number of spectators. In outdoor sports such as baseball and soccer, the brightness of the seats varies greatly depending on how much sunlight enters and the position of the roof. At this time, for example, if the exposure is adjusted to a bright place, it may not be appropriate for the audience in the dark area. In such a case, the processing shown in FIG. 21 is for setting the ISO sensitivity, aperture value, and shutter speed related to exposure to settings suitable for a greater number of spectators.

In S2101, the CPU 01 acquires illuminance information of predetermined N sections from the acquired image of the camera n. The N sections are sections composed of adjacent seats, such as four or six, and include the entire imaging range of the camera n. The image acquired by the camera n was captured at the timing of S2101, but may be captured before S2101.

In S2102, the CPU 01 sets the determination section n=1. The determination section indicates a section in which determination is made to divide into illuminance levels 1 to 4 based on the illuminance information acquired in S2102, and illuminance 1, 2, 3, and 4 gradually become darker in that order. The illuminance level is obtained by dividing the illuminance that can be at a predetermined seat into levels. The number of illuminance levels may not be four as described in this embodiment, and may be two or three if the illuminance does not change significantly. Also, if the shooting settings related to exposure do not change even if the illuminance changes, the same illuminance level may be given a range.

In S2103, the CPU 01 determines whether or not the determination section n is a section with an illuminance level of 1 based on the illuminance information of the determination section n. If it is determined that the section is at illuminance level 1, the process proceeds to S2104; otherwise, the process proceeds to S2105.
In S2104, the CPU 01 registers the determination block n in the illuminance level 1 list.

In S2105, the CPU 01 determines whether or not the determination section n is a section with an illuminance level of 2 based on the illuminance information of the determination section n. If it is determined that the section is at illuminance level 2, the process proceeds to S2106; otherwise, the process proceeds to S2107.
In S2106, the CPU 01 registers the determination section n in the illuminance level 2 list.

In S2107, the CPU 01 determines whether or not the determination section n is a section with an illuminance level of 3 based on the illuminance information of the determination section n. If it is determined that the section is at illuminance level 3, the process proceeds to S2108; otherwise, the process proceeds to S2109.
In S2108, the CPU 01 registers the determination section n in the illuminance level 3 list.
In S2109, the CPU 01 registers the determination section n in the illuminance level 4 list.

In S2110, the CPU 01 determines whether or not the determination for all determination partitions has been completed. If YES in S2110, the process proceeds to S2112; otherwise, the process proceeds to S2111.
In S2111, the CPU 01 sets the determination section to n=n+1 and proceeds to S2103.
In S2112, the CPU 01 counts the number of people whose faces are detected in the sections with illuminance levels 1 and 2. FIG. That is, the number of faces of spectators in the area of illuminance level 1 and the number of faces of spectators in the area of illuminance level 2 are counted.

In S<b>2113 , the CPU 01 determines whether or not there are more people whose faces have been detected in the section with the illuminance level 1 than in the section with the illuminance level 2 . If it is determined that there are more people whose faces have been detected in the section of illuminance level 1 than in the section of illuminance level 2, the process proceeds to S2114; otherwise, the process proceeds to S2115.
In S<b>2114 , the CPU 01 sets shooting setting 1 as the shooting setting related to the exposure that matches the illuminance 1 .
In S<b>2115 , the CPU 01 sets shooting setting 1 as the shooting setting related to the exposure that matches the illuminance 2 .

In S2116, the CPU 01 compares the vacant seat images of sections with illuminance levels 3 and 4 with the image obtained by the camera n to determine the area where the audience is seated. The acquired image of camera n is the one captured by camera n in S2116, but may be the one captured before S2116.
In S<b>2117 , the CPU 01 calculates the ratio of areas where people are present in the sections with illumination levels 3 and 4 . At illuminance levels 3 and 4, since the illuminance is low, the accuracy of human face detection may be lower than at illuminance levels 1 and 2. Therefore, the number of people sitting is calculated by comparing images instead of face detection. On the other hand, for illumination levels 1 and 2, face detection is used to count people more accurately.

In S2118, the CPU 01 determines whether or not the section with the illuminance level 3 has more people than the section with the illuminance level 4. If it is determined that there are more people in the section with illuminance level 3 than in the section with illuminance level 4, the process proceeds to S2119; otherwise, the process proceeds to S2120.
In S<b>2119 , the CPU 01 sets the shooting setting 2 as the shooting setting related to the exposure that matches the illuminance 3 .
In S<b>2120 , the CPU 01 sets the shooting setting related to the exposure adjusted to the illuminance 4 to the shooting setting 2 .

Next, in steps S2121 to S2129, processing is performed to set the photographing interval T according to the number of people present at each illuminance level.
In S2121, the CPU 01 calculates the ratio α of the number of people by illuminance acquired in S2112 and S2116=(the number of people at illuminance levels 1 and 2)/(the number of people at illuminance levels 3 and 4). If it is determined that the value of α is 1.5 or more, that is, there are 1.5 times more people in the bright area than in the dark area in the range captured by camera n, the process proceeds to S2122. If 1.0≤α<1.5, proceed to S2124; if 0.7≤α<1.0, proceed to S2126; if α<0.7, proceed to S2128.

In S2123, the CPU 01 sets shooting with shooting setting 1 as T=t1 and shooting with shooting setting 2 as T=t2 (>t1). For example, t1 is 5 seconds and t2 is 10 seconds.
In S2125, the CPU 01 sets shooting with shooting setting 1 as T=t1 and shooting with shooting setting 2 as T=t3 (>t2). For example, t1 is 5 seconds and t3 is 15 seconds.

In S2127, the CPU 01 sets shooting with shooting setting 1 as T=t4 and shooting with shooting setting 2 as T=t5 (<t4). For example, t4 is 10 seconds and t5 is 5 seconds.
In S2129, the CPU 01 sets shooting with shooting setting 1 as T=t6 (>t4) and shooting with shooting setting 2 as T=t5. For example, t6 is 15 seconds and t5 is 5 seconds.

In this way, when there are many people in a bright area, shooting with an exposure setting that matches the illuminance of the bright area is performed more frequently than shooting with an exposure setting that matches the illuminance of the dark area. make it Also, when there are many people in dark areas, shooting with exposure settings that match the illuminance of dark areas will be performed more frequently than shooting with exposure settings that match the illuminance of bright areas. do.

At S2130, the CPU 01 determines whether or not to end the processing of FIG. If it is determined to end the processing in FIG. 21, the processing in FIG. 21 is ended; otherwise, the process advances to S2101.

In the above-described embodiments, the frequency of photographing with photographing settings that match the illuminance level is performed according to the number of spectators. can be increased. Also, in areas where there are few spectators, the photographing interval T is increased to reduce the frequency of photographing, so that the amount of image data can be reduced.

<Other embodiments>
The present invention supplies a program that implements one or more functions of the above-described embodiments to a system or apparatus via a network or a storage medium, and one or more processors in the computer of the system or apparatus reads and executes the program. It can also be realized by processing to It can also be implemented by a circuit (for example, ASIC) that implements one or more functions.

All of the above-described embodiments merely show specific examples for carrying out the present invention, and the technical scope of the present invention should not be construed to be limited by these. That is, the present invention can be embodied in various forms without departing from its technical concept or main features.

Note that the various controls described above that are performed by the image processing apparatus 201 may be performed by one piece of hardware, or may be performed by a plurality of pieces of hardware (for example, a plurality of processors or circuits). Overall control may be performed.
Moreover, although the present invention has been described in detail based on its preferred embodiments, the present invention is not limited to these specific embodiments, and various forms within the scope of the gist of the present invention can be applied to the present invention. included. Furthermore, each embodiment described above merely shows one embodiment of the present invention, and it is also possible to combine each embodiment as appropriate.

Further, in the above-described embodiment, the case where the present invention is applied to the image processing apparatus 201 has been described as an example, but this is not limited to this example, and an electronic device or a plurality of electronic devices capable of controlling images It is applicable if it is a system consisting of That is, the present invention can be applied to personal computers, PDAs, mobile phone terminals, portable image viewers, printers equipped with displays, digital photo frames, music players, game machines, electronic book readers, and the like. It goes without saying that it is also applicable to perform control in conjunction with AI (artificial intelligence).

The present invention is also realized by executing the following processing. That is, the software (program) that realizes the functions of the above-described embodiments is supplied to a system or device via a network or various storage media, and the computer (or CPU, MPU, etc.) of the system or device reads the program code. This is the process to be executed. In this case, the program and the storage medium storing the program constitute the present invention.

101: photographing instruction unit 102 to 105: camera 201: image processing device 201a: PC (personal computer) 202: trimming unit 203: selection/upload unit 204, 205: storage 206: ticket purchase unit 207: distribution unit

Claims (6)

Acquisition means for acquiring information about a seat to be photographed among a plurality of seats;
an instruction means for instructing an image capturing device to capture an image including the plurality of seats in a view angle range;
providing means for providing the image;
An image providing system, comprising: control means for controlling a photographing interval at which images are photographed by said imaging device based on the information obtained by said obtaining means. 2. The image according to claim 1, wherein said control means controls said photographing interval based on a ratio of said photographing object to said plurality of seats, which is calculated using the information obtained by said obtaining means. offer system. 3. The image providing system according to claim 1, wherein said providing means provides an image trimmed according to said object to be photographed. Acquisition means for acquiring information about a seat to be photographed among a plurality of seats;
an instruction means for instructing an image capturing device to capture an image including the plurality of seats in a view angle range;
providing means for providing the image;
and control means for controlling a shooting interval at which the imaging device takes images based on the information acquired by the acquisition means. an acquisition step of acquiring information about a seat to be photographed among the plurality of seats;
an instruction step of instructing an image capturing device to capture an image including the plurality of seats in a view angle range;
a providing step of providing the image;
A control method for an image providing device, comprising: a control step of controlling a photographing interval for allowing the image pickup device to photograph images based on the information obtained in the obtaining step. an acquisition step of acquiring information about a seat to be photographed among the plurality of seats;
an instruction step of instructing an image capturing device to capture an image including the plurality of seats in a view angle range;
a providing step of providing the image;
A program for causing a computer to execute a control step of controlling a photographing interval at which the imaging device is caused to photograph images based on the information obtained in the obtaining step.

Images