CN111145378A - Automatic video inspection system and method for road traffic incident - Google Patents
Automatic video inspection system and method for road traffic incident Download PDFInfo
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- CN111145378A CN111145378A CN201911392412.3A CN201911392412A CN111145378A CN 111145378 A CN111145378 A CN 111145378A CN 201911392412 A CN201911392412 A CN 201911392412A CN 111145378 A CN111145378 A CN 111145378A
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- G07C1/20—Checking timed patrols, e.g. of watchman
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Abstract
The invention discloses an automatic video inspection system and method for road traffic events, wherein the system comprises a road inspection application platform and a video analysis processing platform, the road inspection application platform is communicated with the video analysis processing platform through a network, the system is connected with a road monitoring video source through the network and is accessed with a video to be inspected, and the road inspection application platform comprises a video monitoring and inspection management module, an algorithm model registration and management module and a database module; the video analysis processing platform comprises a task scheduling module and an algorithm model service module. The invention constructs an extensible and distributed processing framework with service application and algorithm model decoupling based on a road traffic event video inspection service mode and combined with an intelligent video event detection technology, can realize batch automatic round inspection of road monitoring videos and automatic detection and alarm of various road traffic events, can effectively improve the video inspection efficiency of a road network, and reduces the missing inspection risk of road traffic events.
Description
Technical Field
The invention belongs to the technical field of intelligent traffic, and particularly relates to an automatic video inspection system and method for a road traffic incident.
Background
The video patrol service of the road traffic incident mainly comprises the following steps: the method is used for patrolling illegal and abnormal events occurring in the highway range, such as road property and road right encroachment, traffic safety facility states, infrastructure damage and pollution, highway traffic operation abnormity and the like, finding the highway traffic events through a monitoring camera (or video recording equipment such as a patrol vehicle and the like) arranged on the highway, and informing law enforcement departments and road maintenance departments to dispose the events. The video patrol of the road traffic incident has important significance for improving the traffic capacity of the road network and guaranteeing the traffic safety of the road network.
At present, the main mode adopted by road traffic incident video inspection is manual inspection, that is, road network management personnel perform manual round inspection on accessed road monitoring video pictures at a road monitoring center, and find road traffic incidents occurring in the videos in a mode of human eye observation.
However, the number of road network videos which need to be monitored and patrolled by road network management departments is huge, the information amount of the road monitoring videos exceeds the range of effective processing of manpower, the mode of detecting road traffic events through manual round-patrolling videos is low in efficiency, the manual labor intensity is high, the time interval of video round-patrolling is long, the missing risk of the traffic events is high, and timely discovery and rapid disposal of road emergencies are difficult to realize.
With the development of the technology, an intelligent means based on the computer vision technology provides a new approach for video inspection, such as: a plurality of algorithm models are used for detecting events such as vehicle violation, abnormal parking, pedestrian getting on the road, road congestion and the like. However, the types of events detectable by the independent algorithm models are single, and the performance, the applicable conditions, the operating environment and the packaging mode of each algorithm model are different. From the literature documents disclosed at present, the existing technical solutions cannot simultaneously meet the urgent requirements of the video patrol service of the road traffic incident in the following 4 aspects: (1) carrying out batch automatic round inspection on a large number of video sources; (2) the method comprises the following steps of (1) rapidly and automatically detecting various road traffic events; (3) the method comprises the following steps of (1) replacing and expanding a plug-in type of an event detection algorithm model; (4) the method is suitable for application of multi-level road network departments in different scenes.
Disclosure of Invention
The invention aims to provide an automatic video inspection system and method for road traffic events, which realize the batch automatic round inspection of road monitoring videos and the automatic detection and alarm of various road traffic events.
In order to achieve the purpose, the technical scheme adopted by the invention is as follows:
an automatic video patrol system for road traffic events comprises a road patrol application platform and at least one video analysis processing platform, wherein the at least one video analysis processing platform is in communication connection with the road patrol application platform, and the road patrol application platform comprises a video monitoring and patrol management module, an algorithm model registration and management module and a database module which are in communication connection;
the video monitoring and patrolling management module is used for providing a human-computer interface, selecting a video source to be patrolled, editing a patrolling strategy and selecting and editing an event detection algorithm model, and can generate a video patrolling task order according to information input by a user, send a control instruction and a task order to the video analysis processing platform and remotely start or terminate a video patrolling task; receiving an event detection result output by the video analysis processing platform, and carrying out alarm prompt; storing the video inspection task order, the event detection result and the user operation log into a database;
the algorithm model registration and management module is used for registering the road traffic event detection algorithm model meeting the system interface specification according to the algorithm interface defined by the system; providing online deployment, replacement, updating and copying migration functions of the algorithm model; recording and maintaining configuration parameters and historical operating conditions of each algorithm model;
the database module is used for storing, reading, maintaining and managing patrol task orders, configuration parameters, event detection results, service data and operation data, and providing data sharing, backup and migration functions;
the video analysis processing platform comprises a task scheduling module and an algorithm model service module which are in communication connection, wherein the task scheduling module is used for receiving a control instruction and a task order sent by the video monitoring and patrol management module; video patrol task scheduling according to the task order: according to the time sequence and the task duration of each video source in patrol, controlling an algorithm model service module to read video data from the specified video source at a specified time, and controlling a specified algorithm model to analyze and process the video data; starting or stopping the algorithm model service module according to the task control instruction to perform video analysis processing;
the algorithm model service module is used for loading a video source to be analyzed and processed according to the instruction of the task scheduling module and loading a specified algorithm model to analyze and process video data; after the video data are analyzed and processed, when a road traffic event is detected and found, the detected event information is output to the video monitoring and patrol management module.
Preferably, the video analysis processing platform comprises a plurality of platforms.
Preferably, the patrol strategy editing comprises editing and setting a video source patrol mode, a patrol sequence, patrol task duration and time intervals for patrol of each video source.
Preferably, the event detection algorithm model selection and editing comprises the steps of inspecting and detecting road traffic events according to needs, selecting the algorithm model for detecting and discovering the road traffic events, and editing and setting the operating parameters of the algorithm model.
Preferably, the road traffic events include illegal parking and road congestion.
The automatic video patrol method for the road traffic incident of the automatic video patrol system for the road traffic incident comprises the following steps:
step 1, accessing a road patrol application platform through a client, selecting a video source to be patrolled, editing a video patrol strategy, sending a request to a road monitoring video source by a video monitoring and patrol management module according to a user requirement, reading a video source address and loading a real-time video;
step 2, selecting an algorithm model for video analysis processing according to the type of the road traffic incident to be detected, configuring operation parameters of the algorithm model, and synchronously sending a request to an algorithm model registration and management module by a video monitoring and patrol management module according to the requirements of a user to obtain the application conditions and the historical operation conditions of the algorithm model;
step 3, the video monitoring and patrol management module generates task order information, starts a video patrol task according to a user confirmation instruction, sends a task order and a control instruction to the task scheduling module, and stores the task order to the database module;
step 4, the task scheduling module receives a task order and a control instruction, sends a request to a road monitoring video source according to task order information, reads in the address of the video source to be analyzed and processed, and loads the video source to be processed to the algorithm model service module according to the time sequence and the task duration of video inspection;
step 5, the task scheduling module loads a specified event detection analysis algorithm model according to the specified video event analysis algorithm model in the task order and the control algorithm model service module, and starts video analysis processing;
step 6, after the algorithm model service module detects the event, the event detection result is pushed to a video monitoring and inspection management module;
and 7, receiving the event detection result by the video monitoring and patrol management module, generating an event report, and prompting a user to dispose.
Preferably, the method further comprises the step 8: the user disposes the detected event through the client, and the video monitoring and patrol management module pushes the event detection result and the user disposal result to the database module for storage.
Preferably, the task order information in step 3 includes a video source to be detected, a video patrol strategy, an algorithm model for event detection, and configuration parameters thereof.
Preferably, in step 7, the video monitoring and patrol management module prompts the user to perform treatment in an audible and visual alarm manner.
Compared with the prior art, the invention has the beneficial effects that:
(1) the invention provides an extensible and distributed processing framework with decoupled video patrol service application and an event detection algorithm model, which can realize the batch automatic round patrol of the monitoring videos of a road network by editing and configuring a video source and a patrol strategy and combining intelligent video patrol task scheduling management and the event detection algorithm model based on machine vision;
(2) the invention provides algorithm model interface standardization and system function modularization, decoupling and separating the video inspection service application and the event detection algorithm model, realizing 'plug-in' updating and expansion of the algorithm model, and meeting the requirements of diversified automatic detection and future expansion of road events;
(3) the distributed system structure provided by the invention has the advantages that the video inspection task at the center of the urban road network is split and pushed forward to the processing nodes of each district (county), the requirement on network transmission bandwidth is obviously reduced, the event detection response speed is improved, and the multi-level application requirements of different levels in the province, city and district (county) highway industry can be met.
Drawings
Fig. 1 is a structural composition diagram of an automated video inspection system for road traffic events according to the present invention.
Fig. 2 is a schematic diagram of the distributed deployment of the road traffic event automated video inspection system of the present invention.
Fig. 3 is a flow chart of the automated video inspection work flow of a road traffic event according to the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The following describes the implementation of the present invention in detail with reference to specific embodiments.
As shown in fig. 1, the system of the present invention is composed of a road patrol application platform and a video analysis processing platform, which communicate with each other through ethernet. The video source to be detected comes from a road monitoring video source outside the system, does not belong to the system, and is connected with the system through a network. In the embodiment, one road patrol application platform and a plurality of video analysis and processing platforms adopt distributed deployment. As shown in fig. 2, the road patrol application platform is deployed on one application server of the city road network management department, the plurality of video analysis processing platforms are respectively deployed on video processing servers of the plurality of district (county) road network management departments, and the application server and the video processing servers are connected through an ethernet. The application server is connected with a monitoring video source of the urban highway and is accessed with a video source needing to be patrolled; and video processing servers deployed in each district (county) are respectively connected with the home district (county) level highway monitoring video sources and access the highway network monitoring videos in the district.
The road patrol application platform provides a human-computer interface for a user and is responsible for realizing the functions of planning and managing road traffic incident video patrol tasks, registering and managing an incident detection algorithm model and storing and backing up incident detection results. Mainly comprises three modules: the video monitoring and patrolling system comprises a video monitoring and patrolling management module, an algorithm model registration and management module and a database module, wherein the three modules run independently and communicate through data interfaces. In this example, a city-level user (or a provincial user) accesses a road patrol application platform (as shown in fig. 2) on an application server through a network client to implement a video patrol service operation, the user can select a video source to be patrolled through the client, can edit and configure a video patrol strategy, can specify an event analysis algorithm model to be detected for each video source, and can start or terminate a video patrol task.
The video monitoring and patrol management module is mainly responsible for: providing a human-computer interface, selecting a video source to be patrolled, editing a patrolling strategy (namely, editing and setting a video source patrolling mode, a patrolling sequence, a patrolling task time length and a time interval for patrolling each video source), selecting and editing an event detection algorithm model (namely, selecting an algorithm model capable of detecting and finding a road traffic event according to the road traffic event needing to be patrolled and detected, and editing and setting operation parameters of the algorithm model, for example, when a parking event needs to be detected, selecting an algorithm model based on an adaptive mixed Gaussian model and time sequence analysis and an algorithm model based on an improved convolutional neural network); generating a video patrol task order according to information input by a user, sending a control instruction and the task order to a video analysis processing platform, and remotely starting or stopping a video patrol task; receiving an event detection result output by the video analysis processing platform, and carrying out alarm prompt; and storing the video inspection task order, the event detection result and the user operation log in a database.
The algorithm model registration and management module is mainly responsible for: according to the algorithm interface defined by the system, various road traffic event detection algorithm models meeting the interface specification of the system are registered (namely, the information of the algorithm models is added into a database module); providing online deployment of the algorithm model (namely copying a code file corresponding to the algorithm model to a video analysis processing platform to enable the code file to run), replacement, update and copy migration functions; and recording and maintaining configuration parameters and historical operating conditions of each algorithm model.
The database module is mainly responsible for: storing, reading, maintaining and managing patrol task orders, configuration parameters, event detection results, various service data and operation data, and providing data sharing, backup and migration functions.
The video analysis processing platform mainly provides video event detection algorithm model operation service and video patrol task scheduling management functions. Mainly comprises two modules: the task scheduling module and the algorithm model service module run independently and communicate through a data interface.
The task scheduling module is mainly responsible for: receiving a control instruction and a task order sent by a video monitoring and patrolling management module; according to the task order, performing video patrol task scheduling: according to the time sequence and the task duration of each video source in patrol, controlling an algorithm model service module to read video data from the specified video source at a specified time and controlling a specified algorithm model to analyze and process the data; and starting (or stopping) the algorithm model service module according to the task control instruction to perform video analysis processing.
The algorithm model service module is mainly responsible for: loading a video source to be analyzed and processed according to the instruction of the task scheduling module, and loading a specified algorithm model to analyze and process video data; after the video data are analyzed and processed, when a road traffic event is detected and found, the detected event information is output to the video monitoring and patrol management module.
The invention discloses an automatic video patrol method for a road traffic incident, which comprises the following steps as shown in figure 3:
step 1, a user accesses a road patrol application platform through a client, selects a video source needing to be patrolled, edits a video patrol strategy, and a video monitoring and patrol management module sends a request to a road monitoring video source, reads a video source address and loads a real-time video according to the user requirement;
step 2, the user selects an algorithm model for video analysis processing according to the road traffic event type to be detected, and configures the operation parameters of the algorithm model, such as: when a user needs to detect 2 types of events of 'illegal parking' and 'road congestion', an algorithm model for detecting 2 types of road traffic events of 'illegal parking' and 'road congestion' can be correspondingly selected, and optimal parameters recommended by default by a system are selected; the video monitoring and inspecting management module synchronously sends a request to the algorithm model registration and management module according to the user requirement to acquire the application condition and the historical operation condition of the algorithm model;
step 3, the video monitoring and patrol management module generates task order information (including a video source to be detected, a video patrol strategy, an algorithm model for event detection and configuration parameters) and submits the task order information to a user for confirmation; according to the user confirmation instruction, starting a video patrol task, sending a task order and a control instruction (namely a code for starting task operation) to a task scheduling module, and storing the task order to a database module;
step 4, the task scheduling module receives a task order and a control instruction, sends a request to a road monitoring video source according to task order information, reads in the address of the video source to be analyzed and processed, and loads the video source to be processed to the algorithm model service module according to the time sequence and the task duration of video inspection;
step 5, the task scheduling module loads a specified event detection analysis algorithm model according to the specified video event analysis algorithm model in the task order and the control algorithm model service module, and starts video analysis processing;
step 6, after the algorithm model service module detects the event, the event detection result is pushed to a video monitoring and inspection management module;
step 7, the video monitoring and patrol management module receives the event detection result, generates an event report and prompts a user to dispose in an acousto-optic alarm mode;
and 8, the user disposes the detected event through the client, and the video monitoring and patrol management module pushes the event detection result and the user disposal result to the database module for storage.
The invention constructs an extensible distributed processing framework with decoupled video inspection service application and an event detection algorithm model based on a road traffic event video inspection service mode, can realize batch automatic round inspection of road monitoring videos and automatic detection and alarm of various road traffic events, can effectively improve the efficiency of the conventional road network traffic event video inspection, reduce the labor intensity of workers, reduce the risk of missed inspection of events, and meet the requirements of diversified road event detection and future expansion, thereby providing support for improving the traffic capacity of a road network and ensuring the traffic safety of the road network. By adopting a distributed system structure, the video inspection task of the urban road network center is split and pushed forward to the processing nodes of each district (county), so that the pressure of network transmission bandwidth can be obviously reduced, and the event detection response speed is improved, thereby meeting the multi-level application requirements of different levels in the province, city and district (county) highway industry.
The foregoing illustrates and describes the principles, general features, and advantages of the present invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are described in the specification and illustrated only to illustrate the principle of the present invention, but that various changes and modifications may be made therein without departing from the spirit and scope of the present invention, which fall within the scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (9)
1. An automatic video patrol system for road traffic events is characterized by comprising a road patrol application platform and at least one video analysis processing platform, wherein the at least one video analysis processing platform is in communication connection with the road patrol application platform, and the road patrol application platform comprises a video monitoring and patrol management module, an algorithm model registration and management module and a database module which are in communication connection;
the video monitoring and patrolling management module is used for providing a human-computer interface, selecting a video source to be patrolled, editing a patrolling strategy and selecting and editing an event detection algorithm model, and can generate a video patrolling task order according to information input by a user, send a control instruction and a task order to the video analysis processing platform and remotely start or terminate a video patrolling task; receiving an event detection result output by the video analysis processing platform, and carrying out alarm prompt; storing the video inspection task order, the event detection result and the user operation log into a database;
the algorithm model registration and management module is used for registering the road traffic event detection algorithm model meeting the system interface specification according to the algorithm interface defined by the system; providing online deployment, replacement, updating and copying migration functions of the algorithm model; recording and maintaining configuration parameters and historical operating conditions of each algorithm model;
the database module is used for storing, reading, maintaining and managing patrol task orders, configuration parameters, event detection results, service data and operation data, and providing data sharing, backup and migration functions;
the video analysis processing platform comprises a task scheduling module and an algorithm model service module which are in communication connection, wherein the task scheduling module is used for receiving a control instruction and a task order sent by the video monitoring and patrol management module; video patrol task scheduling according to the task order: according to the time sequence and the task duration of each video source in patrol, controlling an algorithm model service module to read video data from the specified video source at a specified time, and controlling a specified algorithm model to analyze and process the video data; starting or stopping the algorithm model service module according to the task control instruction to perform video analysis processing;
the algorithm model service module is used for loading a video source to be analyzed and processed according to the instruction of the task scheduling module and loading a specified algorithm model to analyze and process video data; after the video data are analyzed and processed, when a road traffic event is detected and found, the detected event information is output to the video monitoring and patrol management module.
2. The automated road traffic event video patrol system according to claim 1, wherein the video analysis processing platform comprises a plurality of platforms.
3. The automated road traffic event video patrol system according to claim 1, wherein said patrol strategy editing comprises editing and setting video source patrol modes, patrol sequences, patrol task durations, and time intervals for each video source patrol.
4. The automated road traffic event video patrol system according to claim 1, wherein said event detection algorithm model selection and editing comprises patrolling detected road traffic events as required, selecting an algorithm model having the function of detecting road traffic events of the type found, and editing and setting the operating parameters of the algorithm model.
5. The automated road traffic event video patrol system according to any one of claims 1-4, wherein said road traffic event comprises illegal parking, road congestion.
6. A road traffic event automated video patrol method of a road traffic event automated video patrol system according to any one of claims 1-5, characterized by comprising the steps of:
step 1, accessing a road patrol application platform through a client, selecting a video source to be patrolled, editing a video patrol strategy, sending a request to a road monitoring video source by a video monitoring and patrol management module according to a user requirement, reading a video source address and loading a real-time video;
step 2, selecting an algorithm model for video analysis processing according to the type of the road traffic incident to be detected, configuring operation parameters of the algorithm model, and synchronously sending a request to an algorithm model registration and management module by a video monitoring and patrol management module according to the requirements of a user to obtain the application conditions and the historical operation conditions of the algorithm model;
step 3, the video monitoring and patrol management module generates task order information, starts a video patrol task according to a user confirmation instruction, sends a task order and a control instruction to the task scheduling module, and stores the task order to the database module;
step 4, the task scheduling module receives a task order and a control instruction, sends a request to a road monitoring video source according to task order information, reads in the address of the video source to be analyzed and processed, and loads the video source to be processed to the algorithm model service module according to the time sequence and the task duration of video inspection;
step 5, the task scheduling module loads a specified event detection analysis algorithm model according to the specified video event analysis algorithm model in the task order and the control algorithm model service module, and starts video analysis processing;
step 6, after the algorithm model service module detects the event, the event detection result is pushed to a video monitoring and inspection management module;
and 7, receiving the event detection result by the video monitoring and patrol management module, generating an event report, and prompting a user to dispose.
7. The automated road traffic event video patrol method according to claim 6, further comprising the step 8 of: the user disposes the detected event through the client, and the video monitoring and patrol management module pushes the event detection result and the user disposal result to the database module for storage.
8. The automatic video inspection method for road traffic events according to claim 6 or 7, wherein the task order information in step 3 comprises a video source to be detected, a video inspection strategy, an algorithm model for event detection and configuration parameters thereof.
9. The automatic video inspection method for road traffic events according to claim 6 or 7, wherein in step 7, the video monitoring and inspection management module prompts the user to handle the road traffic events through an audible and visual alarm.
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