WO2023286569A1

WO2023286569A1 - Congestion estimating system

Info

Publication number: WO2023286569A1
Application number: PCT/JP2022/025346
Authority: WO
Inventors: 隆太郎久田; 幹生岩村; 亮介倉地; 雅之横尾; 文紀新清; けい石黒; 健吾松本
Original assignee: 株式会社Ｎｔｔドコモ
Priority date: 2021-07-15
Filing date: 2022-06-24
Publication date: 2023-01-19
Also published as: JPWO2023286569A1

Abstract

The objective of the present invention is to estimate congestion in an estimation target location more simply and appropriately.　A congestion estimating system 10 comprises: an image acquiring unit 11 for acquiring an image to be used to estimate congestion; an imaging information acquiring unit 12 for acquiring, on the basis of the acquired image, imaging information indicating a position and imaging direction, at the time the image was captured, of an imaging device that captured the image; a number-of-persons detecting unit 13 for detecting, from the image, the number of persons appearing in the image; and a congestion estimating unit 14 for determining, from the acquired imaging information, a location that is to serve as a congestion estimation target, and estimating the congestion from the detected number of persons, for the determined location.

Description

Congestion estimation system

The present invention relates to a congestion level estimation system for estimating the congestion level of an estimation target location.

Conventionally, it has been proposed to detect a person in an image taken by an imaging device such as a camera and estimate the degree of congestion in the place where the image was taken (see Patent Document 1, for example).

JP 2018-148422 A

In the conventional method disclosed in Patent Document 1, the degree of congestion is estimated using an image captured by an imaging device that is fixedly installed in advance at the place where the degree of congestion is to be estimated. For this reason, it is necessary to preliminarily provide an imaging device in a fixed location at a place where the degree of congestion is to be estimated. As the number of locations for which the degree of congestion is estimated increases, large costs and labor are required.

An embodiment of the present invention has been made in view of the above, and aims to provide a congestion degree estimation system that can more easily and appropriately estimate the congestion degree of an estimation target location.

In order to achieve the above object, a congestion degree estimation system according to an embodiment of the present invention includes an image acquisition unit that acquires an image used for estimating a congestion degree, and based on the image acquired by the image acquisition unit: , an imaging information acquisition unit that acquires imaging information indicating the imaging position and imaging direction of the image of the imaging device that captured the image; A location for which a congestion degree is to be estimated is specified from the number of people detection unit to be detected and the imaging information acquired by the imaging information acquisition unit, and the congestion degree is estimated from the number of people detected by the people detection unit for the specified location. and a congestion degree estimating unit.

In the congestion level estimation system according to one embodiment of the present invention, a place whose congestion level is to be estimated is specified from the acquired image, and the congestion level is estimated for the specified place. Therefore, an image captured by an image capturing device other than the image capturing device that is fixedly provided in advance, for example, an image captured by an image capturing device carried by a user at the location where the congestion level is to be estimated is used to calculate the congestion degree. can be estimated. In addition, since the imaging information indicating the position and imaging direction of the image at the time of imaging is acquired based on the image, and the location for which the degree of congestion is to be estimated is specified, the location can be appropriately specified. Therefore, according to the congestion degree estimation system according to one embodiment of the present invention, it is possible to more easily and appropriately estimate the congestion degree of the place to be estimated.

According to one embodiment of the present invention, it is possible to more easily and appropriately estimate the congestion degree of the estimation target location.

It is a figure which shows the structure of the congestion degree estimation system which concerns on embodiment of this invention. It is a flowchart which shows the process performed by the congestion degree estimation system which concerns on embodiment of this invention. It is a figure which shows the hardware constitutions of the congestion degree estimation system which concerns on embodiment of this invention.

Hereinafter, an embodiment of the congestion degree estimation system according to the present invention will be described in detail along with the drawings. In the description of the drawings, the same elements are denoted by the same reference numerals, and overlapping descriptions are omitted.

FIG. 1 shows a congestion degree estimation system 10 according to this embodiment. The congestion degree estimation system 10 is a system (apparatus) for estimating the congestion degree of a predetermined place. The degree of congestion indicates the degree of human congestion (how many people are in the location) at the location to be estimated. For example, the congestion degree estimation system 10 estimates the congestion degree in buildings such as commercial facilities. In this case, the inside of the building is divided into a plurality of areas (sections, measurement points), and each of the plurality of areas is set as a place to be estimated. Each of the plurality of regions may have, for example, a mesh-like shape. Each of the plurality of regions corresponds, for example, to individual sales floors within the commercial facility. The congestion degree estimation system 10 manages and outputs information indicating the estimated congestion degree. Information indicating the degree of congestion is output, for example, so that it can be referred to by a person who has visited the place to be estimated. By referring to the estimated degree of congestion, it is possible to grasp which parts of the commercial facility are crowded and which parts are vacant. It should be noted that the location for which the degree of congestion is to be estimated is not limited to the inside of the building such as the above-mentioned commercial facility.

The congestion degree estimation system 10 is configured by a computer such as a PC (personal computer) or a server device. The congestion degree estimation system 10 may be configured by a plurality of computers, that is, computer systems. The congestion degree estimation system 10 has a communication function, and can exchange information with other devices.

The congestion degree estimation system 10 estimates the degree of congestion using images (camera images) captured by the terminal 20 at locations targeted for estimation of the degree of congestion. The terminal 20 is a device that is carried and used by a user, and is, for example, a mobile communication terminal such as a smart phone. Alternatively, the terminal 20 may be a device worn by the user, such as AR (Augmented Reality) glasses (in this case, the terminal 20 is worn on the user's head, specifically on the eyes). good. Note that although only one terminal 20 is illustrated in FIG. 2, a plurality of terminals 20 that are used by a plurality of users may be used to estimate the degree of congestion.

The terminal 20 is equipped with an imaging device. The imaging device may be an existing one, for example, a camera normally provided in a smartphone or the like. The terminal 20 obtains an image by capturing an image using the image capturing function at the place whose congestion degree is to be estimated. For example, the terminal 20 captures an image at a location whose congestion degree is to be estimated at regular intervals (for example, every few minutes). Also, the image obtained by imaging may be a moving image.

The terminal 20 has a communication function and can exchange information with the congestion degree estimation system 10 . The communication function may be an existing one. The terminal 20 transmits the captured image to the congestion degree estimation system 10 . The transmission is performed, for example, each time imaging is performed.

Next, the functions of the congestion degree estimation system 10 according to this embodiment will be explained. As shown in FIG. 1, the congestion degree estimation system 10 includes an image acquisition unit 11, an imaging information acquisition unit 12, a people detection unit 13, and a congestion degree estimation unit .

The image acquisition unit 11 is a functional unit that acquires an image used for estimating the degree of congestion. For example, the image acquisition unit 11 receives an image transmitted from the terminal 20 and acquires the image. Also, the image acquisition unit 11 may acquire an image by a method other than the above. The image acquisition unit 11 outputs the acquired image to the imaging information acquisition unit 12 and the number detection unit 13 .

Based on the image acquired by the image acquisition unit 11, the imaging information acquisition unit 12 acquires imaging information indicating the position and imaging direction of the image of the imaging device (that is, the terminal 20) that captured the image. It is a functional part that The imaging information acquisition unit 12 may acquire information indicating the three-dimensional position in the building as the information indicating the position at the time of imaging. When the terminal 20 is a device worn by the user, such as AR glasses, and the imaging device provided in the terminal 20 captures the line-of-sight direction of the user wearing the terminal 20, the above-mentioned imaging direction is the line-of-sight direction of the user. becomes.

Among the acquired imaging information, the information indicating the position of the terminal 20 at the time of imaging is, for example, the coordinates (three-dimensional position) of a three-dimensional coordinate system defined in advance in a building such as a commercial facility for estimating the degree of congestion. This is the information shown. Among the acquired imaging information, the information indicating the imaging direction is, for example, information indicating an absolute angle (azimuth) with respect to the north direction. However, the imaging information to be acquired may be information other than the above as long as it is acquired based on an image and indicates the position and imaging direction of the terminal 20 at the time of imaging.

For example, the imaging information acquisition unit 12 acquires imaging information as follows. The imaging information acquisition unit 12 inputs an image from the image acquisition unit 11 . The imaging information acquisition unit 12 acquires imaging information based on the image input from the image acquisition unit 11 using existing technology. For example, the imaging information acquisition unit 12 stores in advance the information indicating the position and direction and the information related to the image such as the feature points in association with each other. The imaging information acquisition unit 12 extracts information related to the input image, such as feature points of the image input from the image acquisition unit 11 . The imaging information acquisition unit 12 collates the extracted feature points and the like with information related to the image such as the stored feature points. The imaging information acquisition unit 12 calculates and acquires imaging information related to the image input from the image acquisition unit 11 based on the stored information of the correspondence and the collation result. In this manner, the imaging information acquisition unit 12 may acquire imaging information by the self-location recognition function from the image.

In addition, the imaging information acquisition unit 12 may acquire imaging information using an external function of the congestion degree estimation system 10 . For example, the imaging information acquisition unit 12 may transmit an image to an external server (external service) that calculates imaging information from the image, and acquire imaging information calculated from the image by the external server. An external server may be, for example, one provided by GCA or Immersal.

Also, the imaging information acquisition unit 12 may acquire imaging information based on an image by a method other than the above. The imaging information acquisition unit 12 outputs the acquired imaging information to the congestion degree estimation unit 14 .

The number detection unit 13 is a functional unit that detects the number of people in the image acquired by the image acquisition unit 11 . The number detection unit 13 receives an image from the image acquisition unit 11 . The number-of-people detection unit 13 detects the number of people in the image input from the image acquisition unit 11 by using an existing image recognition technique or the like. The number detection unit 13 outputs information indicating the detected number of people to the congestion degree estimation unit 14 . Note that the imaging information acquired by the imaging information acquisition unit 12 and the number of people detected by the people detection unit 13 from the same image are associated with each other.

The congestion degree estimation unit 14 identifies a location whose congestion degree is to be estimated from the imaging information acquired by the imaging information acquisition unit 12, and estimates the congestion degree of the identified location from the number of people detected by the people detection unit 13. It is a functional part that The congestion level estimating unit 14 may specify any one of a plurality of areas obtained by dividing a building as a location for which the congestion level is to be estimated. The congestion degree estimation unit 14 may estimate the congestion degree from the number of people detected from each of the plurality of images by the people detection unit 13 for the same place.

The congestion degree estimation unit 14 receives imaging information from the imaging information acquisition unit 12 . The congestion degree estimation unit 14 inputs information indicating the number of people detected by the number detection unit 13 . For example, the congestion degree estimating unit 14 estimates the congestion degree as follows, using imaging information obtained from the same image and information indicating the number of people.

The congestion degree estimation unit 14 identifies, from the imaging information, the position appearing in the image related to the imaging information. When the terminal 20 is a device worn by the user, such as AR glasses, and the imaging device provided in the terminal 20 captures the line-of-sight direction of the user wearing the terminal 20, the position captured in the image corresponds to the visual field of the user. It becomes the position of the range. For example, the congestion degree estimating unit 14 determines a position a preset distance (for example, several meters) in the imaging direction indicated by the imaging information from the position at the time of imaging of the terminal 20 indicated by the imaging information. Identify the position in the image.

The congestion degree estimation unit 14 stores in advance information indicating the position of each area whose congestion degree is to be estimated in the same coordinate system as the position of the terminal 20 at the time of image capture indicated by the image information. The congestion degree estimating unit 14 determines an area including the identified position based on the pre-stored position of each area whose congestion degree is to be estimated. The congestion degree estimating unit 14 uses the area determined to include the identified position as an area for estimating the congestion degree from the number of people detected by the number of people detecting unit 13 . The congestion degree estimation unit 14 may use the number of people detected by the number detection unit 13 as the congestion degree of the area. Alternatively, the congestion degree estimating unit 14 may store a formula or condition for estimating the congestion degree from the number of people, and estimate the congestion degree of the area based on the formula or condition. At this time, the estimated degree of congestion may be, for example, a numerical value indicating the degree of congestion, or may be a qualitative degree of congestion (for example, whether the degree of congestion is large, medium, or small). .

The congestion degree estimation unit 14 may store map data indicating the position of the area and associate the estimated congestion degree with the map. That is, the congestion degree estimation unit 14 may plot the congestion degree such as the number of people on the map.

The congestion degree estimating unit 14 determines that when the congestion degree has already been estimated in the region specified as the region for which the congestion degree is to be estimated from the imaging information, that is, when the region already has information indicating the number of people (information indicating the number of people is overlap), the congestion degree of the area may be estimated from the information indicating the existing number of people and the information indicating the new number of people. For example, the congestion level estimation unit 14 may use the average of these numbers as the congestion level. In this manner, the congestion level estimation unit 14 may estimate the congestion level by adjusting the number of people detected by the people detection unit 13 from each of the plurality of images for the same location.

In order to keep the provided congestion degree fresh, the congestion degree estimating unit 14 resets the congestion degree for each region at regular intervals (for example, every few minutes), and calculates the number of people acquired within a certain interval. A new congestion degree may be calculated using only the indicated information.

The congestion degree estimation unit 14 outputs information indicating the estimated congestion degree for each area. For example, the congestion degree estimation unit 14 may transmit information indicating the estimated congestion degree for each region to the terminal 20 . Alternatively, the congestion degree estimation unit 14 may transmit information indicating the estimated congestion degree of each area to a display device such as a digital signage installed in a building such as a commercial facility where the congestion degree is estimated. By displaying information indicating the degree of congestion for each area on these devices that have received the information, a person in the building can grasp the degree of congestion for each area. The above transmission may be performed upon request or at fixed time intervals. In addition, the congestion degree estimation unit 14 may output information indicating the estimated congestion degree of each region to an output destination other than the above by a method other than the above. The functions of the congestion degree estimation system 10 according to the present embodiment have been described above.

Subsequently, the processing executed by the congestion degree estimation system 10 according to the present embodiment (operation method performed by the congestion degree estimation system 10) will be described using the flowchart of FIG. In this process, the image acquisition unit 11 acquires an image used for estimating the degree of congestion (S01). Subsequently, based on the image, the imaging information acquisition unit 12 acquires imaging information indicating the position and imaging direction of the image of the terminal 20 that captured the image (S02). Also, the number of people in the image is detected from the image by the number-of-people detection unit 13 (S03). Note that the imaging information acquisition processing (S02) by the imaging information acquisition unit 12 and the number detection processing (S03) by the people detection unit 13 can be performed independently of each other, so the order shown in FIG. does not need to be done in

Next, the congestion degree estimation unit 14 identifies a location whose congestion degree is to be estimated from the imaging information (S04). Subsequently, the congestion level estimation unit 14 estimates the congestion level of the specified place from the detected number of people (S05). Subsequently, information indicating the estimation result of the congestion degree is output by the congestion degree estimation unit 14 (S06). The above is the processing executed by the congestion degree estimation system 10 according to the present embodiment.

In this embodiment, from the acquired image, a place whose congestion level is to be estimated is specified, and the congestion level is estimated for the specified place. Therefore, an image captured by an imaging device other than an imaging device that is fixedly provided in advance, for example, an image captured by the terminal 20 carried by the user at the place where the congestion level is to be estimated as in the present embodiment. Images can be used to estimate congestion. In addition, imaging information indicating the position and imaging direction at the time of imaging of the image is obtained based on the image, and the location for which the degree of congestion is to be estimated is specified. Therefore, for example, even indoors where the position cannot be accurately estimated by GPS (Global Positioning System) or the like, the location can be appropriately identified. Therefore, according to the present embodiment, it is possible to more easily and appropriately estimate the congestion degree of the estimation target location.

Further, as in the above-described embodiment, information indicating a three-dimensional position in the building is obtained as information indicating the position at the time of imaging, and the area for which the building is divided into a plurality of areas is obtained as a target for estimating the degree of congestion. Any one may be specified. According to this configuration, it is possible to appropriately estimate the degree of congestion for each area even in a building such as a multi-story commercial facility, for example. However, it is not always necessary to adopt the above configuration in estimating the degree of congestion.

Also, as in the above-described embodiment, the degree of congestion may be estimated from the number of people detected from each of a plurality of images for the same location. For example, as described above, the number of people may be averaged. According to this configuration, it is possible to estimate the degree of congestion with high accuracy. However, the degree of congestion for the same place may be estimated from one image.

Some of the functional units described above that are provided in the congestion degree estimation system 10 may be provided in another device such as the terminal 20 . In that case, the congestion degree estimation system may include the other device.

It should be noted that the block diagrams used in the description of the above embodiments show blocks for each function. These functional blocks (components) are realized by any combination of at least one of hardware and software. Also, the method of implementing each functional block is not particularly limited. That is, each functional block may be implemented using one device that is physically or logically coupled, or directly or indirectly using two or more devices that are physically or logically separated (e.g. , wired, wireless, etc.) and may be implemented using these multiple devices. A functional block may be implemented by combining software in the one device or the plurality of devices.

Functions include judging, determining, determining, calculating, calculating, processing, deriving, investigating, searching, checking, receiving, transmitting, outputting, accessing, resolving, selecting, choosing, establishing, comparing, assuming, expecting, assuming, Broadcasting, notifying, communicating, forwarding, configuring, reconfiguring, allocating, mapping, assigning, etc. can't For example, a functional block (component) responsible for transmission is called a transmitting unit or transmitter. In either case, as described above, the implementation method is not particularly limited.

For example, the congestion degree estimation system 10 according to an embodiment of the present disclosure may function as a computer that performs information processing of the present disclosure. FIG. 3 is a diagram illustrating an example of a hardware configuration of congestion degree estimation system 10 according to an embodiment of the present disclosure. The congestion degree estimation system 10 described above may be physically configured as a computer device including a processor 1001, a memory 1002, a storage 1003, a communication device 1004, an input device 1005, an output device 1006, a bus 1007, and the like. Also, the hardware configuration of the terminal 20 may be the one described here.

In the following explanation, the term "apparatus" can be read as a circuit, device, unit, or the like. The hardware configuration of the congestion degree estimation system 10 may be configured to include one or more of each device shown in the figure, or may be configured without some of the devices.

Each function in the congestion degree estimation system 10 is performed by the processor 1001 by loading predetermined software (program) on hardware such as the processor 1001 and the memory 1002, and the processor 1001 performs calculations, controls communication by the communication device 1004, It is realized by controlling at least one of data reading and writing in the memory 1002 and the storage 1003 .

The processor 1001, for example, operates an operating system and controls the entire computer. The processor 1001 may be configured by a central processing unit (CPU) including an interface with peripheral devices, a control device, an arithmetic device, registers, and the like. For example, each function in congestion degree estimation system 10 described above may be implemented by processor 1001 .

Also, the processor 1001 reads programs (program codes), software modules, data, etc. from at least one of the storage 1003 and the communication device 1004 to the memory 1002, and executes various processes according to them. As the program, a program that causes a computer to execute at least part of the operations described in the above embodiments is used. For example, each function in congestion degree estimation system 10 may be implemented by a control program stored in memory 1002 and running on processor 1001 . Although it has been explained that the above-described various processes are executed by one processor 1001, they may be executed simultaneously or sequentially by two or more processors 1001. FIG. Processor 1001 may be implemented by one or more chips. Note that the program may be transmitted from a network via an electric communication line.

The memory 1002 is a computer-readable recording medium, and is composed of at least one of, for example, ROM (Read Only Memory), EPROM (Erasable Programmable ROM), EEPROM (Electrically Erasable Programmable ROM), RAM (Random Access Memory), etc. may be The memory 1002 may also be called a register, cache, main memory (main storage device), or the like. The memory 1002 can store executable programs (program code), software modules, etc. for performing information processing according to an embodiment of the present disclosure.

The storage 1003 is a computer-readable recording medium, for example, an optical disc such as a CD-ROM (Compact Disc ROM), a hard disk drive, a flexible disc, a magneto-optical disc (for example, a compact disc, a digital versatile disc, a Blu-ray disk), smart card, flash memory (eg, card, stick, key drive), floppy disk, magnetic strip, and/or the like. Storage 1003 may also be called an auxiliary storage device. The storage medium included in the congestion degree estimation system 10 may be, for example, a database including at least one of the memory 1002 and the storage 1003, a server, or other suitable medium.

The communication device 1004 is hardware (transmitting/receiving device) for communicating between computers via at least one of a wired network and a wireless network, and is also called a network device, a network controller, a network card, a communication module, or the like.

The input device 1005 is an input device (for example, keyboard, mouse, microphone, switch, button, sensor, etc.) that receives input from the outside. The output device 1006 is an output device (eg, display, speaker, LED lamp, etc.) that outputs to the outside. Note that the input device 1005 and the output device 1006 may be integrated (for example, a touch panel).

Each device such as the processor 1001 and the memory 1002 is connected by a bus 1007 for communicating information. The bus 1007 may be configured using a single bus, or may be configured using different buses between devices.

In addition, the congestion degree estimation system 10 includes hardware such as a microprocessor, a digital signal processor (DSP), an ASIC (Application Specific Integrated Circuit), a PLD (Programmable Logic Device), and an FPGA (Field Programmable Gate Array). part or all of each functional block may be implemented by the hardware. For example, processor 1001 may be implemented using at least one of these pieces of hardware.

The order of the processing procedures, sequences, flowcharts, etc. of each aspect/embodiment described in the present disclosure may be changed as long as there is no contradiction. For example, the methods described in this disclosure present elements of the various steps using a sample order, and are not limited to the specific order presented.

Input/output information may be stored in a specific location (for example, memory) or managed using a management table. Input/output information and the like can be overwritten, updated, or appended. The output information and the like may be deleted. The entered information and the like may be transmitted to another device.

The determination may be made by a value represented by one bit (0 or 1), by a true/false value (Boolean: true or false), or by numerical comparison (for example, a predetermined value).

Each aspect/embodiment described in the present disclosure may be used alone, may be used in combination, or may be used by switching along with execution. In addition, the notification of predetermined information (for example, notification of “being X”) is not limited to being performed explicitly, but may be performed implicitly (for example, not notifying the predetermined information). good too.

Although the present disclosure has been described in detail above, it is clear to those skilled in the art that the present disclosure is not limited to the embodiments described in the present disclosure. The present disclosure can be practiced with modifications and variations without departing from the spirit and scope of the present disclosure as defined by the claims. Accordingly, the description of the present disclosure is for illustrative purposes and is not meant to be limiting in any way.

Software, whether referred to as software, firmware, middleware, microcode, hardware description language or otherwise, includes instructions, instruction sets, code, code segments, program code, programs, subprograms, and software modules. , applications, software applications, software packages, routines, subroutines, objects, executables, threads of execution, procedures, functions, and the like.

In addition, software, instructions, information, etc. may be transmitted and received via a transmission medium. For example, the software uses at least one of wired technology (coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL), etc.) and wireless technology (infrared, microwave, etc.) to website, Wired and/or wireless technologies are included within the definition of transmission medium when sent from a server or other remote source.

The terms "system" and "network" used in this disclosure are used interchangeably.

In addition, the information, parameters, etc. described in the present disclosure may be expressed using absolute values, may be expressed using relative values from a predetermined value, or may be expressed using other corresponding information. may be represented.

The terms "determining" and "determining" used in this disclosure may encompass a wide variety of actions. "Judgement" and "determination" are, for example, judging, calculating, computing, processing, deriving, investigating, looking up, searching, inquiring (eg, lookup in a table, database, or other data structure), ascertaining as "judged" or "determined", and the like. Also, "judgment" and "determination" are used for receiving (e.g., receiving information), transmitting (e.g., transmitting information), input, output, access (accessing) (for example, accessing data in memory) may include deeming that a "judgment" or "decision" has been made. In addition, "judgment" and "decision" are considered to be "judgment" and "decision" by resolving, selecting, choosing, establishing, comparing, etc. can contain. In other words, "judgment" and "decision" may include considering that some action is "judgment" and "decision". Also, "judgment (decision)" may be read as "assuming", "expecting", "considering", or the like.

The terms "connected", "coupled", or any variation thereof, mean any direct or indirect connection or coupling between two or more elements, It can include the presence of one or more intermediate elements between two elements being "connected" or "coupled." Couplings or connections between elements may be physical, logical, or a combination thereof. For example, "connection" may be read as "access". As used in this disclosure, two elements are defined using at least one of one or more wires, cables, and printed electrical connections and, as some non-limiting and non-exhaustive examples, in the radio frequency domain. , electromagnetic energy having wavelengths in the microwave and optical (both visible and invisible) regions, and the like.

The term "based on" as used in this disclosure does not mean "based only on" unless otherwise specified. In other words, the phrase "based on" means both "based only on" and "based at least on."

Any reference to elements using the "first," "second," etc. designations used in this disclosure does not generally limit the quantity or order of those elements. These designations may be used in this disclosure as a convenient method of distinguishing between two or more elements. Thus, reference to a first and second element does not imply that only two elements can be employed or that the first element must precede the second element in any way.

Where "include," "including," and variations thereof are used in this disclosure, these terms are inclusive, as is the term "comprising." is intended. Furthermore, the term "or" as used in this disclosure is not intended to be an exclusive OR.

In this disclosure, if articles are added by translation, such as a, an, and the in English, the disclosure may include that the nouns following these articles are plural.

In the present disclosure, the term "A and B are different" may mean "A and B are different from each other." The term may also mean that "A and B are different from C". Terms such as "separate," "coupled," etc. may also be interpreted in the same manner as "different."

DESCRIPTION OF SYMBOLS 10... Congestion degree estimation system 11... Image acquisition part 12... Imaging information acquisition part 13... People detection part 14... Congestion degree estimation part 20... Terminal 1001... Processor 1002... Memory 1003... Storage 1004 Communication device 1005 Input device 1006 Output device 1007 Bus.

Claims

an image acquisition unit that acquires an image used for estimating the degree of congestion;
an imaging information acquisition unit that acquires imaging information indicating a position and an imaging direction of an imaging device that captured the image based on the image acquired by the image acquisition unit;
A people detection unit that detects the number of people in the image from the image acquired by the image acquisition unit;
a congestion degree estimation unit that identifies a place to be a target for estimating the degree of congestion from the imaging information acquired by the imaging information acquisition unit, and estimates the degree of congestion from the number of people detected by the people detection unit for the specified location;
Congestion degree estimation system with.
The imaging information acquisition unit acquires information indicating a three-dimensional position in a building as information indicating the position at the time of imaging,
2. The congestion degree estimation system according to claim 1, wherein the congestion degree estimation unit specifies any one of a plurality of areas into which the building is divided as a location for which the congestion degree is to be estimated.
The congestion degree estimation system according to claim 1 or 2, wherein the congestion degree estimation unit estimates the degree of congestion from the number of people detected from each of the plurality of images by the people detection unit for the same place.