WO2022168402A1 - Information processing device, information processing method, and computer-readable medium - Google Patents

Information processing device, information processing method, and computer-readable medium Download PDF

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Publication number
WO2022168402A1
WO2022168402A1 PCT/JP2021/042464 JP2021042464W WO2022168402A1 WO 2022168402 A1 WO2022168402 A1 WO 2022168402A1 JP 2021042464 W JP2021042464 W JP 2021042464W WO 2022168402 A1 WO2022168402 A1 WO 2022168402A1
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WIPO (PCT)
Prior art keywords
congestion
information processing
image data
vehicle
degree
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PCT/JP2021/042464
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French (fr)
Japanese (ja)
Inventor
大地 佐藤
篤史 北裏
康晃 向井
信 武内
ショウソ チョウ
大輔 川崎
薫 山根
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日本電気株式会社
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Publication date
Application filed by 日本電気株式会社 filed Critical 日本電気株式会社
Priority to JP2022579348A priority Critical patent/JP7521619B2/en
Publication of WO2022168402A1 publication Critical patent/WO2022168402A1/en

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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B61—RAILWAYS
    • B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
    • B61L25/00—Recording or indicating positions or identities of vehicles or trains or setting of track apparatus
    • B61L25/02—Indicating or recording positions or identities of vehicles or trains
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis

Definitions

  • the present invention relates to an information processing device, an information processing method, and a computer-readable medium.
  • a passenger number detection device is installed in each vehicle of a train, detects the number of passengers on the vehicle when the train departs, and detects the number of passengers. Send the data to the server device.
  • the cameras that make up the vehicle congestion status notification system are installed on the ceiling, which is the upper part of the interior of the vehicle, with the optical axis facing downward. to cover the detection of
  • the train congestion level notification system consists of a camera that captures the area near the door inside the train as train equipment, a data processing unit that calculates the degree of congestion within the train based on the video data acquired by the camera, and output from the data processing unit. Congestion degree information to be used.
  • This system also has a transmitting unit for transmitting congestion state data including train identification information for identifying a train and photographing position information indicating a photographing position in the train by a camera, and stores the congestion state in an information center. , to be displayed on the station display.
  • the present disclosure has been made in view of such problems, and aims to provide an information processing device or the like that accurately determines the degree of congestion with a simple configuration.
  • An information processing apparatus has an image data acquisition unit, an area setting unit, a counting unit, a congestion degree determination unit, and an output unit.
  • the image data acquisition unit acquires image data generated by a camera that captures the interior of the vehicle.
  • the region setting unit divides an image related to image data into a plurality of regions.
  • the counting unit counts the number of persons present in a target area among the plurality of areas.
  • the congestion level determination unit determines the vehicle congestion level based on the number of people.
  • the output unit outputs information about the degree of congestion.
  • a computer executes the following method.
  • the computer acquires image data generated by a camera that captures the interior of the vehicle.
  • a computer divides an image corresponding to image data into a plurality of regions.
  • the computer counts the number of persons present in a target area of the plurality of areas.
  • a computer determines the degree of congestion of the vehicle based on the number of people.
  • the computer outputs information about the degree of congestion.
  • a program causes a computer to execute the following steps.
  • the computer acquires image data generated by a camera that captures the interior of the vehicle.
  • a computer divides an image corresponding to image data into a plurality of regions.
  • the computer counts the number of persons present in a target area of the plurality of areas.
  • a computer determines the degree of congestion of the vehicle based on the number of people.
  • the computer outputs information about the degree of congestion.
  • FIG. 1 is a block diagram of an information processing device according to a first embodiment;
  • FIG. 4 is a flowchart of an information processing method according to the first embodiment;
  • 2 is a block diagram of an information processing system according to a second embodiment;
  • FIG. 2 is a block diagram of an imaging device according to a second embodiment;
  • FIG. 2 is a block diagram of an information providing device according to a second embodiment;
  • FIG. FIG. 2 is a diagram showing an example of a situation inside a vehicle;
  • FIG. FIG. 10 is a diagram showing an example of conditions for determining the degree of congestion according to the second embodiment;
  • FIG. 11 is a first diagram showing an example of an image according to the second embodiment;
  • FIG. 12 is a second diagram showing an example of an image according to the second embodiment;
  • FIG. It is a block diagram which illustrates the hardware constitutions of a computer.
  • FIG. 1 is a block diagram of an information processing device 10 according to the first embodiment.
  • the information processing apparatus 10 shown in FIG. 1 determines and outputs the degree of congestion of a predetermined transportation facility from an image captured by a camera provided in the transportation facility.
  • a predetermined means of transportation in the present disclosure is, for example, a means of transportation boarded by a plurality of persons, such as a train, a tram, a trolley, or a bus.
  • the information processing apparatus 10 shown in FIG. 1 has an image data acquisition unit 111, an area setting unit 112, a counting unit 113, a congestion degree determination unit 114, and an output unit 115 as main components.
  • the image data acquisition unit 111 acquires image data generated by a camera that captures the interior of the vehicle.
  • the image data acquisition unit 111 may acquire image data for each preset period.
  • the preset period is, for example, 2 minutes, 5 minutes, 10 minutes, or the like.
  • the image data acquisition unit 111 supplies the received image data to the area setting unit 112 .
  • the image data received by the image data acquisition unit 111 at one time may be one frame of still image data, or may be several consecutive frames of moving image data.
  • the moving image data is, for example, image data of 30 frames per second or 15 frames per second.
  • the moving image data may conform to standards such as MPEG (Moving Picture Experts Group), motion JPEG (Joint Photographic Experts Group), or AVI (Audio Video Interleave).
  • the area setting unit 112 divides the image corresponding to the image data received from the image data acquisition unit 111 into a plurality of areas.
  • the area for dividing the image by the area setting unit 112 may be set in advance, or may be changed according to a predetermined condition.
  • the predetermined condition may be set by, for example, an operation performed by an administrator of the information processing device 10, or may be changed according to the time of day, the running state of the vehicle, or the like.
  • the division performed by the region setting unit 112 may be, for example, separating the image data into a plurality of pieces of image data to be divided, or generating information indicating the boundaries of the regions to be divided. After dividing the image, the area setting unit 112 supplies image data related to the divided image to the counting unit 113 .
  • the counting unit 113 receives image data related to the divided image from the region setting unit 112, and counts the number of persons existing in the target region among the plurality of divided regions.
  • the target area refers to an area that is set in advance and that is to be processed when the information processing apparatus 10 determines the degree of congestion. After counting the number of persons existing in the target area, the counting unit 113 supplies information about the counted number to the congestion degree determination unit 114 .
  • the congestion degree determination unit 114 receives information about the number of people counted by the counting unit 113, and determines the congestion degree of vehicles in the target area from the received information.
  • the relationship between the number of people in the target area and the degree of congestion is set in advance. However, the congestion level determination unit 114 can also consider other factors in addition to the number of people in the target area when determining the congestion level. Other elements include, for example, information about the positions of people and information about distances between people.
  • the congestion degree determination unit 114 After determining the congestion degree, the congestion degree determination unit 114 generates information about the determined congestion degree, and supplies the generated information to the output unit 115 .
  • Information about the determined degree of congestion includes identification information of the determined vehicle in addition to the degree of congestion.
  • the output unit 115 When the output unit 115 receives information about the degree of congestion from the congestion degree determination unit 114, the output unit 115 outputs the received information to a predetermined output destination.
  • the predetermined output destination is, for example, the user who uses the vehicle for which the above determination is made, or the operation manager who manages the operation of the vehicle.
  • FIG. 2 is a flow chart showing the information management method according to the first embodiment.
  • the flowchart shown in FIG. 2 is started by, for example, activating the information processing apparatus 10 .
  • the image data acquisition unit 111 acquires image data generated by a camera that captures the interior of the vehicle (step S11).
  • the area setting unit 112 divides the image related to the image data into a plurality of areas (step S12).
  • the counting unit 113 counts the number of persons existing in the target area among the plurality of areas (step S13).
  • the congestion degree determination unit 114 determines the congestion degree of the vehicle based on the number of people (step S14).
  • the output unit 115 outputs information about the degree of congestion (step S15), and ends the series of processes. Note that the information processing method described above may be executed each time the information processing apparatus 10 acquires image data. Further, the information processing method described above may be executed for each preset period.
  • the information processing apparatus 10 has a processor and a storage device (not shown).
  • the storage device included in the information processing device 10 includes, for example, a storage device including non-volatile memory such as flash memory and SSD (Solid State Drive).
  • the storage device of the information processing apparatus 10 stores a computer program (hereinafter also simply referred to as a program) for executing the image processing method described above.
  • the processor also loads a computer program from a storage device into a buffer memory such as a DRAM (Dynamic Random Access Memory) and executes the program.
  • a buffer memory such as a DRAM (Dynamic Random Access Memory)
  • Each configuration of the information processing device 10 may be realized by dedicated hardware. Also, part or all of each component may be implemented by a general-purpose or dedicated circuit, processor, etc., or a combination thereof. These may be composed of a single chip, or may be composed of multiple chips connected via a bus. A part or all of each component of each device may be implemented by a combination of the above-described circuits and the like and programs.
  • a processor a CPU (Central Processing Unit), GPU (Graphics Processing Unit), FPGA (field-programmable gate array), or the like can be used. It should be noted that the configuration descriptions described herein may also be applied to other devices or systems described below in the present disclosure.
  • each component of the information processing device 10 when part or all of each component of the information processing device 10 is realized by a plurality of information processing devices, circuits, etc., the plurality of information processing devices, circuits, etc. may be centrally arranged, They may be distributed.
  • the information processing device, circuits, and the like may be implemented as a form in which each is connected via a communication network, such as a client-server system, a cloud computing system, or the like.
  • the functions of the information processing device 10 may be provided in a SaaS (Software as a Service) format.
  • Embodiment 1 has been described above. According to Embodiment 1, it is possible to provide an information processing apparatus or the like that accurately determines the degree of congestion with a simple configuration.
  • FIG. 3 is a block diagram of the information processing system 1 according to the second embodiment.
  • the information processing system 1 shown in FIG. 3 includes an information processing device 10 and an imaging device 310 as main components.
  • the information processing system 1 may also include an information providing device 400 .
  • the information processing system 1 may further include a user terminal 900 .
  • the information processing device 10 in this embodiment is communicably connected to the imaging device 310 via the network N1.
  • the information processing device 10 acquires image data related to an image of the interior of the vehicle 300 captured from the image capturing device 310 .
  • the information processing device 10 determines the degree of congestion from the image data acquired from the photographing device 310 .
  • the information processing device 10 is also communicably connected to the information providing device 400 via the network N1.
  • the information processing device 10 outputs information regarding the degree of congestion of the vehicles 300 to the information providing device 400 .
  • the image data acquisition unit 111 acquires image data related to an image captured by a photographing device 310 installed on the top of the vehicle 300 so as to look down on a person. Further, as described above, the photographing device 310 is installed near the entrance/exit of the vehicle 300 . Therefore, the image data acquisition unit 111 acquires image data related to an image including the entrance/exit of the vehicle 300 .
  • the area setting unit 112 sets an image including the vicinity of the entrance/exit of the vehicle 300 as the target area.
  • the counting unit 113 in the present embodiment recognizes a person's head from the image data acquired from the imaging device 310 . That is, the counting unit 113 counts the number of recognized heads in the target area in the acquired image data. As means for recognizing the head, the counting unit 113 may use, for example, convolution processing of image data by a CNN (Convolutional Neural Network). The counting unit 113 may recognize the head using a learning device that has learned sample images of the head. By using machine learning, the counting unit 113 can improve the recognition accuracy of the head.
  • CNN Convolutional Neural Network
  • the photographing device 310 is installed on the ceiling of the vehicle 300 and photographs a person inside the vehicle 300 from above the vehicle 300 from above.
  • the photographing device 310 is preferably installed on the ceiling near the doorway of the vehicle 300 .
  • the information processing system 1 can suitably determine the degree of congestion of the vehicle 300 .
  • the photographing device 310 photographs the scenery inside the vehicle 300 and generates image data.
  • the imaging device 310 supplies the generated image data to the information processing device 10 via the network N1.
  • the number of the imaging device 310 installed in the vehicle 300 may be one, or may be plural.
  • the information providing device 400 receives information regarding the congestion degree of the vehicle 300 from the information processing device 10 via the network N1.
  • the information providing device 400 is also communicably connected to the user terminal 900 via the network N1.
  • the information providing device 400 provides the user terminal 900 with information on the congestion degree of the vehicle 300 .
  • User terminal 900 is, for example, a smart phone.
  • the user terminal 900 receives the congestion degree of the vehicle 300 from the information providing device 400 via the network N1. Thereby, the user U can grasp the congestion degree of the vehicle 300 by operating the user terminal 900 which is his/her own terminal.
  • the user terminal 900 may be a tablet terminal, a personal computer, or the like.
  • FIG. 4 is a block diagram of the imaging device 310 according to the second embodiment.
  • the photographing device 310 has a camera 311, a communication section 312, a control section 313, and a storage section 320 as main components.
  • the camera 311 captures the scenery inside the vehicle 300 and generates image data.
  • the camera 311 includes an objective lens, an imaging device, a photoelectric conversion section, an image generation section, and the like.
  • the communication unit 312 is an interface for communicably connecting the imaging device 310 to the network N1.
  • the communication unit 312 supplies image data and the like generated by the camera 311 to the information processing apparatus 10 via the network N1.
  • the communication unit 312 may also receive a signal regarding an image data request from the information processing apparatus 10 via the network N1.
  • the control unit 313 is an arithmetic device such as a CPU or MPU, for example, and controls each component of the imaging device 310 . Also, the control unit 313 executes a program 321 stored in the storage unit 320 . More specifically, for example, the control unit 313 executes processing for providing the information processing apparatus 10 with image data generated by the camera 311 and unique identification data at predetermined intervals according to a preset program.
  • the storage unit 320 is a storage device including nonvolatile memory.
  • the storage unit 320 stores, for example, a program 321 that controls the imaging device 310 .
  • the storage unit 320 also stores, for example, unique identification data set in the photographing device 310 .
  • FIG. 5 is a block diagram of the information providing device 400 according to the second embodiment.
  • the information providing device 400 has a congestion degree acquisition unit 411, a provided information generation unit 412, a communication unit 413, a control unit 414, and a storage unit 420 as main components.
  • the congestion level acquisition unit 411 receives information about the congestion level from the information processing device 10 . More specifically, the congestion degree acquisition unit 411 receives the unique identification data of the photographing device 310 from the information processing device 10 and information including the corresponding congestion degree.
  • the provided information generation unit 412 generates information to be provided to the user U.
  • the information provided to the user U includes, for example, the operation status of trains on the vehicle 300 and the degree of congestion received from the information processing device 10 .
  • the communication unit 413 is an interface for communication between the information providing device 400 and the information processing device 10 and communication between the information providing device 400 and the user terminal 900 .
  • the control unit 414 includes an arithmetic device such as a CPU, and controls each component of the information providing device 400 .
  • the control unit 414 reads the program 421 from the storage unit 420 and implements a predetermined function according to the read program.
  • the storage unit 420 is a storage device including a non-volatile memory, and stores a program 421 for causing the information providing device 400 to implement the functions of the present embodiment.
  • FIG. 6 is a diagram showing an example of the situation inside the vehicle.
  • FIG. 6 schematically shows a state in which the inside of vehicle 300 is observed from above downward.
  • Vehicle 300 shown in FIG. 6 includes a right side door 301R and a left side door 301L.
  • Persons P10 to P40 are on board the vehicle 300 .
  • a circle shown in the figure indicates the head of each person.
  • Persons P10-P30 stand between right door 301R and left door 301L.
  • a person P40 is sitting on a seat near the right door 301R.
  • photographing devices 310 are installed on the ceiling near the right door 301R and the ceiling near the left door 301L, respectively.
  • the information processing apparatus 10 may acquire image data from either of these two imaging devices 310 , or may acquire image data from either one of the imaging devices 310 .
  • the image capturing device 310 captures a bird's eye view of the surrounding scenery from the vicinity of the right door 301R or the left door 301L. That is, the photographing device 310 photographs the head of a person present in the vehicle 300 from above.
  • a rectangle indicated by a bold two-dot chain line between the right door 301R and the left door 301L is the target area A310.
  • the area setting unit 112 of the information processing device 10 is set so as to be able to extract the target area A310 from the image of the vehicle 300 . That is, the information processing apparatus 10 determines the degree of congestion by setting the target area to an area including the vicinity of the entrance/exit of the vehicle 300 .
  • persons P10 to P30 are included in a target area A310.
  • the person P40 is not included in the target area A310. Therefore, in the case of the example of FIG. 6, the counting unit 113 counts the number of people as 3.
  • the imaging device 310 in the vehicle 300 is configured as described above for the following two reasons.
  • the first reason is that the vehicle 300 is originally equipped with a surveillance camera near the entrance/exit for the purpose of crime prevention or disaster prevention.
  • the information processing apparatus 10 acquires and uses the images of the monitoring camera for the purpose of crime prevention or disaster prevention, thereby eliminating the need to install a new camera in the vehicle 300 and simplifying the configuration of the information processing system 1. can do.
  • the second reason is that when determining the degree of congestion of the vehicle 300, it is possible to grasp the congestion situation in the entire space of the vehicle 300. It is possible to grasp the degree of congestion in For the above reasons, in the information processing system 1, the photographing device 310 is installed above the vehicle 300 and near the entrance/exit.
  • FIG. 7 is a diagram showing an example of conditions for determining the degree of congestion according to the second embodiment.
  • Table T10 is shown in FIG. Table T10 shows congestion degrees 1 to 4 and conditions for determination corresponding to each congestion degree.
  • Table T10 shows the number of people N in the target area as a specific example of conditions for determination.
  • the number of people N in the target area at the congestion degree of 1 is 0 or more and less than 5.
  • the number of people N in the target area at the degree of congestion 2 is 5 or more and less than 10.
  • the number of people N in the target area at the degree of congestion 3 is 10 or more and less than 14.
  • the number of people N in the target area at the congestion degree of 4 is 14 or more.
  • the congestion degree determination unit 114 determines that the first congestion degree (2) when the number of people is, for example, a first value (5 or more and less than 10) is a second value (0 or more and less than 5) that is less than the first value.
  • the congestion degree may be determined so as to be larger than the second congestion degree (1) in .
  • the setting of the degree of congestion is not limited to the above example.
  • Table T10 shown in FIG. 7 shows, as conditions for determining the degree of congestion, the number of people in the target area, the standard deviation of the inter-person distance, and the setting of the target area.
  • the congestion degree determination unit 114 measures inter-person distances, which are distances between a plurality of persons in the target area, calculates a statistic value of the inter-person distances, and calculates the statistic value.
  • the degree of congestion may be determined by taking into consideration. For example, in FIG. 6, the distance D12 is between the person P10 and the person P20. A distance D23 is between the person P20 and the person P30. A distance D13 is between the person P10 and the person P30.
  • the congestion degree determination unit 114 may calculate the average value and standard deviation of the inter-person distances from the distance D12, the distance D23, and the distance 13, and determine the congestion degree from these values. By adopting such a method, it is possible to determine a relatively high degree of congestion when a space in which people are crowded together is included.
  • the area setting unit 112 can set a first area including the vicinity of the entrance and exit of the vehicle 300 and a second area including a portion different from the first area as target areas. Then, the congestion degree determination unit 114 may determine the congestion degree after setting different weights for the first area and the second area.
  • the area setting unit 112 may set the area according to the time zone, the operation section of the vehicle 300, and the like.
  • the region setting unit 112 sets a plurality of regions, the plurality of regions may overlap each other or may be separated from each other.
  • the area set by the area setting unit 112 may have coordinates set in advance, or may be set by recognizing an image.
  • FIG. 8 is a first diagram showing an example of an image according to the second embodiment.
  • FIG. 8 shows a first image F101 captured by the imaging device 310.
  • the first image F101 includes the right side door 301R and the left side door 301L, and further includes the floor 302 and the seat 303 near the entrance/exit. Further, since the photographing device 310 is installed on the ceiling, the first image F101 also includes the handrail 304 installed on the upper part of the vehicle 300 and the in-vehicle advertisement 305 .
  • the first seating area A101 includes images of seats 303, handrails 304 and in-car advertisements 305.
  • the entrance/exit area A102 mainly includes images of the floor 302, the right door 301R and the left door 301L.
  • the second seating area A103 includes a floor 302, a seat 303 and handrails 304.
  • the region setting unit 112 of the information processing device 10 divides the first image F101 into three regions as described above. Then, the counting unit 113 recognizes and counts the heads of persons existing in the entrance/exit area A102 in the divided area.
  • FIG. 9 is a second diagram illustrating an example of an image according to the second embodiment; FIG. 9 shows the second image F102.
  • the second image F102 differs from the first image F101 shown in FIG. 8 in the area setting.
  • an advertising area A106 indicated by a bold dotted line is shown inside the first seating area A101.
  • the advertisement area A106 the in-vehicle advertisement is reflected in most areas of the image.
  • a right door area A104 and a left door area A105 indicated by bold dotted lines are shown inside the entrance/exit area A102.
  • the right door area A104 includes an image of the right door 301R and has a width of about 70 centimeters from the right door 301R toward the center of the vehicle 300.
  • the left door area A105 includes an image of the left door 301L and has a width of about 70 centimeters from the left door 301L toward the center of the vehicle 300.
  • the area setting unit 112 sets a right door area A104 and a left door area A105 in addition to the entrance/exit area A102 as target areas.
  • the counting unit 113 counts the number of people in the entrance/exit area A102, and counts the number of people in the right door area A104 and the left door area A105.
  • the congestion degree determination unit 114 determines the congestion degree from each number of the entrance/exit area A102, the right door area A104, and the left door area A105.
  • the congestion degree determination unit 114 determines that the number of people in the right door area A104 and the left door area A105 is relatively large. It is determined that the degree of congestion is high compared to the state in which the number of people in A104 and left door area A105 is relatively small.
  • the information processing device 10 can determine the degree of congestion by various methods other than the above example.
  • the counting unit 113 may count the number of people in the first seating area A101 or the second seating area A103 depending on the time period and operation status.
  • the counting unit 113 can exclude the advertisement area A106 from the target areas for counting.
  • In-car advertisements can include various illustrations, photographs, and the like. Therefore, when a person's head is displayed in an in-vehicle advertisement, the counting unit 113 may erroneously detect it. Therefore, by preliminarily excluding the advertising area A106 from the target area, the information processing apparatus 10 can suppress deterioration of the congestion degree determination system.
  • the advertisement area may be set in advance, or may be set by the area setting unit 112 automatically determining whether or not there is an advertisement.
  • the counting unit 113 may count the number of people entering and exiting the vehicle 300 at the timing when the vehicle 300 stops at the station and the doors are open. In this case, for example, the counting unit 113 detects the orientation of the face of the person, adds the person facing the direction of getting into the vehicle, and subtracts the person facing the direction of getting out of the vehicle. With such a configuration, the information processing apparatus 10 can determine the degree of congestion even when a person is getting on and off the vehicle.
  • the second embodiment has been described above. According to the information processing system 1 or the information processing device 10 according to the second embodiment, it is possible to provide an information processing device or the like that accurately determines the degree of congestion with a simple configuration.
  • FIG. 10 is a block diagram illustrating the hardware configuration of a computer.
  • the information processing apparatus can implement the functions described above using a computer 500 including the hardware configuration shown in the drawing.
  • the computer 500 may be a portable computer such as a smart phone or a tablet terminal, or may be a stationary computer such as a PC.
  • Computer 500 may be a dedicated computer designed to implement each device, or may be a general-purpose computer.
  • the computer 500 can implement desired functions by installing predetermined applications.
  • Computer 500 has bus 502 , processor 504 , memory 506 , storage device 508 , input/output interface (I/F) 510 and network interface (I/F) 512 .
  • the bus 502 is a data transmission path through which the processor 504, memory 506, storage device 508, input/output interface 510, and network interface 512 exchange data with each other.
  • the method of connecting the processors 504 and the like to each other is not limited to bus connection.
  • the processor 504 is various processors such as CPU, GPU or FPGA.
  • the memory 506 is a main memory implemented using a RAM (Random Access Memory) or the like.
  • the storage device 508 is an auxiliary storage device realized using a hard disk, SSD, memory card, ROM (Read Only Memory), or the like.
  • the storage device 508 stores programs for realizing desired functions.
  • the processor 504 reads this program into the memory 506 and executes it, thereby realizing each functional component of each device.
  • the input/output interface 510 is an interface for connecting the computer 500 and input/output devices.
  • the input/output interface 510 is connected to an input device such as a keyboard and an output device such as a display device.
  • a network interface 512 is an interface for connecting the computer 500 to a network.
  • a program includes a set of instructions (or software code) that, when read into a computer, cause the computer to perform one or more of the functions described in the embodiments.
  • the program may be stored in a non-transitory computer-readable medium or tangible storage medium.
  • computer readable media or tangible storage media may include random-access memory (RAM), read-only memory (ROM), flash memory, solid-state drives (SSD) or other memory technology, CDs - ROM, digital versatile disc (DVD), Blu-ray disc or other optical disc storage, magnetic cassette, magnetic tape, magnetic disc storage or other magnetic storage device.
  • the program may be transmitted on a transitory computer-readable medium or communication medium.
  • transitory computer readable media or communication media include electrical, optical, acoustic, or other forms of propagated signals.
  • information processing system 10 information processing device 111 image data acquisition unit 112 area setting unit 113 counting unit 114 congestion degree determination unit 115 output unit 300 vehicle 301R right side door 301L left side door 302 floor 303 seat 304 handrail 305 car advertisement 310 photographing device 311 camera 312 communication unit 313 control unit 320 storage unit 400 information providing device 411 congestion level acquisition unit 412 provision information generation unit 413 communication unit 414 control unit 420 storage unit 500 computer 502 bus 504 processor 506 memory 508 storage device 510 input/output I/F 512 network I/F 900 user terminal

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Abstract

An image processing device (10) includes an image data acquisition unit (111), a region setting unit (112), a counting unit (113), a crowding determination unit (114), and an output unit (115). The image data acquisition unit (111) acquires image data generated by a camera that captures the interior of a car. The region setting unit (112) divides an image expressed by the image data into a plurality of regions. The counting unit (113) counts the number of people present in a region of interest from among the plurality of regions. The crowding determination unit (114) determines the degree of crowding inside the car on the basis of the number of people. The output unit (115) outputs information related to the degree of crowding.

Description

情報処理装置、情報処理方法およびコンピュータ可読媒体Information processing device, information processing method and computer readable medium
　本発明は情報処理装置、情報処理方法およびコンピュータ可読媒体に関する。 The present invention relates to an information processing device, an information processing method, and a computer-readable medium.
　列車等の車両の混雑状態を把握したいという要求が高まっている。 　There is an increasing demand for understanding the congestion status of trains and other vehicles.
　特許文献１に記載の車両混雑状況通知システムは、乗車人数検出装置が列車の車両ごとに設置されていて、列車が発車したときに車両に乗車している人数を検出し、検出した乗車人数のデータをサーバ装置に送信する。車両混雑状況通知システムを構成するカメラは、車両の車内の上部である天井に光軸を下方に向け設置され、車両の長手方向に複数台設置されていて、車両に乗車しているすべての利用者の検出をカバーするようにしている。 In the vehicle congestion status notification system described in Patent Document 1, a passenger number detection device is installed in each vehicle of a train, detects the number of passengers on the vehicle when the train departs, and detects the number of passengers. Send the data to the server device. The cameras that make up the vehicle congestion status notification system are installed on the ceiling, which is the upper part of the interior of the vehicle, with the optical axis facing downward. to cover the detection of
　列車混雑度通知システムは、列車設備として、列車内のドア付近を撮影するカメラと、カメラによって取得された映像データに基づいて列車内の混雑度を算出するデータ処理部と、データ処理部から出力される混雑度情報と、を有している。またこのシステムは、列車を特定する列車特定情報と、列車内におけるカメラによる撮影位置を示す撮影位置情報とを含む混雑状況データを送信する送信部とを有し、混雑状況を情報センタに保存させ、駅の表示部に表示させる。 The train congestion level notification system consists of a camera that captures the area near the door inside the train as train equipment, a data processing unit that calculates the degree of congestion within the train based on the video data acquired by the camera, and output from the data processing unit. Congestion degree information to be used. This system also has a transmitting unit for transmitting congestion state data including train identification information for identifying a train and photographing position information indicating a photographing position in the train by a camera, and stores the congestion state in an information center. , to be displayed on the station display.
特開２０１９－０５９３１５号公報JP 2019-059315 A 特開２００７－２９０５７４号公報JP 2007-290574 A
　車両の混雑度を判定するには、車両内に存在する人物の数や状態などを認識する必要がある。しかしながら、車両内の全ての人物や空席を検出すると非常に煩雑なシステムとなり好ましくない。一方、簡易な構成であっても混雑状態を適切に判定したい。 　In order to determine the degree of congestion in a vehicle, it is necessary to recognize the number and conditions of people in the vehicle. However, detecting all persons and vacant seats in the vehicle would result in a very complicated system, which is not preferable. On the other hand, it is desired to appropriately determine the congestion state even with a simple configuration.
　本開示はこのような課題を鑑みてなされたものであり、簡易な構成で精度よく混雑度を判定する情報処理装置等を提供することを目的とする。 The present disclosure has been made in view of such problems, and aims to provide an information processing device or the like that accurately determines the degree of congestion with a simple configuration.
　本開示の１実施形態にかかる情報処理装置は、画像データ取得部、領域設定部、カウント部、混雑度判定部および出力部を有している。画像データ取得部は、車両の内部を撮影するカメラが生成した画像データを取得する。領域設定部は、画像データにかかる画像を複数の領域に分割する。カウント部は、複数の領域のうちの対象領域に存在する人物の数をカウントする。混雑度判定部は、人物の数に基づいて車両の混雑度を判定する。出力部は、混雑度に関する情報を出力する。 An information processing apparatus according to an embodiment of the present disclosure has an image data acquisition unit, an area setting unit, a counting unit, a congestion degree determination unit, and an output unit. The image data acquisition unit acquires image data generated by a camera that captures the interior of the vehicle. The region setting unit divides an image related to image data into a plurality of regions. The counting unit counts the number of persons present in a target area among the plurality of areas. The congestion level determination unit determines the vehicle congestion level based on the number of people. The output unit outputs information about the degree of congestion.
　本開示の１実施形態にかかる情報処理方法は、以下の方法をコンピュータが実行する。コンピュータは、車両の内部を撮影するカメラが生成した画像データを取得する。コンピュータは、画像データにかかる画像を複数の領域に分割する。コンピュータは、複数の前記領域のうちの対象領域に存在する人物の数をカウントする。コンピュータは、人物の数に基づいて前記車両の混雑度を判定する。コンピュータは、混雑度に関する情報を出力する。 In an information processing method according to an embodiment of the present disclosure, a computer executes the following method. The computer acquires image data generated by a camera that captures the interior of the vehicle. A computer divides an image corresponding to image data into a plurality of regions. The computer counts the number of persons present in a target area of the plurality of areas. A computer determines the degree of congestion of the vehicle based on the number of people. The computer outputs information about the degree of congestion.
　本開示の１実施形態にかかるプログラムは、コンピュータに、以下のステップを実行させるものである。コンピュータは、コンピュータは、車両の内部を撮影するカメラが生成した画像データを取得する。コンピュータは、画像データにかかる画像を複数の領域に分割する。コンピュータは、複数の前記領域のうちの対象領域に存在する人物の数をカウントする。コンピュータは、人物の数に基づいて前記車両の混雑度を判定する。コンピュータは、混雑度に関する情報を出力する。 A program according to an embodiment of the present disclosure causes a computer to execute the following steps. The computer acquires image data generated by a camera that captures the interior of the vehicle. A computer divides an image corresponding to image data into a plurality of regions. The computer counts the number of persons present in a target area of the plurality of areas. A computer determines the degree of congestion of the vehicle based on the number of people. The computer outputs information about the degree of congestion.
　本開示によれば、簡易な構成で精度よく混雑度を判定する情報処理装置等を提供することができる。 According to the present disclosure, it is possible to provide an information processing device or the like that accurately determines the degree of congestion with a simple configuration.
実施の形態１にかかる情報処理装置のブロック図である。1 is a block diagram of an information processing device according to a first embodiment; FIG. 実施の形態１にかかる情報処理方法のフローチャートである。4 is a flowchart of an information processing method according to the first embodiment; 実施の形態２にかかる情報処理システムのブロック図である。2 is a block diagram of an information processing system according to a second embodiment; FIG. 実施の形態２にかかる撮影装置のブロック図である。2 is a block diagram of an imaging device according to a second embodiment; FIG. 実施の形態２にかかる情報提供装置のブロック図である。2 is a block diagram of an information providing device according to a second embodiment; FIG. 車両内の状況の例を示す図である。FIG. 2 is a diagram showing an example of a situation inside a vehicle; FIG. 実施の形態２にかかる混雑度を判定するための条件の例を示す図である。FIG. 10 is a diagram showing an example of conditions for determining the degree of congestion according to the second embodiment; FIG. 実施の形態２にかかる画像の例を示す第１の図である。FIG. 11 is a first diagram showing an example of an image according to the second embodiment; FIG. 実施の形態２にかかる画像の例を示す第２の図である。FIG. 12 is a second diagram showing an example of an image according to the second embodiment; FIG. コンピュータのハードウェア構成を例示するブロック図である。It is a block diagram which illustrates the hardware constitutions of a computer.
　以下、発明の実施の形態を通じて本発明を説明するが、特許請求の範囲にかかる発明を以下の実施形態に限定するものではない。また、実施形態で説明する構成の全てが課題を解決するための手段として必須であるとは限らない。説明の明確化のため、以下の記載および図面は、適宜、省略、および簡略化がなされている。なお、各図面において、同一の要素には同一の符号が付されており、必要に応じて重複説明は省略されている。 The present invention will be described below through embodiments of the invention, but the invention according to the scope of claims is not limited to the following embodiments. Moreover, not all the configurations described in the embodiments are essential as means for solving the problems. For clarity of explanation, the following descriptions and drawings are omitted and simplified as appropriate. In each drawing, the same elements are denoted by the same reference numerals, and redundant description is omitted as necessary.
　＜実施の形態１＞
　以下、図面を参照して本発明の実施の形態について説明する。図１は、実施の形態１にかかる情報処理装置１０のブロック図である。図１に示す情報処理装置１０は、所定の交通機関に設けられたカメラが撮影した画像から、かかる交通機関の混雑度を判定して出力する。本開示における所定の交通機関とは例えば、列車、トラム、トロリーまたはバスなど複数の人物が搭乗する交通機関である。図１に示す情報処理装置１０は主な構成として、画像データ取得部１１１、領域設定部１１２、カウント部１１３、混雑度判定部１１４および出力部１１５を有している。 <Embodiment 1>
BEST MODE FOR CARRYING OUT THE INVENTION Hereinafter, embodiments of the present invention will be described with reference to the drawings. FIG. 1 is a block diagram of an information processing device 10 according to the first embodiment. The information processing apparatus 10 shown in FIG. 1 determines and outputs the degree of congestion of a predetermined transportation facility from an image captured by a camera provided in the transportation facility. A predetermined means of transportation in the present disclosure is, for example, a means of transportation boarded by a plurality of persons, such as a train, a tram, a trolley, or a bus. The information processing apparatus 10 shown in FIG. 1 has an image data acquisition unit 111, an area setting unit 112, a counting unit 113, a congestion degree determination unit 114, and an output unit 115 as main components.
　画像データ取得部１１１は、車両の内部を撮影するカメラが生成した画像データを取得する。画像データ取得部１１１は、予め設定された期間ごとに画像データを取得しても良い。予め設定された期間とは例えば２分、５分、１０分などである。画像データ取得部１１１は受け取った画像データを領域設定部１１２に供給する。なお、画像データ取得部１１１が一回に受け取る画像データは１フレーム分の静止画像データであってもよいし、連続した数フレーム分の動画像データであってもよい。動画像データは例えば毎秒３０フレームや毎秒１５フレームの画像データである。動画像データは例えば、ＭＰＥＧ（Moving Picture Experts Group）、モーションＪＰＥＧ（Joint Photographic Experts Group）またはＡＶＩ（Audio Video Interleave）等の規格に沿ったものであってもよい。 The image data acquisition unit 111 acquires image data generated by a camera that captures the interior of the vehicle. The image data acquisition unit 111 may acquire image data for each preset period. The preset period is, for example, 2 minutes, 5 minutes, 10 minutes, or the like. The image data acquisition unit 111 supplies the received image data to the area setting unit 112 . Note that the image data received by the image data acquisition unit 111 at one time may be one frame of still image data, or may be several consecutive frames of moving image data. The moving image data is, for example, image data of 30 frames per second or 15 frames per second. The moving image data may conform to standards such as MPEG (Moving Picture Experts Group), motion JPEG (Joint Photographic Experts Group), or AVI (Audio Video Interleave).
　領域設定部１１２は、画像データ取得部１１１から受け取った画像データにかかる画像を複数の領域に分割する。領域設定部１１２が行う画像の分割にかかる領域は予め設定されたものであってもよいし、所定の条件に応じて変化するものであっても良い。所定の条件とは例えば情報処理装置１０の管理者がおこなう操作によって設定されるものであってもよいし、時刻や車両の運行状態などに応じて変更されるものであってもよい。領域設定部１１２が行う分割は、例えば画像データを分割にかかる複数の画像データに分離してもよいし、分割にかかる領域の境界を示す情報を生成するものであってもよい。領域設定部１１２は画像を分割すると、分割した画像にかかる画像データをカウント部１１３に供給する。 The area setting unit 112 divides the image corresponding to the image data received from the image data acquisition unit 111 into a plurality of areas. The area for dividing the image by the area setting unit 112 may be set in advance, or may be changed according to a predetermined condition. The predetermined condition may be set by, for example, an operation performed by an administrator of the information processing device 10, or may be changed according to the time of day, the running state of the vehicle, or the like. The division performed by the region setting unit 112 may be, for example, separating the image data into a plurality of pieces of image data to be divided, or generating information indicating the boundaries of the regions to be divided. After dividing the image, the area setting unit 112 supplies image data related to the divided image to the counting unit 113 .
　カウント部１１３は、領域設定部１１２から分割した画像にかかる画像データを受け取り、分割にかかる複数の領域のうちの対象領域に存在する人物の数をカウントする。ここで対象領域とは、予め設定されたものであって、情報処理装置１０が混雑度を判定する際の処理の対象となる領域を指す。カウント部１１３は、対象領域に存在する人物の数をカウントすると、カウントした数にかかる情報を混雑度判定部１１４に供給する。 The counting unit 113 receives image data related to the divided image from the region setting unit 112, and counts the number of persons existing in the target region among the plurality of divided regions. Here, the target area refers to an area that is set in advance and that is to be processed when the information processing apparatus 10 determines the degree of congestion. After counting the number of persons existing in the target area, the counting unit 113 supplies information about the counted number to the congestion degree determination unit 114 .
　混雑度判定部１１４は、カウント部１１３がカウントした人物の数にかかる情報を受け取り、受け取った情報から対象領域にかかる車両の混雑度を判定する。対象領域における人物の数と混雑度との関係は、予め設定されたものである。ただし混雑度判定部１１４は混雑度を判定する際に、対象領域における人物の数に加えて、他の要素を加味することもできる。他の要素とは例えば人物が存在する位置にかかる情報や、人物同士の距離に関する情報などである。混雑度判定部１１４は、混雑度を判定すると、判定した混雑度に関する情報を生成し、生成した情報を出力部１１５に供給する。判定した混雑度に関する情報は、混雑度の他に、判定した車両の識別情報が含まれる。 The congestion degree determination unit 114 receives information about the number of people counted by the counting unit 113, and determines the congestion degree of vehicles in the target area from the received information. The relationship between the number of people in the target area and the degree of congestion is set in advance. However, the congestion level determination unit 114 can also consider other factors in addition to the number of people in the target area when determining the congestion level. Other elements include, for example, information about the positions of people and information about distances between people. After determining the congestion degree, the congestion degree determination unit 114 generates information about the determined congestion degree, and supplies the generated information to the output unit 115 . Information about the determined degree of congestion includes identification information of the determined vehicle in addition to the degree of congestion.
　出力部１１５は、混雑度判定部１１４から混雑度に関する情報を受け取ると、受け取った情報を、所定の出力先へ出力する。所定の出力先とは例えば上述の判定にかかる車両を利用する利用者や、かかる車両の運行を管理している運行管理者である。 When the output unit 115 receives information about the degree of congestion from the congestion degree determination unit 114, the output unit 115 outputs the received information to a predetermined output destination. The predetermined output destination is, for example, the user who uses the vehicle for which the above determination is made, or the operation manager who manages the operation of the vehicle.
　次に、図２を参照して、情報処理装置１０が行う情報管理方法について説明する。図２は、実施の形態１にかかる情報管理方法を示すフローチャートである。図２に示すフローチャートは、例えば情報処理装置１０を起動することにより開始される。 Next, an information management method performed by the information processing apparatus 10 will be described with reference to FIG. FIG. 2 is a flow chart showing the information management method according to the first embodiment. The flowchart shown in FIG. 2 is started by, for example, activating the information processing apparatus 10 .
　まず、画像データ取得部１１１は、車両の内部を撮影するカメラが生成した画像データを取得する（ステップＳ１１）。 First, the image data acquisition unit 111 acquires image data generated by a camera that captures the interior of the vehicle (step S11).
　領域設定部１１２は、画像データにかかる画像を複数の領域に分割する（ステップＳ１２）。 The area setting unit 112 divides the image related to the image data into a plurality of areas (step S12).
　カウント部１１３は、複数の前記領域のうちの対象領域に存在する人物の数をカウントする（ステップＳ１３）。 The counting unit 113 counts the number of persons existing in the target area among the plurality of areas (step S13).
　混雑度判定部１１４は、人物の数に基づいて前記車両の混雑度を判定する（ステップＳ１４）。 The congestion degree determination unit 114 determines the congestion degree of the vehicle based on the number of people (step S14).
　出力部１１５は、混雑度に関する情報を出力し（ステップＳ１５）、一連の処理を終了する。なお、上述の情報処理方法は、情報処理装置１０が画像データを取得する度に実行されてもよい。また上述の情報処理方法は、予め設定された期間ごとに実行されてもよい。 The output unit 115 outputs information about the degree of congestion (step S15), and ends the series of processes. Note that the information processing method described above may be executed each time the information processing apparatus 10 acquires image data. Further, the information processing method described above may be executed for each preset period.
　以上、実施の形態１にかかる情報処理装置および情報処理方法について説明した。尚、情報処理装置１０は、図示しない構成としてプロセッサ及び記憶装置を有するものである。情報処理装置１０が有する記憶装置は、例えばフラッシュメモリやＳＳＤ（Solid State Drive）などの不揮発性メモリを含む記憶装置を含む。この場合に、情報処理装置１０が有する記憶装置は、上述の画像処理方法を実行するためのコンピュータプログラム（以降、単にプログラムとも称する）を記憶している。またプロセッサは、記憶装置からコンピュータプログラムをＤＲＡＭ（Dynamic Random Access Memory）等のバッファメモリへ読み込ませ、当該プログラムを実行する。 The information processing apparatus and information processing method according to the first embodiment have been described above. The information processing apparatus 10 has a processor and a storage device (not shown). The storage device included in the information processing device 10 includes, for example, a storage device including non-volatile memory such as flash memory and SSD (Solid State Drive). In this case, the storage device of the information processing apparatus 10 stores a computer program (hereinafter also simply referred to as a program) for executing the image processing method described above. The processor also loads a computer program from a storage device into a buffer memory such as a DRAM (Dynamic Random Access Memory) and executes the program.
　情報処理装置１０が有する各構成は、それぞれが専用のハードウェアで実現されていてもよい。また、各構成要素の一部又は全部は、汎用または専用の回路（circuitry）、プロセッサ等やこれらの組合せによって実現されてもよい。これらは、単一のチップによって構成されてもよいし、バスを介して接続される複数のチップによって構成されてもよい。各装置の各構成要素の一部又は全部は、上述した回路等とプログラムとの組合せによって実現されてもよい。また、プロセッサとして、ＣＰＵ（Central Processing Unit）、ＧＰＵ（Graphics Processing Unit）、ＦＰＧＡ（field-programmable gate array）等を用いることができる。なお、ここに説明した構成に関する説明は、本開示において以下に説明するその他の装置またはシステムにおいても、適用され得る。 Each configuration of the information processing device 10 may be realized by dedicated hardware. Also, part or all of each component may be implemented by a general-purpose or dedicated circuit, processor, etc., or a combination thereof. These may be composed of a single chip, or may be composed of multiple chips connected via a bus. A part or all of each component of each device may be implemented by a combination of the above-described circuits and the like and programs. As the processor, a CPU (Central Processing Unit), GPU (Graphics Processing Unit), FPGA (field-programmable gate array), or the like can be used. It should be noted that the configuration descriptions described herein may also be applied to other devices or systems described below in the present disclosure.
　また、情報処理装置１０の各構成要素の一部又は全部が複数の情報処理装置や回路等により実現される場合には、複数の情報処理装置や回路等は、集中配置されてもよいし、分散配置されてもよい。例えば、情報処理装置や回路等は、クライアントサーバシステム、クラウドコンピューティングシステム等、各々が通信ネットワークを介して接続される形態として実現されてもよい。また、情報処理装置１０の機能がＳａａＳ（Software as a Service）形式で提供されてもよい。 Further, when part or all of each component of the information processing device 10 is realized by a plurality of information processing devices, circuits, etc., the plurality of information processing devices, circuits, etc. may be centrally arranged, They may be distributed. For example, the information processing device, circuits, and the like may be implemented as a form in which each is connected via a communication network, such as a client-server system, a cloud computing system, or the like. Also, the functions of the information processing device 10 may be provided in a SaaS (Software as a Service) format.
　以上、実施の形態１について説明した。実施の形態１によれば、簡易な構成で精度よく混雑度を判定する情報処理装置等を提供することができる。 The first embodiment has been described above. According to Embodiment 1, it is possible to provide an information processing apparatus or the like that accurately determines the degree of congestion with a simple configuration.
　＜実施の形態２＞
　次に、実施の形態２について説明する。図３は、実施の形態２にかかる情報処理システム１のブロック図である。図３に示す情報処理システム１は主な構成として、情報処理装置１０および撮影装置３１０を含む。また情報処理システム１は情報提供装置４００を含んでもよい。情報処理システム１はさらにユーザ端末９００を含んでもよい。 <Embodiment 2>
Next, Embodiment 2 will be described. FIG. 3 is a block diagram of the information processing system 1 according to the second embodiment. The information processing system 1 shown in FIG. 3 includes an information processing device 10 and an imaging device 310 as main components. The information processing system 1 may also include an information providing device 400 . The information processing system 1 may further include a user terminal 900 .
　本実施形態における情報処理装置１０は、ネットワークＮ１を介して撮影装置３１０と通信可能に接続している。情報処理装置１０は撮影装置３１０から車両３００の内部を撮影した画像にかかる画像データを取得する。情報処理装置１０は撮影装置３１０から取得した画像データから混雑度を判定する。情報処理装置１０はまた、ネットワークＮ１を介して情報提供装置４００と通信可能に接続している。情報処理装置１０は撮影装置３１０から取得した画像データから混雑度を判定すると、車両３００の混雑度に関する情報を情報提供装置４００に出力する。 The information processing device 10 in this embodiment is communicably connected to the imaging device 310 via the network N1. The information processing device 10 acquires image data related to an image of the interior of the vehicle 300 captured from the image capturing device 310 . The information processing device 10 determines the degree of congestion from the image data acquired from the photographing device 310 . The information processing device 10 is also communicably connected to the information providing device 400 via the network N1. When the information processing device 10 determines the degree of congestion from the image data acquired from the imaging device 310 , the information processing device 10 outputs information regarding the degree of congestion of the vehicles 300 to the information providing device 400 .
　本実施の形態における画像データ取得部１１１は、車両３００の上部に設置された撮影装置３１０が人物を俯瞰するように撮影した画像にかかる画像データを取得する。また上述のように撮影装置３１０は車両３００の乗降口付近に設置されている。そのため画像データ取得部１１１は、車両３００の乗降口を含む画像にかかる画像データを取得する。 The image data acquisition unit 111 according to the present embodiment acquires image data related to an image captured by a photographing device 310 installed on the top of the vehicle 300 so as to look down on a person. Further, as described above, the photographing device 310 is installed near the entrance/exit of the vehicle 300 . Therefore, the image data acquisition unit 111 acquires image data related to an image including the entrance/exit of the vehicle 300 .
　本実施の形態における領域設定部１１２は、車両３００の乗降口付近を含む画像を対象領域に設定する。 The area setting unit 112 according to the present embodiment sets an image including the vicinity of the entrance/exit of the vehicle 300 as the target area.
　本実施の形態におけるカウント部１１３は、撮影装置３１０から取得した画像データから人物の頭部を認識する。すなわちカウント部１１３は取得した画像データのうちの対象領域において認識した頭部の数をカウントする。カウント部１１３は頭部を認識する手段として、例えば画像データをＣＮＮ（Convolutional Neural Network）による畳み込み処理を利用してもよい。またカウント部１１３は頭部のサンプル画像を学習した学習器を利用して頭部を認識してもよい。機械学習を利用することにより、カウント部１１３は頭部の認識精度を向上させることができる。 The counting unit 113 in the present embodiment recognizes a person's head from the image data acquired from the imaging device 310 . That is, the counting unit 113 counts the number of recognized heads in the target area in the acquired image data. As means for recognizing the head, the counting unit 113 may use, for example, convolution processing of image data by a CNN (Convolutional Neural Network). The counting unit 113 may recognize the head using a learning device that has learned sample images of the head. By using machine learning, the counting unit 113 can improve the recognition accuracy of the head.
　撮影装置３１０は、車両３００の天井に設置され、車両３００の上部から車両３００の内部の人物を俯瞰するように撮影する。撮影装置３１０は車両３００の乗降口付近の天井に設置されるのが好ましい。撮影装置３１０が車両３００の乗降口付近に設置されることにより、情報処理システム１は、車両３００の混雑度を好適に判定できる。撮影装置３１０は、車両３００の内部の風景を撮影して画像データを生成する。撮影装置３１０は、ネットワークＮ１を介して、生成した画像データを情報処理装置１０に供給する。なお、車両３００に設置される撮影装置３１０は１つでもよいし、複数でもよい。 The photographing device 310 is installed on the ceiling of the vehicle 300 and photographs a person inside the vehicle 300 from above the vehicle 300 from above. The photographing device 310 is preferably installed on the ceiling near the doorway of the vehicle 300 . By installing the photographing device 310 near the entrance/exit of the vehicle 300 , the information processing system 1 can suitably determine the degree of congestion of the vehicle 300 . The photographing device 310 photographs the scenery inside the vehicle 300 and generates image data. The imaging device 310 supplies the generated image data to the information processing device 10 via the network N1. In addition, the number of the imaging device 310 installed in the vehicle 300 may be one, or may be plural.
　情報提供装置４００は、ネットワークＮ１を介して情報処理装置１０から車両３００の混雑度に関する情報を受け取る。情報提供装置４００はまた、ネットワークＮ１を介してユーザ端末９００に通信可能に接続している。情報提供装置４００は、車両３００の混雑度に関する情報をユーザ端末９００に提供する。ユーザ端末９００は例えばスマートフォンである。ユーザ端末９００は、ネットワークＮ１を介して情報提供装置４００から車両３００の混雑度を受け取る。これによりユーザＵは、自身の端末であるユーザ端末９００を操作して車両３００の混雑度を把握できる。なおユーザ端末９００はタブレット端末、パーソナルコンピュータ等であってもよい。 The information providing device 400 receives information regarding the congestion degree of the vehicle 300 from the information processing device 10 via the network N1. The information providing device 400 is also communicably connected to the user terminal 900 via the network N1. The information providing device 400 provides the user terminal 900 with information on the congestion degree of the vehicle 300 . User terminal 900 is, for example, a smart phone. The user terminal 900 receives the congestion degree of the vehicle 300 from the information providing device 400 via the network N1. Thereby, the user U can grasp the congestion degree of the vehicle 300 by operating the user terminal 900 which is his/her own terminal. Note that the user terminal 900 may be a tablet terminal, a personal computer, or the like.
　次に図４を参照して撮影装置３１０の詳細について説明する。図４は、実施の形態２にかかる撮影装置３１０のブロック図である。撮影装置３１０は主な構成として、カメラ３１１、通信部３１２、制御部３１３および記憶部３２０を有している。 Next, the details of the imaging device 310 will be described with reference to FIG. FIG. 4 is a block diagram of the imaging device 310 according to the second embodiment. The photographing device 310 has a camera 311, a communication section 312, a control section 313, and a storage section 320 as main components.
　カメラ３１１は、車両３００の内部の風景を撮影して画像データを生成する。カメラ３１１は、対物レンズ、撮像素子、光電変換部および画像生成部等を含む。 The camera 311 captures the scenery inside the vehicle 300 and generates image data. The camera 311 includes an objective lens, an imaging device, a photoelectric conversion section, an image generation section, and the like.
　通信部３１２は、撮影装置３１０をネットワークＮ１に通信可能に接続するためのインタフェースである。通信部３１２は、カメラ３１１が生成した画像データ等を、ネットワークＮ１を介して情報処理装置１０に供給する。また通信部３１２は、ネットワークＮ１を介して情報処理装置１０からの画像データ要求に関する信号を受け取っても良い。 The communication unit 312 is an interface for communicably connecting the imaging device 310 to the network N1. The communication unit 312 supplies image data and the like generated by the camera 311 to the information processing apparatus 10 via the network N1. The communication unit 312 may also receive a signal regarding an image data request from the information processing apparatus 10 via the network N1.
　制御部３１３は、例えばＣＰＵまたはＭＰＵ等の演算装置であって、撮影装置３１０が有する各構成を制御する。また制御部３１３は記憶部３２０が記憶しているプログラム３２１を実行する。より具体的には例えば制御部３１３は、予め設定されたプログラムに従い、所定の期間ごとにカメラ３１１が生成した画像データと固有識別データとを情報処理装置１０に提供する処理を実行する。 The control unit 313 is an arithmetic device such as a CPU or MPU, for example, and controls each component of the imaging device 310 . Also, the control unit 313 executes a program 321 stored in the storage unit 320 . More specifically, for example, the control unit 313 executes processing for providing the information processing apparatus 10 with image data generated by the camera 311 and unique identification data at predetermined intervals according to a preset program.
　記憶部３２０は、不揮発性メモリを含む記憶装置である。記憶部３２０は例えば、撮影装置３１０の制御を司るプログラム３２１を記憶している。また記憶部３２０は例えば撮影装置３１０に設定されている固有識別データを記憶している。 The storage unit 320 is a storage device including nonvolatile memory. The storage unit 320 stores, for example, a program 321 that controls the imaging device 310 . The storage unit 320 also stores, for example, unique identification data set in the photographing device 310 .
　次に、図５を参照して情報提供装置４００について説明する。図５は、実施の形態２にかかる情報提供装置４００のブロック図である。情報提供装置４００は主な構成として、混雑度取得部４１１、提供情報生成部４１２、通信部４１３、制御部４１４および記憶部４２０を有している。 Next, the information providing device 400 will be described with reference to FIG. FIG. 5 is a block diagram of the information providing device 400 according to the second embodiment. The information providing device 400 has a congestion degree acquisition unit 411, a provided information generation unit 412, a communication unit 413, a control unit 414, and a storage unit 420 as main components.
　混雑度取得部４１１は、情報処理装置１０から混雑度に関する情報を受け取る。より詳細には、混雑度取得部４１１は、情報処理装置１０から撮影装置３１０の固有識別データとともに、これに対応する混雑度を含む情報を受け取る。 The congestion level acquisition unit 411 receives information about the congestion level from the information processing device 10 . More specifically, the congestion degree acquisition unit 411 receives the unique identification data of the photographing device 310 from the information processing device 10 and information including the corresponding congestion degree.
　提供情報生成部４１２は、ユーザＵに提供する情報を生成する。ユーザＵに提供する情報には、例えば、車両３００にかかる列車の運行状況とともに、情報処理装置１０から受け取った混雑度が含まれる。 The provided information generation unit 412 generates information to be provided to the user U. The information provided to the user U includes, for example, the operation status of trains on the vehicle 300 and the degree of congestion received from the information processing device 10 .
　通信部４１３は、情報提供装置４００と情報処理装置１０との通信および情報提供装置４００とユーザ端末９００との通信を行うためのインタフェースである。 The communication unit 413 is an interface for communication between the information providing device 400 and the information processing device 10 and communication between the information providing device 400 and the user terminal 900 .
　制御部４１４は、ＣＰＵ等の演算装置を含み、情報提供装置４００の各構成を制御する。制御部４１４は記憶部４２０からプログラム４２１を読み取り、読み取ったプログラムにしたがって、本実施形態にかかる所定の機能を実現する。 The control unit 414 includes an arithmetic device such as a CPU, and controls each component of the information providing device 400 . The control unit 414 reads the program 421 from the storage unit 420 and implements a predetermined function according to the read program.
　記憶部４２０は不揮発性メモリを含む記憶装置であって、情報提供装置４００に本実施の形態における機能を実現させるためのプログラム４２１を記憶している。 The storage unit 420 is a storage device including a non-volatile memory, and stores a program 421 for causing the information providing device 400 to implement the functions of the present embodiment.
　次に、車両３００における撮影装置３１０の位置、撮影装置３１０が撮影する領域および混雑度を判定するための対象領域の例について説明する。 Next, an example of the position of the photographing device 310 in the vehicle 300, the region photographed by the photographing device 310, and the target region for determining the degree of congestion will be described.
　図６は、車両内の状況の例を示す図である。図６は、車両３００の内部を上方から下方に向かって観察した状態を模式的に示している。図６に示す車両３００は、右側ドア３０１Ｒおよび左側ドア３０１Ｌを含む。車両３００内には人物Ｐ１０～Ｐ４０が搭乗している。図に示す円形はそれぞれの人物の頭部を示している。人物Ｐ１０～Ｐ３０は、右側ドア３０１Ｒと左側ドア３０１Ｌとの間に立っている。また人物Ｐ４０は右側ドア３０１Ｒ付近の座席に座っている。 FIG. 6 is a diagram showing an example of the situation inside the vehicle. FIG. 6 schematically shows a state in which the inside of vehicle 300 is observed from above downward. Vehicle 300 shown in FIG. 6 includes a right side door 301R and a left side door 301L. Persons P10 to P40 are on board the vehicle 300 . A circle shown in the figure indicates the head of each person. Persons P10-P30 stand between right door 301R and left door 301L. A person P40 is sitting on a seat near the right door 301R.
　車両３００は右側ドア３０１Ｒの近傍の天井と左側ドア３０１Ｌの近傍の天井それぞれに、撮影装置３１０がそれぞれ設置されている。情報処理装置１０はこれら２つの撮影装置３１０のいずれからの画像データを取得してもよいし、いずれか一方の撮影装置３１０から画像データを取得するものであってもよい。撮影装置３１０は右側ドア３０１Ｒまたは左側ドア３０１Ｌの近傍から周辺の風景を俯瞰するように撮影する。すなわち撮影装置３１０は車両３００に存在する人物の頭部を上方から撮影する。 In the vehicle 300, photographing devices 310 are installed on the ceiling near the right door 301R and the ceiling near the left door 301L, respectively. The information processing apparatus 10 may acquire image data from either of these two imaging devices 310 , or may acquire image data from either one of the imaging devices 310 . The image capturing device 310 captures a bird's eye view of the surrounding scenery from the vicinity of the right door 301R or the left door 301L. That is, the photographing device 310 photographs the head of a person present in the vehicle 300 from above.
　右側ドア３０１Ｒと左側ドア３０１Ｌとの間に太字の二点鎖線により示された矩形は、対象領域Ａ３１０である。情報処理装置１０の領域設定部１１２は車両３００の画像からこの対象領域Ａ３１０を抽出できるように設定される。すなわち情報処理装置１０は、対象領域を車両３００の乗降口付近を含む領域に設定することにより混雑度を判定する。図において、人物Ｐ１０～Ｐ３０は、対象領域Ａ３１０に含まれる。一方、人物Ｐ４０は対象領域Ａ３１０に含まれない。そのため図６の例の場合において、カウント部１１３は人数を３とカウントする。 A rectangle indicated by a bold two-dot chain line between the right door 301R and the left door 301L is the target area A310. The area setting unit 112 of the information processing device 10 is set so as to be able to extract the target area A310 from the image of the vehicle 300 . That is, the information processing apparatus 10 determines the degree of congestion by setting the target area to an area including the vicinity of the entrance/exit of the vehicle 300 . In the figure, persons P10 to P30 are included in a target area A310. On the other hand, the person P40 is not included in the target area A310. Therefore, in the case of the example of FIG. 6, the counting unit 113 counts the number of people as 3.
　なお、車両３００において撮影装置３１０が上述のように構成されているのは、次の２つの理由による。すなわち１つ目の理由は、車両３００において元々防犯または防災を目的として乗降口付近に監視カメラが設置されることがある。情報処理装置１０はこのような防犯または防災を目的とした監視カメラの画像を取得して利用することにより、車両３００に新たにカメラを設置する必要がなくなり、情報処理システム１の構成を簡易にすることができる。２つめの理由は、車両３００の混雑度を判定する場合に、車両３００の全ての空間における混雑状況を把握してもよいが、乗降口付近の混雑状況を把握することにより、車両全体のおおよその混雑度が把握できる。以上の理由から、情報処理システム１においては、撮影装置３１０を車両３００の上部且つ乗降口付近に設置する。 The imaging device 310 in the vehicle 300 is configured as described above for the following two reasons. The first reason is that the vehicle 300 is originally equipped with a surveillance camera near the entrance/exit for the purpose of crime prevention or disaster prevention. The information processing apparatus 10 acquires and uses the images of the monitoring camera for the purpose of crime prevention or disaster prevention, thereby eliminating the need to install a new camera in the vehicle 300 and simplifying the configuration of the information processing system 1. can do. The second reason is that when determining the degree of congestion of the vehicle 300, it is possible to grasp the congestion situation in the entire space of the vehicle 300. It is possible to grasp the degree of congestion in For the above reasons, in the information processing system 1, the photographing device 310 is installed above the vehicle 300 and near the entrance/exit.
　図７は、実施の形態２にかかる混雑度を判定するための条件の例を示す図である。図７には、表Ｔ１０が示されている。表Ｔ１０は、混雑度１～４と、それぞれの混雑度に対応した判定のための条件が示されている。表Ｔ１０には判定のための条件の具体例として、対象領域の人数Ｎが示されている。混雑度１における対象領域の人数Ｎは０以上５未満である。混雑度２における対象領域の人数Ｎは５以上１０未満である。混雑度３における対象領域の人数Ｎは１０以上１４未満である。混雑度４における対象領域の人数Ｎは１４以上である。このように、混雑度判定部１１４は、人数が例えば第１値（５以上１０未満）の場合における第１混雑度（２）が、前記第１値より少ない第２値（０以上５未満）における第２混雑度（１）より大きくなるように混雑度を判定するものであってもよい。 FIG. 7 is a diagram showing an example of conditions for determining the degree of congestion according to the second embodiment. Table T10 is shown in FIG. Table T10 shows congestion degrees 1 to 4 and conditions for determination corresponding to each congestion degree. Table T10 shows the number of people N in the target area as a specific example of conditions for determination. The number of people N in the target area at the congestion degree of 1 is 0 or more and less than 5. The number of people N in the target area at the degree of congestion 2 is 5 or more and less than 10. The number of people N in the target area at the degree of congestion 3 is 10 or more and less than 14. The number of people N in the target area at the congestion degree of 4 is 14 or more. In this way, the congestion degree determination unit 114 determines that the first congestion degree (2) when the number of people is, for example, a first value (5 or more and less than 10) is a second value (0 or more and less than 5) that is less than the first value. The congestion degree may be determined so as to be larger than the second congestion degree (1) in .
　なお、混雑度の設定は、上述の例に限られない。図７に示す表Ｔ１０は、混雑度の判定のための条件として、対象領域の人数に加えて、人物間距離の標準偏差と、対象領域の設定と、が示されている。 　The setting of the degree of congestion is not limited to the above example. Table T10 shown in FIG. 7 shows, as conditions for determining the degree of congestion, the number of people in the target area, the standard deviation of the inter-person distance, and the setting of the target area.
　すなわち混雑度の判定において、例えば、混雑度判定部１１４は、対象領域における複数の人物の互いの距離である人物間距離を測定し、さらに人物間距離の統計値を算出し、この統計値を加味して混雑度を判定してもよい。例えば図６において、人物Ｐ１０と人物Ｐ２０と間は距離Ｄ１２である。また人物Ｐ２０と人物Ｐ３０と間は距離Ｄ２３である。人物Ｐ１０と人物Ｐ３０と間は距離Ｄ１３である。混雑度判定部１１４は、距離Ｄ１２、距離Ｄ２３および距離１３から、人物間距離の平均値や標準偏差を算出し、これらの値から混雑度を判定してもよい。このような手法を採用することにより、人物同士が密集している空間を含む場合には混雑度を比較的に高く判定できる。 That is, in determining the degree of congestion, for example, the congestion degree determination unit 114 measures inter-person distances, which are distances between a plurality of persons in the target area, calculates a statistic value of the inter-person distances, and calculates the statistic value. The degree of congestion may be determined by taking into consideration. For example, in FIG. 6, the distance D12 is between the person P10 and the person P20. A distance D23 is between the person P20 and the person P30. A distance D13 is between the person P10 and the person P30. The congestion degree determination unit 114 may calculate the average value and standard deviation of the inter-person distances from the distance D12, the distance D23, and the distance 13, and determine the congestion degree from these values. By adopting such a method, it is possible to determine a relatively high degree of congestion when a space in which people are crowded together is included.
　また混雑度の判定に際し、領域設定部１１２は、対象領域として、車両３００の乗降口付近を含む第１領域と、第１領域と異なる部分を含む第２領域とをそれぞれ設定でし得る。そして、混雑度判定部１１４は、この第１領域と第２領域とに異なる重みづけを設定したうえで、混雑度を判定してもよい。 Also, when determining the degree of congestion, the area setting unit 112 can set a first area including the vicinity of the entrance and exit of the vehicle 300 and a second area including a portion different from the first area as target areas. Then, the congestion degree determination unit 114 may determine the congestion degree after setting different weights for the first area and the second area.
　またその他にも、領域設定部１１２は、時間帯や車両３００の運行区間などに応じて領域の設定を行ってもよい。領域設定部１１２が複数の領域を設定する場合、複数の領域は互いに重なり合っていてもよいし、離れていてもよい。領域設定部１１２が設定する領域は、予め座標が設定されていてもよいし、画像を認識することにより設定されてもよい。 In addition, the area setting unit 112 may set the area according to the time zone, the operation section of the vehicle 300, and the like. When the region setting unit 112 sets a plurality of regions, the plurality of regions may overlap each other or may be separated from each other. The area set by the area setting unit 112 may have coordinates set in advance, or may be set by recognizing an image.
　図８は、実施の形態２にかかる画像の例を示す第１の図である。図８は、撮影装置３１０が撮影した第１画像Ｆ１０１である。第１画像Ｆ１０１は、右側ドア３０１Ｒおよび左側ドア３０１Ｌを含み、さらに床３０２および乗降口付近の座席３０３が含まれる。また撮影装置３１０は天井に設置されているため、第１画像Ｆ１０１は、車両３００の上部に設置されている手摺り３０４や車内広告３０５も含む。 FIG. 8 is a first diagram showing an example of an image according to the second embodiment. FIG. 8 shows a first image F101 captured by the imaging device 310. FIG. The first image F101 includes the right side door 301R and the left side door 301L, and further includes the floor 302 and the seat 303 near the entrance/exit. Further, since the photographing device 310 is installed on the ceiling, the first image F101 also includes the handrail 304 installed on the upper part of the vehicle 300 and the in-vehicle advertisement 305 .
　図８の第１画像Ｆ１０１において、太字の二点鎖線により示された３つの矩形は、左側からそれぞれ第１座席領域Ａ１０１、乗降口領域Ａ１０２および第２座席領域Ａ１０３である。第１座席領域Ａ１０１は、座席３０３、手摺り３０４および車内広告３０５の画像を含む。乗降口領域Ａ１０２は主に、床３０２、右側ドア３０１Ｒおよび左側ドア３０１Ｌの画像を含む。第２座席領域Ａ１０３は、床３０２、座席３０３および手摺り３０４を含む。 In the first image F101 of FIG. 8, the three rectangles indicated by the bold two-dot chain lines are the first seat area A101, the entrance/exit area A102, and the second seat area A103 from the left. The first seating area A101 includes images of seats 303, handrails 304 and in-car advertisements 305. The entrance/exit area A102 mainly includes images of the floor 302, the right door 301R and the left door 301L. The second seating area A103 includes a floor 302, a seat 303 and handrails 304.
　図８に示す例において、情報処理装置１０の領域設定部１１２は、上述のように、第１画像Ｆ１０１を、３つの領域に分割する。そして、カウント部１１３は、分割した領域の内の乗降口領域Ａ１０２内に存在する人物の頭部を認識してカウントする。 In the example shown in FIG. 8, the region setting unit 112 of the information processing device 10 divides the first image F101 into three regions as described above. Then, the counting unit 113 recognizes and counts the heads of persons existing in the entrance/exit area A102 in the divided area.
　次に、図９を参照して領域の設定についてさらに説明する。図９は、実施の形態２にかかる画像の例を示す第２の図である。図９には、第２画像Ｆ１０２が示されている。第２画像Ｆ１０２は、領域の設定が、図８に示した第１画像Ｆ１０１と異なる。 Next, setting the area will be further described with reference to FIG. FIG. 9 is a second diagram illustrating an example of an image according to the second embodiment; FIG. 9 shows the second image F102. The second image F102 differs from the first image F101 shown in FIG. 8 in the area setting.
　図９において、第１座席領域Ａ１０１の内側には、太字の点線により示された広告領域Ａ１０６が示されている。広告領域Ａ１０６は画像の殆どの領域に車内広告が写り込んでいる。乗降口領域Ａ１０２の内側には、太字の点線により示された右側ドア領域Ａ１０４と、左側ドア領域Ａ１０５とが示されている。右側ドア領域Ａ１０４は、右側ドア３０１Ｒの画像を含み、右側ドア３０１Ｒから車両３００の中央に向かって７０センチメートル程度の幅を有する。左側ドア領域Ａ１０５は、左側ドア３０１Ｌの画像を含み、左側ドア３０１Ｌから車両３００の中央に向かって７０センチメートル程度の幅を有する。 In FIG. 9, an advertising area A106 indicated by a bold dotted line is shown inside the first seating area A101. In the advertisement area A106, the in-vehicle advertisement is reflected in most areas of the image. Inside the entrance/exit area A102, a right door area A104 and a left door area A105 indicated by bold dotted lines are shown. The right door area A104 includes an image of the right door 301R and has a width of about 70 centimeters from the right door 301R toward the center of the vehicle 300. As shown in FIG. The left door area A105 includes an image of the left door 301L and has a width of about 70 centimeters from the left door 301L toward the center of the vehicle 300. FIG.
　図９に示す例において、領域設定部１１２は、対象領域として、乗降口領域Ａ１０２に加えて、右側ドア領域Ａ１０４および左側ドア領域Ａ１０５を設定する。そしてカウント部１１３は、乗降口領域Ａ１０２における人物をカウントするとともに、右側ドア領域Ａ１０４および左側ドア領域Ａ１０５における人物をそれぞれカウントする。そして混雑度判定部１１４は、乗降口領域Ａ１０２、右側ドア領域Ａ１０４および左側ドア領域Ａ１０５のそれぞれの数から混雑度を判定する。混雑度判定部１１４は、乗降口領域Ａ１０２における人物の数が例えばＮ２であった場合に、右側ドア領域Ａ１０４および左側ドア領域Ａ１０５における人物の数が比較的に多い状態の方が、右側ドア領域Ａ１０４および左側ドア領域Ａ１０５における人物の数が比較的に少ない状態に比べて混雑度を高いと判定する。 In the example shown in FIG. 9, the area setting unit 112 sets a right door area A104 and a left door area A105 in addition to the entrance/exit area A102 as target areas. The counting unit 113 counts the number of people in the entrance/exit area A102, and counts the number of people in the right door area A104 and the left door area A105. Then, the congestion degree determination unit 114 determines the congestion degree from each number of the entrance/exit area A102, the right door area A104, and the left door area A105. When the number of people in the entrance/exit area A102 is, for example, N2, the congestion degree determination unit 114 determines that the number of people in the right door area A104 and the left door area A105 is relatively large. It is determined that the degree of congestion is high compared to the state in which the number of people in A104 and left door area A105 is relatively small.
　情報処理装置１０は、上述の例の他にも様々な手法により混雑度を判定できる。例えばカウント部１１３は、時間帯や運行状況により、第１座席領域Ａ１０１や第２座席領域Ａ１０３の人物の数をカウントしてもよい。この場合に、カウント部１１３は、広告領域Ａ１０６をカウントの対象領域から除外することができる。車内広告は様々なイラストや写真等が掲載され得る。そのため、車内広告に人物の頭部が表示されていた場合には、カウント部１１３が誤検出してしまう虞がある。そのため、予め広告領域Ａ１０６を対象領域から除外することにより、情報処理装置１０は混雑度の判定制度の低下を抑制できる。なお、広告領域は予め設定されていてもよいし、領域設定部１１２が広告の有無を自動判別することにより設定してもよい。 The information processing device 10 can determine the degree of congestion by various methods other than the above example. For example, the counting unit 113 may count the number of people in the first seating area A101 or the second seating area A103 depending on the time period and operation status. In this case, the counting unit 113 can exclude the advertisement area A106 from the target areas for counting. In-car advertisements can include various illustrations, photographs, and the like. Therefore, when a person's head is displayed in an in-vehicle advertisement, the counting unit 113 may erroneously detect it. Therefore, by preliminarily excluding the advertising area A106 from the target area, the information processing apparatus 10 can suppress deterioration of the congestion degree determination system. Note that the advertisement area may be set in advance, or may be set by the area setting unit 112 automatically determining whether or not there is an advertisement.
　カウント部１１３は、車両３００が駅に停止してドアを開いているタイミングで車両３００に出入りしている人物のカウントを行ってもよい。この場合、カウント部１１３は例えば、人物の顔の向きを検出し、車両に乗り込む方向に向いている人物を加算し、車両から降りる方向に向いている人物を減算する。このような構成により情報処理装置１０は人物が乗降中であっても混雑度の判定を行うことができる。 The counting unit 113 may count the number of people entering and exiting the vehicle 300 at the timing when the vehicle 300 stops at the station and the doors are open. In this case, for example, the counting unit 113 detects the orientation of the face of the person, adds the person facing the direction of getting into the vehicle, and subtracts the person facing the direction of getting out of the vehicle. With such a configuration, the information processing apparatus 10 can determine the degree of congestion even when a person is getting on and off the vehicle.
　以上、実施の形態２について説明した。実施の形態２にかかる情報処理システム１または情報処理装置１０によれば、簡易な構成で精度よく混雑度を判定する情報処理装置等を提供することができる。 The second embodiment has been described above. According to the information processing system 1 or the information processing device 10 according to the second embodiment, it is possible to provide an information processing device or the like that accurately determines the degree of congestion with a simple configuration.
　＜ハードウェア構成の例＞
　以下、本開示における情報処理装置の各機能構成がハードウェアとソフトウェアとの組み合わせで実現される場合の例について説明する。 <Example of hardware configuration>
An example in which each functional configuration of the information processing apparatus according to the present disclosure is realized by a combination of hardware and software will be described below.
　図１０は、コンピュータのハードウェア構成を例示するブロック図である。本開示における情報処理装置は、図に示すハードウェア構成を含むコンピュータ５００により上述の機能を実現できる。コンピュータ５００は、スマートフォンやタブレット端末などといった可搬型のコンピュータであってもよいし、ＰＣなどの据え置き型のコンピュータであってもよい。コンピュータ５００は、各装置を実現するために設計された専用のコンピュータであってもよいし、汎用のコンピュータであってもよい。コンピュータ５００は、所定のアプリケーションをインストールされることにより、所望の機能を実現できる。 FIG. 10 is a block diagram illustrating the hardware configuration of a computer. The information processing apparatus according to the present disclosure can implement the functions described above using a computer 500 including the hardware configuration shown in the drawing. The computer 500 may be a portable computer such as a smart phone or a tablet terminal, or may be a stationary computer such as a PC. Computer 500 may be a dedicated computer designed to implement each device, or may be a general-purpose computer. The computer 500 can implement desired functions by installing predetermined applications.
　コンピュータ５００は、バス５０２、プロセッサ５０４、メモリ５０６、ストレージデバイス５０８、入出力インタフェース（Ｉ／Ｆ）５１０およびネットワークインタフェース（Ｉ／Ｆ）５１２を有する。バス５０２は、プロセッサ５０４、メモリ５０６、ストレージデバイス５０８、入出力インタフェース５１０、及びネットワークインタフェース５１２が、相互にデータを送受信するためのデータ伝送路である。ただし、プロセッサ５０４などを互いに接続する方法は、バス接続に限定されない。 Computer 500 has bus 502 , processor 504 , memory 506 , storage device 508 , input/output interface (I/F) 510 and network interface (I/F) 512 . The bus 502 is a data transmission path through which the processor 504, memory 506, storage device 508, input/output interface 510, and network interface 512 exchange data with each other. However, the method of connecting the processors 504 and the like to each other is not limited to bus connection.
　プロセッサ５０４は、ＣＰＵ、ＧＰＵまたはＦＰＧＡなどの種々のプロセッサである。メモリ５０６は、ＲＡＭ（Random Access Memory）などを用いて実現される主記憶装置である。 The processor 504 is various processors such as CPU, GPU or FPGA. The memory 506 is a main memory implemented using a RAM (Random Access Memory) or the like.
　ストレージデバイス５０８は、ハードディスク、ＳＳＤ、メモリカード、又はＲＯＭ（Read Only Memory）などを用いて実現される補助記憶装置である。ストレージデバイス５０８は、所望の機能を実現するためのプログラムが格納されている。プロセッサ５０４は、このプログラムをメモリ５０６に読み出して実行することで、各装置の各機能構成部を実現する。 The storage device 508 is an auxiliary storage device realized using a hard disk, SSD, memory card, ROM (Read Only Memory), or the like. The storage device 508 stores programs for realizing desired functions. The processor 504 reads this program into the memory 506 and executes it, thereby realizing each functional component of each device.
　入出力インタフェース５１０は、コンピュータ５００と入出力デバイスとを接続するためのインタフェースである。例えば入出力インタフェース５１０には、キーボードなどの入力装置や、ディスプレイ装置などの出力装置が接続される。ネットワークインタフェース５１２は、コンピュータ５００をネットワークに接続するためのインタフェースである。 The input/output interface 510 is an interface for connecting the computer 500 and input/output devices. For example, the input/output interface 510 is connected to an input device such as a keyboard and an output device such as a display device. A network interface 512 is an interface for connecting the computer 500 to a network.
　以上、本開示における情報処理装置の各機能構成がハードウェアとソフトウェアとの組み合わせで実現される場合の例について説明した。 An example in which each functional configuration of the information processing apparatus according to the present disclosure is realized by a combination of hardware and software has been described above.
　なお、本発明は上記実施の形態に限られたものではなく、趣旨を逸脱しない範囲で適宜変更することが可能である。 It should be noted that the present invention is not limited to the above embodiments, and can be modified as appropriate without departing from the scope of the invention.
　プログラムは、コンピュータに読み込まれた場合に、実施形態で説明された１又はそれ以上の機能をコンピュータに行わせるための命令群（又はソフトウェアコード）を含む。プログラムは、非一時的なコンピュータ可読媒体又は実体のある記憶媒体に格納されてもよい。限定ではなく例として、コンピュータ可読媒体又は実体のある記憶媒体は、random-access memory（RAM）、read-only memory（ROM）、フラッシュメモリ、solid-state drive（SSD）又はその他のメモリ技術、CD-ROM、digital versatile disc（DVD）、Blu-ray（登録商標）ディスク又はその他の光ディスクストレージ、磁気カセット、磁気テープ、磁気ディスクストレージ又はその他の磁気ストレージデバイスを含む。プログラムは、一時的なコンピュータ可読媒体又は通信媒体上で送信されてもよい。限定ではなく例として、一時的なコンピュータ可読媒体又は通信媒体は、電気的、光学的、音響的、またはその他の形式の伝搬信号を含む。 A program includes a set of instructions (or software code) that, when read into a computer, cause the computer to perform one or more of the functions described in the embodiments. The program may be stored in a non-transitory computer-readable medium or tangible storage medium. By way of example, and not limitation, computer readable media or tangible storage media may include random-access memory (RAM), read-only memory (ROM), flash memory, solid-state drives (SSD) or other memory technology, CDs - ROM, digital versatile disc (DVD), Blu-ray disc or other optical disc storage, magnetic cassette, magnetic tape, magnetic disc storage or other magnetic storage device. The program may be transmitted on a transitory computer-readable medium or communication medium. By way of example, and not limitation, transitory computer readable media or communication media include electrical, optical, acoustic, or other forms of propagated signals.
　この出願は、２０２１年２月４日に出願された日本出願特願２０２１－０１６９６８を基礎とする優先権を主張し、その開示の全てをここに取り込む。 This application claims priority based on Japanese Patent Application No. 2021-016968 filed on February 4, 2021, and the entire disclosure thereof is incorporated herein.
　１　情報処理システム
　１０　情報処理装置
　１１１　画像データ取得部
　１１２　領域設定部
　１１３　カウント部
　１１４　混雑度判定部
　１１５　出力部
　３００　車両
　３０１Ｒ　右側ドア
　３０１Ｌ　左側ドア
　３０２　床
　３０３　座席
　３０４　手摺り
　３０５　車内広告
　３１０　撮影装置
　３１１　カメラ
　３１２　通信部
　３１３　制御部
　３２０　記憶部
　４００　情報提供装置
　４１１　混雑度取得部
　４１２　提供情報生成部
　４１３　通信部
　４１４　制御部
　４２０　記憶部
　５００　コンピュータ
　５０２　バス
　５０４　プロセッサ
　５０６　メモリ
　５０８　ストレージデバイス
　５１０　出入力Ｉ／Ｆ
　５１２　ネットワークＩ／Ｆ
　９００　ユーザ端末 1 information processing system 10 information processing device 111 image data acquisition unit 112 area setting unit 113 counting unit 114 congestion degree determination unit 115 output unit 300 vehicle 301R right side door 301L left side door 302 floor 303 seat 304 handrail 305 car advertisement 310 photographing device 311 camera 312 communication unit 313 control unit 320 storage unit 400 information providing device 411 congestion level acquisition unit 412 provision information generation unit 413 communication unit 414 control unit 420 storage unit 500 computer 502 bus 504 processor 506 memory 508 storage device 510 input/output I/F
512 network I/F
900 user terminal

Claims (10)

  1. 　車両の内部を撮影するカメラが生成した画像データを取得する画像データ取得手段と、
    　前記画像データにかかる画像を複数の領域に分割する領域設定手段と、
    　複数の前記領域のうちの対象領域に存在する人物の数をカウントするカウント手段と、
    　前記人物の数に基づいて前記車両の混雑度を判定する混雑度判定手段と、
    　前記混雑度に関する情報を出力する出力手段と、を備える
    情報処理装置。     image data acquisition means for acquiring image data generated by a camera that captures the interior of the vehicle;
    an area setting means for dividing an image corresponding to the image data into a plurality of areas;
    counting means for counting the number of persons existing in a target area among the plurality of areas;
    congestion level determination means for determining the congestion level of the vehicle based on the number of people;
    An information processing apparatus comprising output means for outputting information about the degree of congestion.
  2. 　前記画像データ取得手段は、前記車両の上部に設置された前記カメラが前記人物を俯瞰するように撮影した前記画像にかかる前記画像データを取得する、
    請求項１に記載の情報処理装置。     The image data acquisition means acquires the image data related to the image captured by the camera installed on the upper part of the vehicle so as to look down on the person.
    The information processing device according to claim 1 .
  3. 　前記画像データ取得手段は、前記車両の乗降口を含む前記画像にかかる前記画像データを取得する、
    請求項１または２に記載の情報処理装置。     The image data acquisition means acquires the image data related to the image including the entrance/exit of the vehicle.
    The information processing apparatus according to claim 1 or 2.
  4. 　前記領域設定手段は、前記車両の乗降口付近を含む前記画像を前記対象領域に設定する、
    請求項１～３のいずれか一項に記載の情報処理装置。     The area setting means sets the image including the vicinity of the entrance/exit of the vehicle as the target area.
    The information processing apparatus according to any one of claims 1 to 3.
  5. 　前記カウント手段は、前記人物の頭部を認識し、前記対象領域において認識した前記頭部の数をカウントする、
    請求項１～４のいずれか一項に記載の情報処理装置。     The counting means recognizes the head of the person and counts the number of the recognized heads in the target area.
    The information processing apparatus according to any one of claims 1 to 4.
  6. 　前記混雑度判定手段は、前記人物の数が第１値の場合における第１混雑度が、前記第１値より少ない第２値における第２混雑度より大きくなるように前記混雑度を判定する、
    請求項１～５のいずれか一項に記載の情報処理装置。     The congestion level determination means determines the congestion level such that a first congestion level when the number of people is a first value is greater than a second congestion level when the number of people is a second value smaller than the first value.
    The information processing apparatus according to any one of claims 1 to 5.
  7. 　前記混雑度判定手段は、前記対象領域における複数の前記人物の互いの距離である人物間距離の統計値に基づいて前記混雑度を判定する、
    請求項１～５のいずれか一項に記載の情報処理装置。     The congestion degree determination means determines the congestion degree based on a statistical value of inter-person distances, which are distances between the plurality of persons in the target area.
    The information processing apparatus according to any one of claims 1 to 5.
  8. 　前記領域設定手段は、前記対象領域として、前記車両の乗降口付近を含む第１領域と、前記第１領域と異なる部分を含む第２領域とをそれぞれ設定し、
    前記混雑度判定手段は、前記第１領域と前記第２領域とに異なる重みづけを設定したうえで前記混雑度を判定する、
    請求項１～５のいずれか一項に記載の情報処理装置。     The region setting means sets, as the target regions, a first region including a vicinity of the entrance and exit of the vehicle and a second region including a portion different from the first region, and
    The congestion degree determination means determines the congestion degree after setting different weights for the first area and the second area.
    The information processing apparatus according to any one of claims 1 to 5.
  9. 　コンピュータが、
    　車両の内部を撮影するカメラが生成した画像データを取得し、
    　前記画像データにかかる画像を複数の領域に分割し、
    　複数の前記領域のうちの対象領域に存在する人物の数をカウントし、
    　前記人物の数に基づいて前記車両の混雑度を判定し、
    　前記混雑度に関する情報を出力する、
    情報処理方法。     the computer
    Acquire image data generated by a camera that captures the interior of the vehicle,
    dividing an image corresponding to the image data into a plurality of regions;
    Counting the number of people present in the target area of the plurality of areas;
    Determining the degree of congestion of the vehicle based on the number of people,
    outputting information about the degree of congestion;
    Information processing methods.
  10. 　車両の内部を撮影するカメラが生成した画像データを取得し、
    　前記画像データにかかる画像を複数の領域に分割し、
    　複数の前記領域のうちの対象領域に存在する人物の数をカウントし、
    　前記人物の数に基づいて前記車両の混雑度を判定し、
    　前記混雑度に関する情報を出力する、
    情報処理方法を、コンピュータに実行させる
    プログラムが格納された非一時的なコンピュータ可読媒体。     Acquire image data generated by a camera that captures the interior of the vehicle,
    dividing an image corresponding to the image data into a plurality of regions;
    Counting the number of people present in the target area of the plurality of areas;
    Determining the degree of congestion of the vehicle based on the number of people,
    outputting information about the degree of congestion;
    A non-transitory computer-readable medium storing a program for causing a computer to execute an information processing method.
PCT/JP2021/042464 2021-02-04 2021-11-18 Information processing device, information processing method, and computer-readable medium WO2022168402A1 (en)

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Citations (5)

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JP2007290574A (en) * 2006-04-26 2007-11-08 Mitsubishi Electric Corp Train congestion factor notification system
KR20100114294A (en) * 2009-04-15 2010-10-25 김철수 A system for informing crowdedness of subway
JP2018042049A (en) * 2016-09-06 2018-03-15 パナソニックＩｐマネジメント株式会社 Apparatus, system and method for congestion detection
JP2020149710A (en) * 2014-06-30 2020-09-17 日本電気株式会社 Guidance system, guidance method, and program
JP2021003972A (en) * 2019-06-26 2021-01-14 株式会社東芝 Information processor, station management system, station management equipment and program

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2007290574A (en) * 2006-04-26 2007-11-08 Mitsubishi Electric Corp Train congestion factor notification system
KR20100114294A (en) * 2009-04-15 2010-10-25 김철수 A system for informing crowdedness of subway
JP2020149710A (en) * 2014-06-30 2020-09-17 日本電気株式会社 Guidance system, guidance method, and program
JP2018042049A (en) * 2016-09-06 2018-03-15 パナソニックＩｐマネジメント株式会社 Apparatus, system and method for congestion detection
JP2021003972A (en) * 2019-06-26 2021-01-14 株式会社東芝 Information processor, station management system, station management equipment and program

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