CN115035725A - Passenger flow statistical method and system based on machine vision - Google Patents
Passenger flow statistical method and system based on machine vision Download PDFInfo
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- CN115035725A CN115035725A CN202210958102.9A CN202210958102A CN115035725A CN 115035725 A CN115035725 A CN 115035725A CN 202210958102 A CN202210958102 A CN 202210958102A CN 115035725 A CN115035725 A CN 115035725A
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- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
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- G06V20/50—Context or environment of the image
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Abstract
The invention relates to the technical field of data storage, in particular to a passenger flow statistical method and a system based on machine vision, which comprises a control terminal, a passenger flow statistical system and a passenger flow statistical system, wherein the control terminal is a main control terminal of the system and is used for sending out an execution command; the monitoring module is used for monitoring the passenger collecting and distributing area; the receiving module is used for receiving image data acquired by the real-time operation of the monitoring module; the processing module is used for processing the image data received in the receiving module and providing an image data target extraction condition; the invention can reasonably arrange monitoring equipment on the carriers and the waiting stations, collect image data through the monitoring equipment, and then count passenger flow by the image data, and the whole process is reliable and effective, and the statistical data is more accurate, thereby providing data support for urban traffic on the basis of the above, and leading passenger flow in cities to be distributed and correspondingly to the number of the carriers more reasonable.
Description
Technical Field
The invention relates to the technical field of data storage, in particular to a passenger flow statistical method and system based on machine vision.
Background
In recent years, with the rapid development of a rail transit transportation network, urban traffic construction has achieved huge achievements, problems such as rapid increase of passenger flow and the like also come with the urban traffic network, potential hazards are caused to driving safety, urban traffic vehicles comprise buses, taxis, subways and the like, and the vehicles can provide travel demands for multiple passengers;
however, the travel demands and people flows of passengers are mostly distributed and circulated, and are concentrated, and vehicles for providing travel services are provided.
Disclosure of Invention
Solves the technical problem
Aiming at the defects in the prior art, the invention provides a passenger flow statistical method and a passenger flow statistical system based on machine vision, and solves the problems that the traveling demands and the people flows of the passengers are mostly, circularly and intensively distributed, and carriers for providing the traveling services are provided.
Technical scheme
In order to achieve the purpose, the invention is realized by the following technical scheme:
in a first aspect, a machine vision-based passenger flow statistics system includes:
the control terminal is a main control end of the system and is used for sending out an execution command;
the monitoring module is used for monitoring the passenger collecting and distributing area;
the receiving module is used for receiving image data acquired by the real-time operation of the monitoring module;
the processing module is used for processing the image data received in the receiving module and providing an image data target extraction condition;
the storage module is used for receiving passenger image data captured by the monitoring module after the image data is processed by the form capturing unit in the processing module, counting the passenger image data and storing the passenger image data;
the analysis module is used for analyzing the passenger flow numerical value of the waiting platform corresponding to each monitoring module;
and the reporting module is used for receiving the operation result of the analysis module, summarizing the passenger flow volume statistics of the waiting station platform into an electronic file and sending the electronic file to the control terminal.
Furthermore, the monitoring module is disposed with sub-modules, including:
the deployment unit is used for planning and deploying the installation position of the monitoring module;
the networking unit is used for setting a network docking signal to construct a monitoring module data interaction channel;
wherein the networking unit is deployed with sub-modules, comprising:
the signal transmitting module is used for transmitting a data transmission signal;
the signal receiving module is used for receiving data transmission signals;
the monitoring module is installed on the carrier and the waiting platform, the monitoring module with the signal transmitting module is installed on the carrier, and the monitoring module with the signal receiving module is installed at the position of the waiting platform.
Furthermore, two groups of monitoring modules are arranged on the signal transmitting module and are respectively arranged at two positions of an entrance and an exit on the carrier, and one group of monitoring module is arranged on each waiting platform on which the signal receiving module is arranged;
the monitoring module provided with the signal receiving module is marked by adopting an actual geographic installation position coordinate when the installation position is planned and deployed; the monitoring module is vertically arranged on the top of the carrier or the waiting platform.
Furthermore, the processing module is disposed with sub-modules, including:
the filtering unit is used for inhibiting noise audio interference in the image data;
and the shape capturing unit is used for capturing the passenger target image in the image data.
Further, the filtering unit is operative to process the image data using any one of mean filtering, gaussian filtering and median filtering.
Further, the storage module is disposed with sub-modules, including:
the storage unit is used for storing image data acquired by the monitoring module deployed at the waiting platform in real time;
the storage unit is arranged on the signal transmitting module and establishes a data transmission channel with the signal receiving module through a wireless network.
Furthermore, a submodule is deployed in the analysis module, and includes:
the improvement unit is used for controlling the coordinated deployment unit to operate again and carrying out reconcile on the installation position of the monitoring module;
the initial default improvement logic of the improvement unit is the additional installation of the monitoring module and the coordination of the installation position of the monitoring module.
Furthermore, the control terminal is electrically connected with the control terminal through a medium, the medium in the monitoring module is electrically connected with a deployment unit and a networking unit, the networking unit is connected with a signal transmitting module and a signal receiving module through a wireless network, the monitoring module is electrically connected with a receiving module and a processing module through a medium, the medium in the processing module is electrically connected with a filtering unit and a form capturing unit, the processing module is electrically connected with a storage module through a medium, the medium in the storage module is electrically connected with a storage unit, the storage unit is electrically connected with an analysis module through a medium, the medium in the analysis module is electrically connected with an improvement unit, the medium in the analysis module is electrically connected with a reporting module, the storage unit is connected with the signal receiving module through a medium, and the improvement unit is electrically connected with the deployment unit through a medium, and the reporting module establishes a data transmission channel with the control terminal through a wireless network.
In a second aspect, a machine vision-based passenger flow statistics method comprises the following steps:
step 1: acquiring a carrier travel route, acquiring position coordinates of a waiting station in the travel route, and referring to the position coordinates of the waiting station in the carrier travel route to the waiting station and the carrier deployment monitoring equipment;
step 2: establishing a data transmission channel of the monitoring equipment, so that the monitoring equipment on the carrier completes pairing connection when arriving at a monitoring area of the monitoring equipment deployed on a waiting platform, and the monitoring equipment deployed on the carrier receives image data acquired by the monitoring equipment deployed on the waiting platform in real time and stores the image data in the monitoring equipment deployed on the carrier;
step 3: collecting image data stored in monitoring equipment deployed on a carrier, analyzing an image data frame with human body morphological characteristics in the image data, extracting the image data frame with the human body morphological characteristics, and counting a local image data image of the human body morphological characteristics in the data frame;
step 4: tracing the local image data images of the human morphological characteristics in the statistical data frame, and judging the monitoring equipment corresponding to the source of each local image data image;
step 5: analyzing waiting stations configured by monitoring equipment corresponding to local image data image sources, and sequencing passenger flow volume density of the waiting stations;
step 6: and coordinating the deployment parameters of the monitoring equipment of the waiting platform according to the passenger flow density sequencing sequence of the waiting platform.
Furthermore, when the deployment parameters of the monitoring devices at the waiting platform are coordinated in Step6, the storage space of the image data content stored in the monitoring devices on the vehicle is synchronously reconstructed and cleared.
Advantageous effects
Compared with the known public technology, the technical scheme provided by the invention has the following beneficial effects:
1. the invention provides a passenger flow statistical system based on machine vision, which can be used for reasonably arranging monitoring equipment on carriers and waiting stations, acquiring image data through the monitoring equipment, and counting passenger flow by the image data, has reliable and effective integral process, and more accurate obtained statistical data, thereby providing data support for urban traffic on the basis of the image data, ensuring that the number of the carriers correspondingly configured for passenger flow distribution in cities is more reasonable, and bringing convenience for the passenger flow distribution in the cities.
2. The invention provides a passenger flow statistical method based on machine vision, which is used for urban passenger flow statistics.
3. The invention is mutually configured with the waiting station in the process of collecting passenger flow data for statistics, so that the passenger flow data is received in a sectional mode, thereby providing time for processing image data by the system, ensuring that the system runs more stably, and avoiding the occurrence of an irregular event of accumulating and intensively processing a large amount of data.
Drawings
In order to more clearly illustrate the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below. It is obvious that the drawings in the following description are only some embodiments of the invention, and that for a person skilled in the art, other drawings can be derived from them without inventive effort.
FIG. 1 is a schematic diagram of a machine vision based passenger flow statistics system;
FIG. 2 is a flow chart of a passenger flow statistical method based on machine vision;
the reference numerals in the drawings denote: 1. a control terminal; 2. a monitoring module; 21. a deployment unit; 22. a networking unit; 221. a signal transmitting module; 222. a signal receiving module; 3. a receiving module; 4. a processing module; 41. a filtering unit; 42. a form capturing unit; 5. a storage module; 51. a storage unit; 6. an analysis module; 61. an improvement unit; 7. and a reporting module.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be described clearly and completely with reference to the accompanying drawings. It is to be understood that the embodiments described are only a few embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The present invention will be further described with reference to the following examples.
Example 1
The machine vision-based passenger flow statistics system of the embodiment, as shown in fig. 1, includes:
the control terminal 1 is a main control end of the system and is used for sending out an execution command;
the monitoring module 2 is used for monitoring the passenger collecting and distributing area;
the receiving module 3 is used for receiving image data acquired by the monitoring module 2 in real time;
the processing module 4 is used for processing the image data received in the receiving module 3 and providing an image data target extraction condition;
the storage module 5 is used for receiving passenger image data captured by the monitoring module 2 after the image data is processed by the form capturing unit 42 in the processing module 4, counting the passenger image data and storing the passenger image data;
the analysis module 6 is used for analyzing the passenger flow numerical value of the waiting platform corresponding to each monitoring module 2;
and the reporting module 7 is used for receiving the operation result of the analysis module 6, summarizing the passenger flow volume statistics of the waiting station platform into an electronic file and sending the electronic file to the control terminal 1.
In this embodiment, the control terminal 1 controls the monitoring module 2 to monitor the passenger distribution area, receives the image data collected by the real-time operation of the monitoring module 2 via the receiving module 3, synchronously operates the processing module 4 to process the image data received by the receiving module 3, provides the image data target extraction conditions, receives the passenger image data collected by the monitoring module 2 via the storage module 5 after the image data is processed by the shape capturing unit 42 in the processing module 4, the passenger image data are counted and stored, the passenger image data are stored through the storage module 5 and then analyzed through the analysis module 6, the passenger flow numerical values of the waiting stations corresponding to the monitoring modules 2 are received through the report module 7, the operation results of the analysis module 6 are finally received, the passenger flow statistical values of the waiting stations are collected to generate electronic files to be sent to the control terminal 1, and the operation of the passenger flow statistical system is finished.
Example 2
In a specific implementation aspect, on the basis of embodiment 1, this embodiment further specifically describes the passenger flow statistics system based on machine vision in embodiment 1 with reference to fig. 1:
as shown in fig. 1, the monitoring module 2 is deployed with sub-modules, including:
the deployment unit 21 is used for planning and deploying the installation position of the monitoring module 2;
the networking unit 22 is used for setting a network docking signal to construct a data interaction channel of the monitoring module 2;
the networking unit 22 has sub-modules deployed therein, including:
the signal transmitting module 221 is configured to transmit a data transmission signal;
a signal receiving module 222, configured to receive a data transmission signal;
the signal transmitting module 221 is disposed on the monitoring module 2 at the signal receiving module 222, the monitoring module 2 is mounted on the vehicle and the waiting platform, the monitoring module 2 mounted with the signal transmitting module 221 is disposed on the vehicle, and the monitoring module 2 mounted with the signal receiving module 222 is disposed at the waiting platform.
The setting provides the interaction condition for the monitoring equipment 2 to acquire the image data, so that the image data is acquired step by step, and the system can stably process the operation data acquired by the monitoring equipment 2.
As shown in fig. 1, two sets of monitoring modules 2 installed on the signal transmitting module 221 are respectively installed at two entrances and exits on the vehicle, and one set of monitoring module 2 installed on the signal receiving module 222 is configured at each waiting platform;
wherein, the monitoring module 2 installed with the signal receiving module 222 adopts the actual geographic installation position coordinate to mark when planning and deploying the installation position; the monitoring module 2 is vertically installed on the top of a carrier or a waiting platform.
The arrangement can lead the configuration of the monitoring device 2 to be less during the system application, thereby achieving the purpose of saving the system application cost.
As shown in fig. 1, the processing module 4 has sub-modules disposed therein, including:
a filtering unit 41 for suppressing noise and audio interference in the image data;
and a form capturing unit 42 for capturing the passenger target image present in the image data.
Through the arrangement, the process of capturing and extracting the image data collected in the monitoring equipment 2 in the passenger target image content can be more efficient, and interference sources in the image data collected in the monitoring equipment 2 are reduced.
As shown in fig. 1, the filtering unit 41 is operative to process the image data filtering using any one of mean filtering, gaussian filtering and median filtering.
As shown in fig. 1, the storage module 5 has sub-modules disposed therein, including:
the storage unit 51 is used for storing the image data acquired by the real-time operation of the monitoring module 2 deployed at the waiting platform;
the storage unit 51 is disposed on the signal transmitting module 221 to establish a data transmission channel with the signal receiving module 222 through a wireless network.
As shown in fig. 1, the analysis module 6 has sub-modules deployed therein, including:
the improvement unit 61 is used for controlling the coordination deployment unit 21 to operate again and performing coordination again on the installation position of the monitoring module 2;
the improvement unit 61 initially defaults to the improvement logic of the installation of the monitoring module 2 and the coordination of the installation position of the monitoring module 2.
Through the setting, the later stage of system application can be coordinated according to the actual condition of the urban traffic passenger flow, and the positive effect and the application cost brought by system application are further improved.
As shown in fig. 1, the control terminal 1 is electrically connected to the deployment unit 21 and the networking unit 22 through a medium, the networking unit 22 is connected to the signal transmission module 221 and the signal reception module 222 through a wireless network, the monitoring module 2 is electrically connected to the reception module 3 and the processing module 4 through a medium, the filtering unit 41 and the form capturing unit 42 are electrically connected to the medium of the processing module 4, the processing module 4 is electrically connected to the storage module 5 through a medium, the storage unit 51 is electrically connected to the medium of the storage module 5, the storage unit 51 is electrically connected to the analysis module 6 through a medium, the improvement unit 61 is electrically connected to the medium of the analysis module 6, the report module 7 is electrically connected to the medium of the analysis module 6, the storage unit 51 is electrically connected to the signal reception module 222 through a medium, and the improvement unit 61 is electrically connected to the deployment unit 21 through a medium, the reporting module 7 establishes a data transmission channel with the control terminal 1 through a wireless network.
Example 3
In a specific implementation aspect, on the basis of embodiment 1, this embodiment further specifically describes the passenger flow statistics system based on machine vision in embodiment 1 with reference to fig. 2:
the passenger flow statistical method based on the machine vision comprises the following steps:
step 1: acquiring a carrier travel route, acquiring position coordinates of a waiting station in the travel route, and referring to the position coordinates of the waiting station in the carrier travel route to the waiting station and the carrier deployment monitoring equipment;
step 2: establishing a data transmission channel of the monitoring equipment, so that the monitoring equipment on the carrier completes pairing connection when arriving at a monitoring area of the monitoring equipment deployed on a waiting platform, and the monitoring equipment deployed on the carrier receives image data acquired by the monitoring equipment deployed on the waiting platform in real time and stores the image data in the monitoring equipment deployed on the carrier;
step 3: collecting image data stored in monitoring equipment deployed on a carrier, analyzing an image data frame with human body morphological characteristics in the image data, extracting the image data frame with the human body morphological characteristics, and counting a local image data image of the human body morphological characteristics in the data frame;
step 4: tracing the local image data images of the human morphological characteristics in the statistical data frame, and judging the monitoring equipment corresponding to each local image data image source;
step 5: analyzing the waiting stations configured by the monitoring equipment corresponding to each local image data image source, and sequencing the passenger flow density of the waiting stations;
step 6: and coordinating the deployment parameters of the monitoring equipment of the waiting stations according to the passenger flow density sequencing sequence of the waiting stations.
As shown in fig. 2, in Step6, when the deployment parameters of the monitoring devices at the waiting platform are coordinated, the storage space of the image data content stored in the monitoring devices on the vehicle is synchronously reconfigured and cleared.
Through the setting, useless data can be cleared up so that the storage space of the monitoring equipment can be automated, the condition that the storage space of the monitoring equipment is insufficient is ensured, the application of the monitoring equipment is more intelligent, the manual intervention amount for maintenance and management of the monitoring equipment is reduced, and the workload of logistics workers is reduced.
In summary, according to the technical scheme provided in the above embodiments, the monitoring devices can be reasonably deployed on the carriers and the waiting platforms, the image data is collected by the monitoring devices, then the passenger flow volume is counted by the image data, the whole process is reliable and effective, and the obtained statistical data is more accurate, so that data support is provided for urban traffic on the basis of the above data, the number of carriers correspondingly configured for passenger flow distribution in the city is more reasonable, and convenience is brought to the urban passenger flow distribution; meanwhile, sufficient passenger flow data can be acquired by using the method, and on the basis of the sufficient passenger flow data, a planning basis is provided for subsequent urban traffic planning, so that the development of urban traffic construction is facilitated; and the system is mutually configured with the waiting station in the process of collecting passenger flow data for statistics, so that the passenger flow data is received in a sectional manner, thereby providing time for processing image data by the system, ensuring that the system runs more stably, and avoiding the occurrence of an irregular event of accumulating and intensively processing a large amount of data.
The above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. Machine vision based passenger flow statistics system, characterized by comprising:
the control terminal (1) is a main control end of the system and is used for sending out an execution command;
the monitoring module (2) is used for monitoring the passenger collecting and distributing area;
the receiving module (3) is used for receiving the image data acquired by the monitoring module (2) in real-time operation;
the processing module (4) is used for processing the image data received in the receiving module (3) and providing image data target extraction conditions;
the storage module (5) is used for receiving passenger image data captured after the image data collected by the monitoring module (2) is processed by the form capturing unit (42) in the processing module (4), counting the passenger image data and storing the passenger image data;
the analysis module (6) is used for analyzing the passenger flow numerical value of the waiting platform corresponding to each monitoring module (2);
and the reporting module (7) is used for receiving the operation result of the analysis module (6), summarizing the passenger flow statistics of the waiting station platform into an electronic file and sending the electronic file to the control terminal (1).
2. The machine vision based passenger flow statistics system of claim 1, characterized in that a submodule is deployed in the monitoring module (2) comprising:
the deployment unit (21) is used for planning and deploying the installation position of the monitoring module (2);
the networking unit (22) is used for setting a data interaction channel of the network docking signal construction monitoring module (2);
wherein a sub-module is deployed in the networking unit (22), comprising:
the signal transmitting module (221) is used for sending out a data transmission signal;
a signal receiving module (222) for receiving a data transmission signal;
the monitoring system comprises a signal transmitting module (221), a signal receiving module (222), a carrier and a waiting platform, wherein the signal transmitting module (221) and the signal receiving module (222) are both arranged and installed on a monitoring module (2), the monitoring module (2) installed with the signal transmitting module (221) is arranged and installed on the carrier, and the monitoring module (2) installed with the signal receiving module (222) is arranged and installed at the position of the waiting platform.
3. The machine vision based passenger flow statistics system according to claim 2, wherein the signal transmitting module (221) is provided with two sets of monitoring modules (2) respectively installed at two entrances and exits of the vehicle, and the signal receiving module (222) is provided with one set of monitoring modules (2) at each waiting platform;
the monitoring module (2) provided with the signal receiving module (222) adopts the actual geographic installation position coordinates to mark when planning and deploying the installation position; the monitoring module (2) is vertically arranged on the top of the carrier or the waiting platform.
4. The machine vision based passenger flow statistics system of claim 1, characterized in that a sub-module is deployed in the processing module (4) comprising:
a filtering unit (41) for suppressing noise and audio interference in the image data;
and a shape capturing unit (42) for capturing the passenger target image present in the image data.
5. The machine-vision-based passenger flow statistics system of claim 4, wherein the filtering unit (41) is operative to process image data filtering using any one of mean filtering, Gaussian filtering, and median filtering.
6. The machine-vision-based passenger flow statistics system of claim 1, characterized in that a sub-module is deployed in the storage module (5) comprising:
the storage unit (51) is used for storing image data acquired by the real-time operation of the monitoring module (2) deployed at the waiting platform;
the storage unit (51) is deployed on the signal transmitting module (221) and establishes a data transmission channel with the signal receiving module (222) through a wireless network.
7. The machine-vision-based passenger flow statistics system according to claim 1, characterized in that a sub-module is deployed in the analysis module (6) comprising:
the improvement unit (61) is used for controlling the coordinated deployment unit (21) to operate again and carrying out reconcile on the installation position of the monitoring module (2);
the improvement unit (61) initially defaults to an improvement logic, and the improvement logic is installation of the monitoring module (2) and coordination of installation positions of the monitoring module (2).
8. The machine vision based passenger flow statistics system of claim 1, wherein the control terminal (1) is electrically connected with a monitoring module (2) through a medium, the monitoring module (2) is electrically connected with a deployment unit (21) and a networking unit (22) through a medium, the networking unit (22) is connected with a signal transmitting module (221) and a signal receiving module (222) through a wireless network, the monitoring module (2) is electrically connected with a receiving module (3) and a processing module (4) through a medium, the processing module (4) is electrically connected with a filtering unit (41) and a shape capturing unit (42) through a medium, the processing module (4) is electrically connected with a storage module (5) through a medium, the storage module (5) is electrically connected with a storage unit (51) through a medium, and the storage unit (51) is electrically connected with an analysis module (6) through a medium, the medium electric connection of analysis module (6) has improvement unit (61), analysis module (6) medium electric connection has reporting module (7), storage unit (51) is connected with signal receiving module (222) through the medium electric property, improvement unit (61) is connected with deployment unit (21) through the medium electric property, reporting module (7) establishes the data transmission passageway with control terminal (1) through wireless network.
9. A machine vision based passenger flow statistics method, said method is a method for implementing said machine vision based passenger flow statistics system as claimed in claim 1, characterized by comprising the steps of:
step 1: acquiring a carrier travel route, acquiring position coordinates of a waiting station in the travel route, and deploying monitoring equipment for the waiting station and the carrier by referring to the position coordinates of the waiting station in the carrier travel route;
step 2: establishing a data transmission channel of the monitoring equipment, so that the monitoring equipment on the carrier completes pairing connection when arriving at a monitoring area of the monitoring equipment deployed on a waiting platform, and the monitoring equipment deployed on the carrier receives image data acquired by the monitoring equipment deployed on the waiting platform in real time and stores the image data in the monitoring equipment deployed on the carrier;
step 3: collecting image data stored in monitoring equipment deployed on a carrier, analyzing an image data frame with human body morphological characteristics in the image data, extracting the image data frame with the human body morphological characteristics, and counting a local image data image of the human body morphological characteristics in the data frame;
step 4: tracing the local image data images of the human morphological characteristics in the statistical data frame, and judging the monitoring equipment corresponding to the source of each local image data image;
step 5: analyzing waiting stations configured by monitoring equipment corresponding to local image data image sources, and sequencing passenger flow volume density of the waiting stations;
step 6: and coordinating the deployment parameters of the monitoring equipment of the waiting platform according to the passenger flow density sequencing sequence of the waiting platform.
10. The machine-vision-based passenger flow statistics method of claim 9, wherein the image data content storage space stored in the on-vehicle monitoring device is synchronously reorganized and cleared when the deployment parameters of the platform monitoring device are coordinated at Step 6.
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