CN111008580A - Human behavior analysis method and device based on intelligent security of park - Google Patents
Human behavior analysis method and device based on intelligent security of park Download PDFInfo
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Abstract
The invention discloses a human behavior analysis method and a human behavior analysis device based on intelligent security of a garden. The region-based tracking algorithm is adopted to track the motion generation region of the target, so that the motion human body data is obtained, and the tracking precision is high and the tracking is stable. The human behavior analysis method based on intelligent security of the garden has high accuracy of analysis and identification, and can remarkably improve the performance of a security monitoring system by combining theoretical research and practical application.
Description
Technical Field
The invention relates to the technical field of intelligent security, in particular to a human behavior analysis method and device based on intelligent security of a park.
Background
The wisdom garden is as a miniature of building wisdom city, and the new wisdom garden based on the technology of thing networking, artificial intelligence is also developing constantly, and the wisdom security protection is as indispensable partly in the wisdom garden solution, and its function is also improving constantly.
The human body anti-intrusion automatic identification system based on image identification integrates the advanced technology of multiple disciplines, overcomes the weakness of the traditional intelligent security, liberates labor force, makes efficient, convenient and reliable intelligent security possible, and brings safety guarantee to the life of people. Meanwhile, the research of the human body intrusion image recognition algorithm for the security monitoring system becomes a research hotspot in the field of computer vision, and has high academic value and research significance. The accuracy of analysis and recognition of the existing human behavior analysis method based on intelligent security in a park still needs to be further improved.
Disclosure of Invention
The invention provides a human behavior analysis method and device based on intelligent security of a park, and aims to solve the problem that the accuracy of analysis and recognition of the existing human behavior analysis method based on intelligent security of the park is to be further improved.
In a first aspect, the invention provides a human behavior analysis method based on intelligent security of a campus, which comprises the following steps:
acquiring video data acquired by a camera;
preprocessing the video data;
detecting a motion generation area of a target in the preprocessed video data by adopting an interframe difference method:
tracking the motion generation area of the target by adopting an area-based tracking algorithm to obtain motion human body data;
extracting motion features from the motion body data;
and identifying the behavior and the action of the human body according to the motion characteristics.
With reference to the first aspect, in a first implementation manner of the first aspect, the detecting a motion occurrence region of an object in the preprocessed video data by using an inter-frame difference method includes:
comparing difference data between two or three consecutive frames in a sequence of video images of the video data;
and detecting a motion occurrence area of the target according to the difference data.
With reference to the first aspect, in a second implementation manner of the first aspect, the tracking a motion occurrence region of the target by using a region-based tracking algorithm, and obtaining motion human body data includes:
acquiring a template containing a target, wherein the template is obtained by image segmentation or artificially determined in advance, and is in a rectangular or irregular shape larger than the target;
and tracking the motion generation area of the target by using a tracking algorithm based on the area according to the motion generation area of the target in the video image sequence to obtain the motion human body data of the target.
With reference to the first aspect, in a third implementable manner of the first aspect, the extracting motion features from the moving human body data includes:
generating motion characteristic data by the motion human body data through a recognition algorithm;
and matching the motion characteristic data with the existing data in the original database, and determining the motion characteristic according to the matching result.
With reference to the first aspect, in a fourth implementable manner of the first aspect, after the behavior action of the human body is recognized according to the motion feature, the method further includes:
and sending the behavior action of the human body to a logistics support system.
In a second aspect, the present invention provides a human behavior analysis device based on intelligent security in a campus, the device comprising:
the acquisition unit is used for acquiring video data acquired by the camera;
the preprocessing unit is used for preprocessing the video data;
a detecting unit, configured to detect a motion occurrence region of a target in the preprocessed video data by using an inter-frame difference method:
the tracking unit is used for tracking the motion generation area of the target by adopting an area-based tracking algorithm to obtain motion human body data;
the extraction unit is used for extracting motion characteristics from the motion human body data;
and the identification unit is used for identifying the behavior and the action of the human body according to the motion characteristics.
With reference to the second aspect, in a first implementable manner of the second aspect, the detection unit includes:
a comparison subunit for comparing difference data between two or three consecutive frames in a sequence of video images of the video data, and a detection subunit for detecting a motion occurrence region of the object based on the difference data.
With reference to the second aspect, in a second implementable manner of the second aspect, the tracking unit includes:
the acquisition subunit is used for acquiring a template containing a target, wherein the template is obtained by image segmentation or artificially determined in advance, and is in a rectangular or irregular shape larger than the target;
and the tracking subunit is used for tracking the motion generation area of the target by using a tracking algorithm based on the area according to the motion generation area of the target in the video image sequence to obtain the motion human body data of the target.
With reference to the second aspect, in a third implementable manner of the second aspect, the extraction unit includes:
the generating subunit is used for generating motion characteristic data by the motion human body data through a recognition algorithm;
and the matching subunit is used for matching the motion characteristic data with the existing data in the original database and determining the motion characteristic according to the matching result.
With reference to the second aspect, in a fourth implementable manner of the second aspect, the apparatus further includes:
and the sending unit is used for sending the behavior action of the human body to a logistics support system.
The invention has the following beneficial effects: the human behavior analysis method and the device based on the intelligent security of the garden provided by the invention have the advantages that the video data acquired by the camera is acquired, the video data are preprocessed, the motion occurrence region of the target in the preprocessed video data is detected by adopting an interframe difference method, the dynamic property is strong, the detection of the motion target under a dynamic background can be adapted, the motion occurrence region of the target is tracked by adopting a region-based tracking algorithm to obtain the motion human data, the tracking precision is high, the tracking is stable, the motion characteristic is extracted from the motion human data, and the behavior action of the human body is identified according to the motion characteristic.
Drawings
In order to more clearly illustrate the technical solution of the present invention, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious to those skilled in the art that other drawings can be obtained according to the drawings without any inventive exercise.
Fig. 1 is a flowchart of a human behavior analysis method based on intelligent security in a campus according to an embodiment of the present invention.
Fig. 2 is a flowchart of step S103 of a human behavior analysis method based on intelligent security in a campus according to an embodiment of the present invention.
Fig. 3 is a flowchart of step S104 of a human behavior analysis method based on intelligent security in a campus according to an embodiment of the present invention.
Fig. 4 is a flowchart of step S105 of a human behavior analysis method based on intelligent security in a campus according to an embodiment of the present invention.
Fig. 5 is a schematic view of a human behavior analysis device based on intelligent security in a campus according to an embodiment of the present invention.
Fig. 6 is a schematic diagram illustrating a target classification method adopted by a classifier of a human behavior analysis device based on intelligent security in a campus according to an embodiment of the present invention.
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 clearly and completely described below with reference to the specific embodiments of the present invention and the accompanying drawings. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the invention. 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 technical solutions provided by the embodiments of the present invention are described in detail below with reference to the accompanying drawings.
Referring to fig. 1, in order to provide a human behavior analysis method based on intelligent security in a campus according to an embodiment of the present invention, an execution subject of the method may be a processor, and the method includes:
and S101, acquiring video data acquired by a camera.
And step S102, preprocessing the video data.
The data collected by the camera is complex and comprises background information, position information, facial information and the like. After the data are determined to be collected, static and dynamic identification is carried out in different environments, then difference characteristic information is collected, dynamic tracking is carried out, and interference factors such as limbs, speed proportion, inclination angle, light shadow intensity and various shielding factors are processed.
And step S103, detecting a motion generation area of the target in the preprocessed video data by adopting an inter-frame difference method.
For target tracking independent of prior knowledge, motion detection is the first step of tracking, namely, a change area is extracted from a background image from a sequence image, the main idea of an interframe difference method is to detect the area with motion by using the difference of two or three continuous frames in a video image sequence, and the interframe difference method is characterized by strong dynamic property and can adapt to the detection of a moving target under a dynamic background.
In this embodiment, please refer to fig. 2, the detecting the motion occurrence region of the target in the preprocessed video data by using the inter-frame difference method includes: in step S201, difference data between two or three consecutive frames in a video image sequence of video data is compared. Step S202, detecting a motion generation area of the target according to the difference data.
And step S104, tracking the motion generation area of the target by adopting an area-based tracking algorithm to obtain motion human body data.
In this embodiment, please refer to fig. 3, the tracking the motion occurrence region of the target by using a region-based tracking algorithm to obtain the motion human body data includes: step S301, a template containing a target is obtained, the template is obtained through image segmentation or is artificially determined in advance, and the template is in a rectangular or irregular shape larger than the target. Step S302, according to the motion generation area of the target in the video image sequence, the motion generation area of the target is tracked by using a tracking algorithm based on the area, and the motion human body data of the target is obtained. The tracking algorithm of the region has the advantages that when the target is not shielded, the tracking precision is very high, and the tracking is very stable. At present, much attention is paid to a tracking method based on an area on how to process the condition of template change, the change is caused by the posture change of a moving target, and if the posture change of the target can be correctly predicted, stable tracking can be realized.
And step S105, extracting motion characteristics from the motion human body data.
In this embodiment, please refer to fig. 4, the extracting of the motion feature from the motion human body data includes: and S401, generating motion characteristic data by the motion human body data through a recognition algorithm. And S402, matching the motion characteristic data with the existing data in the original database, and determining the motion characteristic according to the matching result.
And step S106, identifying the behavior and the action of the human body according to the motion characteristics.
In the embodiment, classification based on combination of static and dynamic features, target classification based on combination of target static features and dynamic motion characteristics, similarity of static contours of similar targets, inclination angles of bodies, distances between feet and other motion features are adopted, and classification is performed by a support vector machine classifier, so that accuracy and robustness are improved. The method can also distinguish people, crowds, automobiles and bicycles by utilizing the compactness value and the variable quantity of the motion direction, and use the characteristics of speed, length-width ratio, dispersion and the like, and distinguish the people and the bicycles in the traffic scene by taking the BP neural network as a classifier, so as to better classify the people and the bicycles in the complex scene.
The object classification refers to extracting an interested object region from a foreground moving region detected by a moving object. The small detected foreground area of the complex scene may contain different kinds of targets, such as pedestrians, vehicles, birds, liu clouds, shaken branches and the like, and in the human body motion analysis system, only the moving human body is interested, so that the type of the moving target needs to be analyzed and identified to extract the human body target. The currently common object classification method is shown in fig. 6.
In this embodiment, after the behavior of the human body is recognized according to the motion characteristics, the method further includes:
and sending the behavior action of the human body to a logistics support system. Specifically, a logistics support system interface can be set, interconnection and intercommunication of the intelligent park system and the logistics support system are achieved through the json interface, and interactive pushing of data information, park intrusion reminding and the like are achieved. The invention can verify and verify the identity by using an identification technology, does not prompt the personnel in the garden if the personnel are identified as the invasion, and informs the entrance guard to process if the personnel are identified as the invasion. Can effectively discern personnel's identity through the video stream, have high security and reliability, reducible hidden danger and risk can play fine security protection effect. The identification technology is compared with a rear-end face list and a database, so that the identification accuracy of the system can be effectively improved, and the reliability of preventing invasion in the park is ensured.
In this embodiment, the object classification method may adopt classification based on shape information and classification based on motion information, and the two types of methods may be used in combination to obtain a more accurate classification result. The classification based on the shape information may specifically be a classification according to shape features of the motion region, for example, a shape parameter of a simple human body contour pattern is used to detect a moving human body. And extracting the characteristics of the region such as dispersity, area, aspect ratio and the like, and dividing the foreground target into human, crowd, vehicle and background interference by adopting a three-layer neural network. People, vehicles and chaotic disturbance are distinguished through the dispersion degree and area information. Classification based on motion information is based on the periodicity of human motion. And judging whether the motion trail has periodicity by adopting a time-frequency analysis method according to the periodicity characteristic of the human motion, thereby identifying the moving human body. The rigidity and periodicity of the moving object are analyzed by calculating the residual streamer of the moving area. Non-rigid body movements have a higher average residual streamer compared to rigid vehicle movements, and body movements are periodic, so the body can be distinguished.
Please refer to 5, the present invention further provides a human behavior analysis device based on intelligent security in a campus, the device comprising:
the acquiring unit 501 is configured to acquire video data acquired by a camera.
A preprocessing unit 502, configured to perform preprocessing on the video data.
A detecting unit 503, configured to detect a motion occurrence region of an object in the preprocessed video data by using an inter-frame difference method.
A tracking unit 504, configured to track the motion occurrence area of the target by using an area-based tracking algorithm, so as to obtain motion human body data.
An extracting unit 505, configured to extract motion features from the moving human body data.
And the identifying unit 506 is used for identifying the behavior and the action of the human body according to the motion characteristics.
A classifier 507 may be further included for implementing classification of the object in recognition in cooperation with the recognition unit 506.
In this embodiment, the detecting unit 503 includes:
a comparison subunit for comparing difference data between two or three consecutive frames in a sequence of video images of the video data,
and the detection subunit is used for detecting the motion generation area of the target according to the difference data.
In this embodiment, the tracking unit 504 includes:
the acquisition subunit is used for acquiring a template containing a target, wherein the template is obtained by image segmentation or artificially determined in advance, and is in a rectangular or irregular shape larger than the target;
and the tracking subunit is used for tracking the motion generation area of the target by using a tracking algorithm based on the area according to the motion generation area of the target in the video image sequence to obtain the motion human body data of the target.
In this embodiment, the extracting unit 505 includes:
the generating subunit is used for generating motion characteristic data by the motion human body data through a recognition algorithm;
and the matching subunit is used for matching the motion characteristic data with the existing data in the original database and determining the motion characteristic according to the matching result.
In this embodiment, the apparatus further includes:
and the sending unit is used for sending the behavior action of the human body to a logistics support system.
The embodiment of the invention also provides a storage medium, and the storage medium stores a computer program, and when the computer program is executed by a processor, the computer program realizes part or all of the steps of the human behavior analysis method based on intelligent security of the garden provided by the invention. The storage medium may be a magnetic disk, an optical disk, a Read-only memory (ROM) or a Random Access Memory (RAM).
Those skilled in the art will readily appreciate that the techniques of the embodiments of the present invention may be implemented as software plus a required general purpose hardware platform. Based on such understanding, the technical solutions in the embodiments of the present invention may be essentially or partially implemented in the form of a software product, which may be stored in a storage medium, such as ROM/RAM, magnetic disk, optical disk, etc., and includes several instructions for enabling a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method according to the embodiments or some parts of the embodiments.
The same and similar parts in the various embodiments in this specification may be referred to each other. Particularly, for the embodiment of the human behavior analysis device based on intelligent security of the campus, the description is simple because the embodiment is basically similar to the embodiment of the method, and the relevant points can be referred to the description in the embodiment of the method.
The above-described embodiments of the present invention should not be construed as limiting the scope of the present invention.
Claims (10)
1. A human behavior analysis method based on intelligent security of a park is characterized by comprising the following steps:
acquiring video data acquired by a camera;
preprocessing the video data;
detecting a motion generation area of a target in the preprocessed video data by adopting an interframe difference method:
tracking the motion generation area of the target by adopting an area-based tracking algorithm to obtain motion human body data;
extracting motion features from the motion body data;
and identifying the behavior and the action of the human body according to the motion characteristics.
2. The method of claim 1, wherein detecting a motion occurrence region of an object in the pre-processed video data using an inter-frame difference method comprises:
comparing difference data between two or three consecutive frames in a sequence of video images of the video data;
and detecting a motion occurrence area of the target according to the difference data.
3. The method of claim 1, wherein tracking the motion occurrence region of the target using a region-based tracking algorithm to obtain motion body data comprises:
acquiring a template containing a target, wherein the template is obtained by image segmentation or artificially determined in advance, and is in a rectangular or irregular shape larger than the target;
and tracking the motion generation area of the target by using a tracking algorithm based on the area according to the motion generation area of the target in the video image sequence to obtain the motion human body data of the target.
4. The method of claim 1, wherein extracting motion features from the moving body data comprises:
generating motion characteristic data by the motion human body data through a recognition algorithm;
and matching the motion characteristic data with the existing data in the original database, and determining the motion characteristic according to the matching result.
5. The method of claim 1, wherein after identifying the behavioral action of the human body based on the motion characteristics, the method further comprises:
and sending the behavior action of the human body to a logistics support system.
6. The utility model provides a human behavior analysis device based on garden wisdom security protection, a serial communication port, the device includes:
the acquisition unit is used for acquiring video data acquired by the camera;
the preprocessing unit is used for preprocessing the video data;
a detecting unit, configured to detect a motion occurrence region of a target in the preprocessed video data by using an inter-frame difference method:
the tracking unit is used for tracking the motion generation area of the target by adopting an area-based tracking algorithm to obtain motion human body data;
the extraction unit is used for extracting motion characteristics from the motion human body data;
and the identification unit is used for identifying the behavior and the action of the human body according to the motion characteristics.
7. The apparatus of claim 6, wherein the detection unit comprises:
a comparison subunit for comparing difference data between two or three consecutive frames in a sequence of video images of the video data,
and the detection subunit is used for detecting the motion generation area of the target according to the difference data.
8. The apparatus of claim 6, wherein the tracking unit comprises:
the acquisition subunit is used for acquiring a template containing a target, wherein the template is obtained by image segmentation or artificially determined in advance, and is in a rectangular or irregular shape larger than the target;
and the tracking subunit is used for tracking the motion generation area of the target by using a tracking algorithm based on the area according to the motion generation area of the target in the video image sequence to obtain the motion human body data of the target.
9. The apparatus of claim 6, wherein the extraction unit comprises:
the generating subunit is used for generating motion characteristic data by the motion human body data through a recognition algorithm;
and the matching subunit is used for matching the motion characteristic data with the existing data in the original database and determining the motion characteristic according to the matching result.
10. The apparatus of claim 6, wherein the apparatus further comprises:
and the sending unit is used for sending the behavior action of the human body to a logistics support system.
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Application publication date: 20200414 |