CN111191525A - Open public place people flow density estimation method based on multi-rotor unmanned aerial vehicle - Google Patents
Open public place people flow density estimation method based on multi-rotor unmanned aerial vehicle Download PDFInfo
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Abstract
The invention relates to the technical field of people stream density detection, in particular to a people stream density estimation method in an open public place based on a multi-rotor unmanned aerial vehicle. The invention can meet the requirement of a user on people stream density detection in an open public place, visually, timely and accurately monitor the large passenger stream in the open public place during holidays, and prevent sudden accidents. Four rotor unmanned aerial vehicle have the field of vision wide, the flexibility is high, convenient to carry, the use degree of difficulty is low, advantages such as degree of automation height, adopt the RTK module, and can establish the GIS map fast, combine together video position information and high definition GIS map, can present people stream density result on the GIS map, be convenient for monitor whole open public place directly perceivedly, and can preserve historical record, very big degree has promoted the efficiency of open public place crowd density detection, make the control can go on more simply smoothly.
Description
Technical Field
The invention relates to the technical field of people stream density detection, in particular to a people stream density estimation method for an open public place based on a multi-rotor unmanned aerial vehicle.
Background
There are various safety hazards in locations with dense traffic. For an open public place with dense personnel, supervision and control are necessary, and the core content is to estimate the people flow density. Without accurate people flow data, it is difficult to reasonably direct the flow of passengers in public places. However, the management of the areas with highly concentrated flows by means of the manpower through the method of visually observing the flows not only consumes the manpower and increases the cost, but also has low accuracy, and once an emergency occurs, the number of the population in the area to be managed cannot be clearly mastered, and the evacuation and emergency modes of which levels are adopted. In order to prevent such accidents, various densely populated places need to clearly control the number and flow conditions of the population in the jurisdiction in real time. In this case, an accurate people stream density estimation system is very important.
Most of the current people stream density estimation schemes focus on indoor public places, and people stream density detection and people group counting are achieved by monitoring all entrances and exits of the indoor public places through fixed monitoring probe formation or modes of additionally arranging intelligent carpets and the like. Because the range of the open public places (such as Shanghai outer beaches and the like) is far larger than that of the indoor public places and no clear access is provided, the requirements of crowd density statistics can not be met obviously by adopting a fixed camera or additionally arranging an intelligent carpet. If the staff is sent to carry out statistics on the spot, the labor consumption is huge, and accurate results cannot be obtained when intensive people flow. The method aims at outdoor open public places, adopts a mode that the unmanned aerial vehicle carries the high-definition pan-tilt camera for detection, has the advantages of wide visual angle, large video coverage, flexible movement of the unmanned aerial vehicle and the like, and meets the application requirements of the scene very much.
In the aspect of people stream density statistics, pedestrian detection methods are conventionally adopted, and a detector based on a component model (such as DPM) is required to overcome the problem of crowd occlusion. This approach does not work well in crowded situations. Or a visual characteristic track clustering method is adopted, for video monitoring, a KLT tracker and a clustering method are generally used, and the number of people is estimated according to the number obtained by track clustering. The method is suitable for indoor monitoring probe clusters and is also not suitable for open public places
In view of the above, an open public place people flow density estimation method based on a multi-rotor unmanned aerial vehicle is provided.
Disclosure of Invention
The invention aims to provide a method for estimating the pedestrian flow density in an open public place based on a multi-rotor unmanned aerial vehicle, and aims to solve the problems that the measurement process of surveying and surveying personnel in geographical mapping, electric power inspection and emergency disaster relief is complicated, the efficiency is low and the data of a satellite map is unclear at present in the background technology.
In order to achieve the purpose, the invention provides the following technical scheme:
an open public place people stream density estimation method based on a multi-rotor unmanned aerial vehicle specifically comprises the following steps:
s1: selecting an open public place area, creating a GIS map of a target area, directly reading the GIS map if the GIS map exists in the target area, and uploading navigation point information and flight parameters by a tablet device;
s2: creating a task, reading the GIS map in an air route drawing module, setting corresponding air routes and flight parameters, and uploading and synchronizing the task to a background server after the task is completed;
s3: carrying equipment such as an unmanned aerial vehicle by field personnel to reach the site, assembling the unmanned aerial vehicle, accessing a remote controller into RTK service, creating a GIS map in real time if the GIS map of a target area does not exist, and importing the GIS map;
s4: downloading an air route area on the panel equipment, generating an orthotropic air route by using an APP (application) built in a PAD (PAD application), and uploading the air route to the unmanned aerial vehicle by the APP through a remote controller;
s5: after the task is confirmed, the unmanned aerial vehicle takes off, the unmanned aerial vehicle automatically finishes flight on a flight line according to the flight line, and meanwhile, the high-definition camera carries out high-definition video acquisition on a lower public area;
s6: the shooting result is uploaded to an image processing server background through a communication module in a video uploading module of the tablet device side, and a key frame in the video is matched with position information in an RTK (real-time kinematic) through a timestamp on the image processing server;
s7: the MCNN algorithm module deployed in the background server analyzes the video stream frame by frame to obtain a real-time crowd density map, further calculates the crowd scale, projects the crowd density map onto a map of an open public place area, realizes global crowd density statistics and real-time display, and calculates the corresponding crowd scale;
s8: the large screen reads and displays the unmanned aerial vehicle position information from the flat panel device and the detection result output by the image processing server, thereby obtaining the people stream density distribution information of the open public area and further performing management measures according to the information;
s9: all data are stored in the data center for backup, and a user views history records at a Web end.
S10: after the detection is finished, the unmanned aerial vehicle automatically returns, field workers recover the unmanned aerial vehicle and confirm the task completion at the front end,
preferably, the unmanned aerial vehicle adopts a quad-rotor unmanned aerial vehicle with a pan-tilt camera, and the unmanned aerial vehicle is provided with an RTK module for network RTK positioning.
Preferably, the tablet device is used to run standalone APPs.
Preferably, the background server performs function operation by using a Web page.
Preferably, the background server is provided with 2 servers, including an image processing server and a data management server, wherein the image processing server is used for processing the real-time video stream, and the data management server is used for arranging data services.
Preferably, the communication network comprises 3G, 4G or 5G network transmission.
Preferably, the data of the unmanned aerial vehicle are transmitted by being connected with the tablet device through an unmanned aerial vehicle remote controller.
Preferably, the tablet device may also be a mobile phone device.
Compared with the prior art, the invention has the beneficial effects that: the open public place people stream density estimation method based on the multi-rotor unmanned aerial vehicle can meet the requirement of a user on people stream density detection of the open public place, visually, timely and accurately monitors the large public stream in the open public place during holidays, and prevents sudden accidents. Four rotor unmanned aerial vehicle have the field of vision wide, the flexibility is high, convenient to carry, use the degree of difficulty low, advantage such as degree of automation. The invention adopts the multi-column convolution neural network, and has better processing capability in the scene of dense people stream. The invention adopts the RTK module, can quickly create the GIS map, combines the video position information with the high-definition GIS map, can present people stream density results on the GIS map, and is convenient for visually monitoring the whole open public place. The scheme has the advantages of high data acquisition definition, wide visual field range, simplicity and convenience in operation, high safety, historical record preservation, and capability of improving the density detection efficiency of people in open public places to a great extent and enabling monitoring to be carried out more simply and smoothly.
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FIG. 1 is a schematic view of the overall scheme of the present invention;
FIG. 2 is a flow chart illustrating the implementation of the present invention;
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the 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.
Example 1
An open public place people stream density estimation method based on a multi-rotor unmanned aerial vehicle is shown in fig. 1-2, and specifically comprises the following steps:
s1: selecting an open public place area, creating a GIS map of a target area, directly reading the GIS map if the GIS map exists in the target area, and uploading navigation point information and flight parameters by a tablet device;
s2: creating a task, reading the GIS map in an air route drawing module, setting corresponding air routes and flight parameters, and uploading and synchronizing the task to a background server after the task is completed;
s3: carrying equipment such as an unmanned aerial vehicle by field personnel to reach the site, assembling the unmanned aerial vehicle, accessing a remote controller into RTK service, creating a GIS map in real time if the GIS map of a target area does not exist, and importing the GIS map;
s4: downloading an air route area on the panel equipment, generating an orthotropic air route by using an APP (application) built in a PAD (PAD application), and uploading the air route to the unmanned aerial vehicle by the APP through a remote controller;
s5: after the task is confirmed, the unmanned aerial vehicle takes off, the unmanned aerial vehicle automatically finishes flight on a flight line according to the flight line, and meanwhile, the high-definition camera carries out high-definition video acquisition on a lower public area;
s6: the shooting result is uploaded to an image processing server background through a communication module in a video uploading module of the tablet device end, and a key frame in the video is matched with position information in an RTK (real-time kinematic) through a timestamp on the image processing server;
s7: the MCNN algorithm module deployed in the background server analyzes the video stream frame by frame to obtain a real-time crowd density map, further calculates the crowd scale, projects the crowd density map onto a map of an open public place area, realizes global crowd density statistics and real-time display, and calculates the corresponding crowd scale;
s8: the large screen reads and displays the unmanned aerial vehicle position information from the flat panel device and the detection result output by the image processing server, thereby obtaining the people stream density distribution information of the open public area and further performing management measures according to the information;
s9: all data are stored in the data center for backup, and a user views history records at a Web end.
S10: after the detection is finished, the unmanned aerial vehicle automatically returns, field workers recover the unmanned aerial vehicle and confirm the task completion at the front end,
further, unmanned aerial vehicle adopts the four rotor unmanned aerial vehicle that contain the cloud platform camera for network RTK location, the four rotor unmanned aerial vehicle of this embodiment adopts the four rotor unmanned aerial vehicle of Xinntom 4 series of big institute's innovation, and unmanned aerial vehicle can realize network RTK location from taking the RTK module, improves the position accuracy to centimetre level, can acquire accurate CMOS positional information. The tripod head camera also adopts a high-definition tripod head camera innovated in the world, and can shoot high-definition digital videos.
Specifically, the tablet device is used for running an independent APP, and the background server performs function operation by using a Web page.
It should be noted that the communication network includes 3G, 4G or 5G network transmission, which can be selected according to the requirement.
Besides, the data of the unmanned aerial vehicle is transmitted through the connection of the unmanned aerial vehicle remote controller and the tablet device, and the tablet device can also adopt a mobile phone device.
When the method for estimating the pedestrian flow density of the open public place based on the multi-rotor unmanned aerial vehicle executes a task, firstly, a GIS map is created for a target area, and if the map exists, the map can be directly read. And then, uploading the navigation point information and the flight parameters by the PAD, after confirming the task, taking off the unmanned aerial vehicle, flying along the task route according to the set parameters, and simultaneously carrying out video acquisition on the public area below by the high-definition camera. The collected videos are transmitted to a background server through a 4G network through PAD connected with an unmanned aerial vehicle remote controller, and the CMOS position information of the key frame is obtained through corresponding time stamps of the videos and the time stamps of the RTK module. The MCNN algorithm module deployed in the background server analyzes the video stream frame by frame to obtain a real-time crowd density map, further calculates the crowd scale, and can project the crowd density map onto a map of an open public place area to realize global crowd density statistics and real-time display. The user can visually obtain the people flow density distribution information of the open public area based on the map, and further management measures are carried out according to the information.
Example 2
As a second embodiment of the present invention, this embodiment provides a set of job module combinations. The field equipment comprises a Phantom4 RTK multi-rotor unmanned aerial vehicle (comprising a high-definition pan-tilt camera and an RTK module), a remote controller and a PAD. Unmanned aerial vehicle's data all is connected with PAD through the remote controller and is transmitted. Two servers need to be arranged in the background, wherein one image processing server serves as the server background and is used for processing the real-time video stream, and the other data management server (data center) serves as a data service, so that the influence of higher CPU occupation on the normal data service during image calculation is avoided. In use, front-end functions are displayed in a Web page form or on an APP at a PAD end, and the page functions comprise a project and task management module, an air route drawing module and a historical record query module. The real-time people stream density statistical result can be displayed on a large screen by combining a high-definition GIS map.
In the implementation process of the open public place people flow density estimation method based on the multi-rotor unmanned aerial vehicle, aiming at an open public place area, business personnel firstly create a people flow density detection project at the front end (a web end or a PAD end), and then the density detection and video historical data of all the open public place areas are attached to the project. At this time, if the GIS map of the area already exists, a high-definition GIS map of the open public place area is imported; then, a task is created, the GIS map is read in an air route drawing module, and corresponding air routes and flight parameters are set; after completion, the task is uploaded and synchronized to the background server. At this moment, field personnel carry equipment such as unmanned aerial vehicles to reach the scene, carry out unmanned aerial vehicle equipment to insert the RTK service with the remote controller. At this time, if there is no GIS map of the area, the GIS map should be created in real time and imported. Then, loading and unloading a route area on the PAD, generating an orthonormal route by using an APP built in the PAD, uploading the route to an unmanned aerial vehicle by the APP through a remote controller, automatically completing route flight by the unmanned aerial vehicle according to the route, shooting a high-definition video in real time by a pan-tilt camera in the flight process, and uploading the shooting result to a background of an image processing server through a video uploading module of a PAD end; on an image processing server, matching a key frame in a video with position information in an RTK (real-time kinematic) through a timestamp, then automatically operating an MCNN (micro-channel network), processing an uploaded video frame in real time to obtain a people stream density map of the open public place, and calculating the corresponding crowd scale. At the moment, the large screen can read and display the unmanned aerial vehicle position information from the PAD and the detection result output by the image processing server; meanwhile, all data are stored in the data center for backup, and a user can view history records at a web end. After the detection is finished, the unmanned aerial vehicle automatically returns, field personnel recover the unmanned aerial vehicle and confirm the task to be finished at the front end, and the task closed loop can be realized.
The open public place people stream density estimation method based on the multi-rotor unmanned aerial vehicle can meet the requirement of a user on people stream density detection of an open public place, visually, timely and accurately monitors the large public places during holidays, and prevents sudden accidents. The detection equipment (quad-rotor unmanned aerial vehicle) has the advantages of wide visual field, high flexibility, convenience in carrying, low use difficulty, high automation degree and the like. The invention adopts the multi-column convolution neural network, and has better processing capability in the scene of dense people stream. The invention adopts the RTK module, can quickly create the GIS map, combines the video position information with the high-definition GIS map, can present people stream density results on the GIS map, and is convenient for visually monitoring the whole open public place. The scheme has the advantages of high data acquisition definition, wide visual field range, simplicity and convenience in operation, high safety, historical record preservation, and capability of improving the density detection efficiency of people in open public places to a great extent and enabling monitoring to be carried out more simply and smoothly.
It should be noted that the electric devices, electronic components, circuits, power modules, etc. related to the present invention are only conventional and adaptable applications of the prior art. Therefore, the present invention is an improvement of the prior art, and is substantially in the connection relationship between hardware, rather than the electric device, the electronic device, the circuit and the power module, that is, although the present invention relates to some electric devices, electronic devices, circuits and power modules, the present invention does not include the improvements of the electric devices, the electronic devices, the circuits and the power modules. The present invention has been described in terms of electrical devices, electronic components, circuits, and power modules for the purpose of better illustrating the present invention and for better understanding of the present invention.
The foregoing shows and describes the general principles, essential features, and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, and the preferred embodiments of the present invention are described in the above embodiments and the description, and are not intended to limit the present invention. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (8)
1. An open public place people stream density estimation method based on a multi-rotor unmanned aerial vehicle is characterized by comprising the following steps: the method specifically comprises the following steps:
s1: selecting an open public place area, creating a GIS map of a target area, directly reading the GIS map if the GIS map exists in the target area, and uploading navigation point information and flight parameters by a tablet device;
s2: creating a task, reading the GIS map in an air route drawing module, setting corresponding air routes and flight parameters, and uploading and synchronizing the task to a background server after the task is completed;
s3: carrying equipment such as an unmanned aerial vehicle by field personnel to reach the site, assembling the unmanned aerial vehicle, accessing a remote controller into RTK service, creating a GIS map in real time if the GIS map of a target area does not exist, and importing the GIS map;
s4: downloading an air route area on the panel equipment, generating an orthotropic air route by using an APP (application) built in a PAD (PAD application), and uploading the air route to the unmanned aerial vehicle by the APP through a remote controller;
s5: after the task is confirmed, the unmanned aerial vehicle takes off, the unmanned aerial vehicle automatically finishes flight on a flight line according to the flight line, and meanwhile, the high-definition camera carries out high-definition video acquisition on a lower public area;
s6: the shooting result is uploaded to an image processing server background through a communication module in a video uploading module of the tablet device end, and a key frame in the video is matched with position information in an RTK (real-time kinematic) through a timestamp on the image processing server;
s7: the MCNN algorithm module deployed in the background server analyzes the video stream frame by frame to obtain a real-time crowd density graph, calculates the crowd scale, projects the crowd density graph onto a map of an open public place area to realize global crowd density statistics and real-time display, and calculates the corresponding crowd scale;
s8: the large screen reads and displays the unmanned aerial vehicle position information from the flat panel device and the detection result output by the image processing server, thereby obtaining the people stream density distribution information of the open public area and carrying out management measures according to the information;
s9: all data are stored in a data center for backup, and a user checks a historical record at a Web end;
s10: after the detection is finished, the unmanned aerial vehicle automatically returns, and field personnel recover the unmanned aerial vehicle and confirm the task to be finished at the front end.
2. The method of estimation of open public space traffic density based on multi-rotor drones according to claim 1, characterized in that: unmanned aerial vehicle adopts the four rotor unmanned aerial vehicle that contain the cloud platform camera, and unmanned aerial vehicle is from taking the RTK module for network RTK location.
3. The method of estimation of open public space traffic density based on multi-rotor drones according to claim 1, characterized in that: the tablet device is used for running independent APP.
4. The method of estimation of open public space traffic density based on multi-rotor drones according to claim 1, characterized in that: and the background server adopts a Web page to perform functional operation.
5. The method of estimation of open public space traffic density based on multi-rotor drones according to claim 1, characterized in that: the background server is provided with 2 stations and comprises an image processing server and a data management server, wherein the image processing server is used for processing real-time video streams, and the data management server is used for arranging data services.
6. The method of estimation of open public space traffic density based on multi-rotor drones according to claim 1, characterized in that: the communication network includes 3G, 4G or 5G network transmission.
7. The method of estimation of open public space traffic density based on multi-rotor drones according to claim 1, characterized in that: unmanned aerial vehicle's data are connected with the panel equipment through the unmanned aerial vehicle remote controller and are transmitted.
8. The method of estimation of open public space traffic density based on multi-rotor drones according to claim 1, characterized in that: the tablet device can also adopt a mobile phone device.
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| CN110470279A (en) * | 2019-09-05 | 2019-11-19 | 上海伯镭智能科技有限公司 | A kind of centralized photovoltaic plant battery component defect cruising inspection system based on multi-rotor unmanned aerial vehicle |
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