CN110414375A - Recognition methods, device, storage medium and the electronic equipment of low target - Google Patents
Recognition methods, device, storage medium and the electronic equipment of low target Download PDFInfo
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Abstract
The present invention provides a kind of recognition methods of low target, device, storage medium and electronic equipments, which comprises the detection of suspicious object is carried out to predeterminable area；When detecting suspicious object, detection tracking is carried out to the suspicious object, to obtain video information of suspicious object during detecting tracking, the video information includes visible light video information and infrared video information；The behavioural characteristic of the suspicious object is extracted according to the video information；Identification classification is carried out to the corresponding characteristic parameter of the behavioural characteristic using preset deep learning disaggregated model, the suspicious object is identified according to identification classification results.The present invention provides a kind of low target recognition methods of high efficient and reliable, can effectively ensure that recognition efficiency and the accuracy of low target.
Description
Technical field
The present invention relates to the identification technology field of low target more particularly to a kind of recognition methods of low target, device,
Storage medium and electronic equipment.
Background technique
In recent years, civilian small miniature drone development is swift and violent, and unmanned plane quantity is at geometric growth, and the management of unmanned plane
Serious lag.Unmanned plane " black to fly ", " disorderly flying " phenomenon are got worse, flight safety of the unmanned plane to civil aviation, military aviation
Constitute new threat.
Currently, it is single to the detection of small miniature drone target, identification and monitoring means, it only can be realized to low-altitude low-velocity
The suspicious detection of Small object, it is difficult to quickly, precisely identify whether suspicious object is unmanned plane or other low targets.
Summary of the invention
The invention proposes a kind of recognition methods of low target, device, storage medium and electronic equipments, solve existing nothing
Man-machine detection be difficult to it is quick, precisely identify the problem of whether suspicious object is unmanned plane or other low targets.
One aspect of the present invention provides a kind of recognition methods of low target, which comprises
The detection of suspicious object is carried out to predeterminable area；
When detecting suspicious object, detection tracking is carried out to the suspicious object, is being visited with obtaining the suspicious object
The video information during tracking is surveyed, the video information includes visible light video information and infrared video information；
The behavioural characteristic of the suspicious object is extracted according to the video information；
Identification classification, root are carried out to the corresponding characteristic parameter of the behavioural characteristic using preset deep learning disaggregated model
Identify whether the suspicious object is unmanned plane according to identification classification results.
Optionally, the behavioural characteristic that the suspicious object is extracted according to the video information, comprising:
Each picture frame in the video information is parsed for current video information based on preset neural network model
Activity recognition importance, each figure is matched according to importance of each picture frame for the Activity recognition of current video information
As weight of the frame in preset Activity recognition model；
Behavioural characteristic based on suspicious object described in weight Activity recognition model extraction adjusted.
Optionally, identify whether the suspicious object is the side after unmanned plane according to identification classification results described
Method further include:
If the recognition result of the suspicious object is surface car, the suspicious object is predicted according to the video information
Driving trace；
The urban construction information for obtaining the predeterminable area parses in the predeterminable area according to the urban construction information
The path of each road configures；
Judge in each road of the predeterminable area with the presence or absence of the driving trace of path configuration and the suspicious object
Consistent road, if unanimously, confirming that the suspicious object is surface car.
Optionally, the method also includes:
According to the difference of the recognition result of the suspicious object, the suspicious object is marked using different colors
Know.
Another aspect of the present invention, provides a kind of identification device of low target, and described device includes:
Detecting module, for carrying out the detection of suspicious object to predeterminable area；
Module is obtained, for carrying out detection tracking to the suspicious object when detecting suspicious object, described in obtaining
Video information of suspicious object during detecting tracking, the video information include visible light video information and infrared video letter
Breath；
Extraction module, for extracting the behavioural characteristic of the suspicious object according to the video information；
Identification module, for using preset deep learning disaggregated model to the corresponding characteristic parameter of the behavioural characteristic into
Row identification classification identifies whether the suspicious object is unmanned plane according to identification classification results.
Optionally, the extraction module, comprising:
Configuration unit, for based on preset neural network model parse each picture frame in the video information for
The importance of the Activity recognition of current video information, according to each picture frame for current video information Activity recognition it is important
Property matches weight of each picture frame in preset Activity recognition model；
Extraction unit, for the behavioural characteristic based on suspicious object described in weight Activity recognition model extraction adjusted.
Optionally, described device further include:
Prediction module, for it is described identify according to identification classification results whether the suspicious object is unmanned plane after,
If the recognition result of the suspicious object is surface car, the traveling rail of the suspicious object is predicted according to the video information
Mark；
Parsing module is parsed for obtaining the urban construction information of the predeterminable area according to the urban construction information
The path configuration of each road in the predeterminable area；
Correction verification module, with the presence or absence of path configuration and the suspicious mesh in each road for judging the predeterminable area
The consistent road of target driving trace, if unanimously, confirming that the suspicious object is surface car.
Optionally, described device further include:
Mark module, for the difference according to the recognition result of the suspicious object, using different colors to it is described can
Doubtful target is identified.
In addition, it is stored thereon with computer program the present invention also provides a kind of computer readable storage medium, the program
The step of method as described above is realized when being executed by processor.
In addition, the present invention also provides a kind of electronic equipment, including memory, processor and storage are on a memory and can
The step of computer program run on a processor, the processor realizes method as described above when executing described program.
Recognition methods, device, storage medium and the electronic equipment of low target provided in an embodiment of the present invention, are being detected
After suspicious object, according in the row for carrying out video information extraction suspicious object obtained in detection tracking process to suspicious object
It is characterized, and identification classification is carried out to the characteristic parameter of suspicious object behavioural characteristic using deep learning algorithm model, according to knowledge
Other classification results realize suspicious object whether be unmanned plane identification, can effectively ensure that the recognition efficiency and standard of low target
Exactness.
The above description is only an overview of the technical scheme of the present invention, in order to better understand the technical means of the present invention,
And it can be implemented in accordance with the contents of the specification, and in order to allow above and other objects of the present invention, feature and advantage can
It is clearer and more comprehensible, the followings are specific embodiments of the present invention.
Detailed description of the invention
By reading the following detailed description of the preferred embodiment, various other advantages and benefits are common for this field
Technical staff will become clear.The drawings are only for the purpose of illustrating a preferred embodiment, and is not considered as to the present invention
Limitation.And throughout the drawings, the same reference numbers will be used to refer to the same parts.In the accompanying drawings:
Fig. 1 is a kind of flow diagram of the recognition methods of low target of the embodiment of the present invention；
Fig. 2 is a kind of flow diagram of the recognition methods of low target of another embodiment of the present invention；
Fig. 3 is a kind of structural schematic diagram of the identification device of low target of the embodiment of the present invention；
Fig. 4 is a kind of structural schematic diagram of the identification device of low target of another embodiment of the present invention.
Specific embodiment
Exemplary embodiments of the present disclosure are described in more detail below with reference to accompanying drawings.Although showing the disclosure in attached drawing
Exemplary embodiment, it being understood, however, that may be realized in various forms the disclosure without should be by embodiments set forth here
It is limited.On the contrary, these embodiments are provided to facilitate a more thoroughly understanding of the present invention, and can be by the scope of the present disclosure
It is fully disclosed to those skilled in the art.
Those skilled in the art of the present technique are appreciated that unless otherwise defined, all terms used herein (including technology art
Language and scientific term), there is meaning identical with the general understanding of those of ordinary skill in fields of the present invention.Should also
Understand, those terms such as defined in the general dictionary, it should be understood that have in the context of the prior art
The consistent meaning of meaning, and unless otherwise will not be explained in an idealized or overly formal meaning by specific definitions.
Fig. 1 diagrammatically illustrates the flow chart of the recognition methods of the low target of one embodiment of the invention.Referring to Fig.1,
The recognition methods for the low target that the embodiment of the present invention proposes specifically includes step S11~S14, as follows:
S11, the detection that suspicious object is carried out to predeterminable area.
S12, when detecting suspicious object, detection tracking is carried out to the suspicious object, to obtain the suspicious object
Video information during detecting tracking, the video information includes visible light video information and infrared video information.
In the present embodiment, the hardware system that the recognition methods of low target is applicable in includes low-altitude surveillance radar, photoelectricity
Recognition subsystem, wherein low-altitude surveillance radar, which can be realized, carries out accurately detecting tracking to predeterminable area suspicious object；Then by light
Electric recognition subsystem carries out imaging analysis to the suspicious object traced into, so that the subsequent imaging based on photoelectricity recognition subsystem is real
The identification of existing low target.
S13, the behavioural characteristic that the suspicious object is extracted according to the video information.
S14, identification point is carried out to the corresponding characteristic parameter of the behavioural characteristic using preset deep learning disaggregated model
Class identifies whether the suspicious object is unmanned plane according to identification classification results.
In the present embodiment, data set is acquired in advance, is classified as training set and test set, and it is suspicious to extract training data concentration
The behavioural characteristic of target, to carry out the training of deep learning disaggregated model according to training dataset, and using test set to training
Deep learning disaggregated model out is tested, it is made to meet certain recognition accuracy.
The recognition methods of low target provided in an embodiment of the present invention, after detecting suspicious object, according to can
Doubtful target carries out the behavioural characteristic that video information obtained in detection tracking process extracts suspicious object, and is calculated using deep learning
Method model carries out identification classification to the characteristic parameter of suspicious object behavioural characteristic, realizes that suspicious object is according to identification classification results
The no identification for unmanned plane can effectively ensure that recognition efficiency and the accuracy of low target.
In embodiments of the present invention, the behavioural characteristic that the suspicious object is extracted according to the video information, comprising:
Each picture frame in the video information is parsed for current video information based on preset neural network model
Activity recognition importance, each figure is matched according to importance of each picture frame for the Activity recognition of current video information
As weight of the frame in preset Activity recognition model；
Behavioural characteristic based on suspicious object described in weight Activity recognition model extraction adjusted.
It, can be steady by video before the behavioural characteristic for extracting suspicious object according to video information in the embodiment of the present invention
As algorithm handles video information, compensation photoelectricity recognition subsystem movement is mended by low-rank matrix recovery algorithms from movement
Motion candidates target area is detected in video image after repaying, by removing noise spot tiny in motion candidates target area,
Accuracy is extracted so as to improve the behavioural characteristic of suspicious object, is further increased, guarantees the recognition efficiency of low target and accurate
Degree.
Further, in this embodiment identifying whether the suspicious object is nobody according to identification classification results described
After machine, when being other objects for recognition result, corresponding verification mode also can be used, it is further determined.One
In a specific embodiment, if the recognition result of the suspicious object is surface car, according to video information prediction
The driving trace of suspicious object；The urban construction information for obtaining the predeterminable area parses institute according to the urban construction information
State the path configuration of each road in predeterminable area；Judge in each road of the predeterminable area with the presence or absence of path configuration with
The consistent road of the driving trace of the suspicious object, if unanimously, confirming that the suspicious object is surface car.
It, can also be according to institute if the recognition result of the suspicious object is unmanned plane in another specific embodiment
State the sound characteristic of suspicious object described in acquiring video information；According to the sound characteristic of the suspicious object and preset voice bank
In corresponding unmanned plane sound characteristic it is whether consistent, if unanimously, confirm the suspicious object be unmanned plane.
In the present embodiment, the unmanned plane obtained for the identification classification results according to preset deep learning disaggregated model is known
Other result carries out further identification verifying by other features, and the recognition accuracy of low target is effectively ensured.
In embodiments of the present invention, as shown in Fig. 2, it is described suspicious according to identification classification results identification in step S14
After whether target is unmanned plane, the method also includes:
S15, the difference according to the recognition result of the suspicious object carry out the suspicious object using different colors
Mark.
In the present embodiment, different face can be used in terminal display according to the difference of the recognition result to suspicious object
Color is identified the suspicious object, so that operator is adjusted by the dynamic that control command centre carries out man-machine interface, In
After further confirming that target, starting interference destruction system is interfered unmanned plane normal flight or is directly smashed, and then realization pair
The effective detection and protection of the suspicious airbound target in low latitude.
For embodiment of the method, for simple description, therefore, it is stated as a series of action combinations, but this field
Technical staff should be aware of, and embodiment of that present invention are not limited by the describe sequence of actions, because implementing according to the present invention
Example, some steps may be performed in other sequences or simultaneously.Secondly, those skilled in the art should also know that, specification
Described in embodiment belong to preferred embodiment, the actions involved are not necessarily necessary for embodiments of the present invention.
Fig. 3 diagrammatically illustrates the structural schematic diagram of the identification device of the low target of one embodiment of the invention.Reference
Fig. 3, the identification device of the low target of the embodiment of the present invention specifically include detecting module 201, obtain module 202, extraction module
203 and identification module 204, in which:
Detecting module 201, for carrying out the detection of suspicious object to predeterminable area；
Module 202 is obtained, for carrying out detection tracking to the suspicious object when detecting suspicious object, to obtain
Video information of suspicious object during detecting tracking, the video information includes visible light video information and infrared view
Frequency information；
Extraction module 203, for extracting the behavioural characteristic of the suspicious object according to the video information；
Identification module 204, for being joined using preset deep learning disaggregated model to the corresponding feature of the behavioural characteristic
Number carries out identification classification, identifies whether the suspicious object is unmanned plane according to identification classification results.
In an alternate embodiment of the present invention where, the extraction module 203 specifically includes configuration unit and extracts single
Member, in which:
Configuration unit, for based on preset neural network model parse each picture frame in the video information for
The importance of the Activity recognition of current video information, according to each picture frame for current video information Activity recognition it is important
Property matches weight of each picture frame in preset Activity recognition model；
Extraction unit, for the behavioural characteristic based on suspicious object described in weight Activity recognition model extraction adjusted.
In an alternate embodiment of the present invention where, described device further includes attached prediction module not shown in the figure, parsing
Module and correction verification module, in which:
The prediction module, for identifying whether the suspicious object is unmanned plane according to identification classification results described
Later, if the recognition result of the suspicious object is surface car, the suspicious object is predicted according to the video information
Driving trace；
The parsing module is believed for obtaining the urban construction information of the predeterminable area according to the urban construction
Breath parses the path configuration of each road in the predeterminable area；
The correction verification module, in each road for judging the predeterminable area with the presence or absence of path configuration with it is described
The consistent road of the driving trace of suspicious object, if unanimously, confirming that the suspicious object is surface car.
In an alternate embodiment of the present invention where, as shown in figure 4, described device further includes mark module, the mark
Know module 205, for the difference according to the recognition result of the suspicious object, using different colors to the suspicious object into
Line identifier.
For device embodiment, since it is basically similar to the method embodiment, related so being described relatively simple
Place illustrates referring to the part of embodiment of the method.
The apparatus embodiments described above are merely exemplary, wherein described, unit can as illustrated by the separation member
It is physically separated with being or may not be, component shown as a unit may or may not be physics list
Member, it can it is in one place, or may be distributed over multiple network units.It can be selected according to the actual needs
In some or all of the modules achieve the purpose of the solution of this embodiment.Those of ordinary skill in the art are not paying creativeness
Labour in the case where, it can understand and implement.
The recognition methods of low target provided in an embodiment of the present invention, device, after detecting suspicious object, according to
Video information obtained in detection tracking process is carried out to suspicious object and extracts the behavioural characteristic of suspicious object, and uses depth
It practises algorithm model and identification classification is carried out to the characteristic parameter of suspicious object behavioural characteristic, realize suspicious mesh according to identification classification results
Mark whether be unmanned plane identification, can effectively ensure that recognition efficiency and the accuracy of low target.
In addition, it is stored thereon with computer program the embodiment of the invention also provides a kind of computer readable storage medium,
The step of program realizes method as described above when being executed by processor.
In the present embodiment, if module/unit that the identification device of the low target integrates is with SFU software functional unit
Form realize and when sold or used as an independent product, can store in a computer readable storage medium.Base
In such understanding, the present invention realizes all or part of the process in above-described embodiment method, can also pass through computer program
It is completed to instruct relevant hardware, the computer program can be stored in a computer readable storage medium, the calculating
Machine program is when being executed by processor, it can be achieved that the step of above-mentioned each embodiment of the method.Wherein, the computer program includes
Computer program code, the computer program code can for source code form, object identification code form, executable file or certain
A little intermediate forms etc..The computer-readable medium may include: any entity that can carry the computer program code
Or device, recording medium, USB flash disk, mobile hard disk, magnetic disk, CD, computer storage, read-only memory (ROM, Read-Only
Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software
Distribution medium etc..It should be noted that the content that the computer-readable medium includes can be according to making laws in jurisdiction
Requirement with patent practice carries out increase and decrease appropriate, such as in certain jurisdictions, according to legislation and patent practice, computer
Readable medium does not include electric carrier signal and telecommunication signal.
Electronic equipment provided in an embodiment of the present invention, including memory, processor and storage on a memory and can located
The computer program run on reason device, the processor realize the knowledge of above-mentioned each low target when executing the computer program
Step in other embodiment of the method, such as S11~S14 shown in FIG. 1.Alternatively, the processor executes the computer program
The function of each module/unit in the identification device embodiment of the above-mentioned each low target of Shi Shixian, such as detecting module shown in Fig. 3
201, module 202, extraction module 203 and identification module 204 are obtained.
Illustratively, the computer program can be divided into one or more module/units, one or more
A module/unit is stored in the memory, and is executed by the processor, to complete the present invention.It is one or more
A module/unit can be the series of computation machine program instruction section that can complete specific function, and the instruction segment is for describing institute
State implementation procedure of the computer program in the identification device of the low target.For example, the computer program can be divided
It is cut into detecting module 201, obtains module 202, extraction module 203 and identification module 204.
The electronic equipment may include, but be not limited only to, processor, memory.It will be understood by those skilled in the art that this
Electronic equipment in embodiment may include more or fewer components, perhaps combine certain components or different components, example
Such as described electronic equipment can also include input-output equipment, network access equipment, bus.
The processor can be central processing unit (Central Processing Unit, CPU), can also be it
His general processor, digital signal processor (Digital Signal Processor, DSP), specific integrated circuit
(Application Specific Integrated Circuit, ASIC), ready-made programmable gate array (Field-
Programmable Gate Array, FPGA) either other programmable logic device, discrete gate or transistor logic,
Discrete hardware components etc..General processor can be microprocessor or the processor is also possible to any conventional processor
Deng the processor is the control centre of the electronic equipment, utilizes each of various interfaces and the entire electronic equipment of connection
A part.
The memory can be used for storing the computer program and/or module, and the processor is by operation or executes
Computer program in the memory and/or module are stored, and calls the data being stored in memory, described in realization
The various functions of electronic equipment.The memory can mainly include storing program area and storage data area, wherein storing program area
It can application program (such as sound-playing function, image player function etc.) needed for storage program area, at least one function etc.；
Storage data area, which can be stored, uses created data (such as audio data, phone directory etc.) etc. according to mobile phone.In addition, storage
Device may include high-speed random access memory, can also be hard including nonvolatile memory, such as hard disk, memory, plug-in type
Disk, intelligent memory card (Smart Media Card, SMC), secure digital (Secure Digital, SD) card, flash card
(Flash Card), at least one disk memory, flush memory device or other volatile solid-state parts.
It will be appreciated by those of skill in the art that although some embodiments in this include included in other embodiments
Certain features rather than other feature, but the combination of the feature of different embodiments means to be within the scope of the present invention simultaneously
And form different embodiments.For example, in the following claims, the one of any of embodiment claimed all may be used
Come in a manner of in any combination using.
Finally, it should be noted that the above embodiments are merely illustrative of the technical solutions of the present invention, rather than its limitations；Although
Present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that: it still may be used
To modify the technical solutions described in the foregoing embodiments or equivalent replacement of some of the technical features；
And these are modified or replaceed, technical solution of various embodiments of the present invention that it does not separate the essence of the corresponding technical solution spirit and
Range.
Claims (10)
1. a kind of recognition methods of low target, which is characterized in that the described method includes:
The detection of suspicious object is carried out to predeterminable area；
When detecting suspicious object, detection tracking is carried out to the suspicious object, with obtain the suspicious object detection with
Video information during track, the video information include visible light video information and infrared video information；
The behavioural characteristic of the suspicious object is extracted according to the video information；
Identification classification is carried out to the corresponding characteristic parameter of the behavioural characteristic using preset deep learning disaggregated model, according to knowledge
Other classification results identify whether the suspicious object is unmanned plane.
2. the method according to claim 1, wherein described extract the suspicious object according to the video information
Behavioural characteristic, comprising:
Each picture frame in the video information is parsed for the row of current video information based on preset neural network model
For the importance of identification, each picture frame is matched according to importance of each picture frame for the Activity recognition of current video information
Weight in preset Activity recognition model；
Behavioural characteristic based on suspicious object described in weight Activity recognition model extraction adjusted.
3. the method according to claim 1, wherein identifying the suspicious mesh according to identification classification results described
After whether mark is unmanned plane, the method also includes:
If the recognition result of the suspicious object is surface car, the row of the suspicious object is predicted according to the video information
Sail track；
The urban construction information for obtaining the predeterminable area parses each in the predeterminable area according to the urban construction information
The path of road configures；
Judge consistent with the driving trace of the suspicious object with the presence or absence of path configuration in each road of the predeterminable area
Road, if unanimously, confirm the suspicious object be surface car.
4. method according to claim 1-3, which is characterized in that the method also includes:
According to the difference of the recognition result of the suspicious object, the suspicious object is identified using different colors.
5. a kind of identification device of low target, which is characterized in that described device includes:
Detecting module, for carrying out the detection of suspicious object to predeterminable area；
Module is obtained, it is described suspicious to obtain for carrying out detection tracking to the suspicious object when detecting suspicious object
Video information of target during detecting tracking, the video information includes visible light video information and infrared video information；
Extraction module, for extracting the behavioural characteristic of the suspicious object according to the video information；
Identification module, for being known using preset deep learning disaggregated model to the corresponding characteristic parameter of the behavioural characteristic
Do not classify, identifies whether the suspicious object is unmanned plane according to identification classification results.
6. device according to claim 5, which is characterized in that the extraction module, comprising:
Configuration unit, for parsing each picture frame in the video information for current based on preset neural network model
The importance of the Activity recognition of video information, according to each picture frame for the importance of the Activity recognition of current video information
Weight with each picture frame in preset Activity recognition model；
Extraction unit, for the behavioural characteristic based on suspicious object described in weight Activity recognition model extraction adjusted.
7. device according to claim 5, which is characterized in that described device further include:
Prediction module, for it is described identify according to identification classification results whether the suspicious object is unmanned plane after, if institute
When the recognition result for stating suspicious object is surface car, the driving trace of the suspicious object is predicted according to the video information；
Parsing module, for obtaining the urban construction information of the predeterminable area, according to urban construction information parsing
The path configuration of each road in predeterminable area；
Correction verification module, with the presence or absence of path configuration and the suspicious object in each road for judging the predeterminable area
The consistent road of driving trace, if unanimously, confirming that the suspicious object is surface car.
8. according to the described in any item devices of claim 5-7, which is characterized in that described device further include:
Mark module, for the difference according to the recognition result of the suspicious object, using different colors to the suspicious mesh
Mark is identified.
9. a kind of computer readable storage medium, is stored thereon with computer program, which is characterized in that the program is held by processor
It is realized when row such as the step of any one of claim 1-4 the method.
10. a kind of electronic equipment including memory, processor and stores the calculating that can be run on a memory and on a processor
Machine program, which is characterized in that the processor realizes the step such as any one of claim 1-4 the method when executing described program
Suddenly.
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| CN112199198A (en) * | 2020-10-28 | 2021-01-08 | 上海特金无线技术有限公司 | Method, device, equipment and medium for allocating operation resources detected by unmanned aerial vehicle |
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