CN109543579A - Recognition methods, device and the storage medium of target object in a kind of image - Google Patents
Recognition methods, device and the storage medium of target object in a kind of image Download PDFInfo
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- CN109543579A CN109543579A CN201811355315.2A CN201811355315A CN109543579A CN 109543579 A CN109543579 A CN 109543579A CN 201811355315 A CN201811355315 A CN 201811355315A CN 109543579 A CN109543579 A CN 109543579A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/40—Extraction of image or video features
- G06V10/44—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
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- G—PHYSICS
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- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/40—Scenes; Scene-specific elements in video content
- G06V20/41—Higher-level, semantic clustering, classification or understanding of video scenes, e.g. detection, labelling or Markovian modelling of sport events or news items
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Abstract
The invention discloses recongnition of objects method, apparatus and storage mediums in a kind of image, for reducing the resource overhead of target object in identification image.The recognition methods of target object in described image, comprising: a frame image is selected from the video of acquisition；Selected image is traversed according to preset step-length；For each topography of traversal, the similarity between the topography and target image is determined, include the target object in the target image；If the similarity is greater than preset threshold, it is determined that there are target objects in selected image.
Description
Technical field
The present invention relates to the recognition methods of target object, device in image identification technical field more particularly to a kind of image
And storage medium.
Background technique
With popularizing for domestic intelligent camera, more and more users like recording by camera some fine
Moment therefrom intercepts the pictures such as personage or pet and is made into the picture collection of choice specimens.
Currently, intercepting out image from the video flowing that camera acquires, backstage image procossing is sent by truncated picture
Server, image processing server by some algorithms based on deep learning frame identify task image in image or
Pet image etc..But this method calculating cost is too high, because picture is sent to background server by network, has certain
Network delay detects additionally by complicated deep learning algorithm, can also consume more resource.
Summary of the invention
The embodiment of the present invention provides recongnition of objects method, apparatus and storage medium in a kind of image, for reducing knowledge
The resource overhead of target object in other image.
In a first aspect, providing a kind of recognition methods of target object in image, comprising:
A frame image is selected from the video of acquisition；
Selected image is traversed according to preset step-length；
For each topography of traversal, the similarity between the topography and target image, the mesh are determined
It include the target object in logo image；
If the similarity is greater than preset threshold, it is determined that there are target objects in selected image.
Optionally, the target image is that user intercepts in advance by client and is sent to video acquisition device；And
It determines the similarity between the topography and pre-stored target image, specifically includes:
Topography local binary patterns LBP feature vector corresponding with the target image is determined respectively；
According to the corresponding LBP feature vector of the topography and the corresponding LBP feature vector of the target image, determine
Similarity between the topography and pre-stored target image.
Optionally, it in each topography for traversal, determines similar between the topography and target image
Before degree, further includes:
The corresponding LBP feature vector of the target image that client is sent is received, the target image is that user is preparatory
Interception；And
It determines the similarity between the topography and pre-stored target image, specifically includes:
Determine the corresponding LBP feature vector of the topography；
According to the corresponding LBP feature vector of the topography and the corresponding LBP feature vector of the target image, determine
Similarity between the topography and pre-stored target image.
Optionally, according to the corresponding LBP feature vector of the topography and the corresponding LBP feature of the target image to
Amount, determines the similarity between the topography and pre-stored target image, specifically includes:
According to the corresponding LBP feature vector of the topography and the corresponding LBP feature vector of the target image, utilize
Cosine similarity algorithm determines the similarity between the topography and pre-stored target image.
Second aspect provides a kind of identification device of target object in image, comprising:
Selecting unit, for selecting a frame image from the video of acquisition；
Traversal Unit, for traversing selected image according to preset step-length；
First determination unit, for each topography for traversal, determine the topography and target image it
Between similarity, include the target object in the target image；
Second determination unit, if being greater than preset threshold for the similarity, it is determined that exist in selected image
Target object.
Optionally, the target image is that user intercepts in advance by client and is sent to video acquisition device；And
First determination unit, for determining topography local binary corresponding with the target image respectively
Mode LBP feature vector；According to the corresponding LBP feature vector of the topography and the corresponding LBP feature of the target image
Vector determines the similarity between the topography and pre-stored target image.
Optionally, in image provided in an embodiment of the present invention target object identification device, further include receiving unit,
In:
The receiving unit determines the office for each topography in first determination unit for traversal
Before similarity between portion's image and target image, receive client send the corresponding LBP feature of the target image to
Amount, the target image are what user intercepted in advance；
First determination unit, for determining the corresponding LBP feature vector of the topography；According to the Local map
As corresponding LBP feature vector and the corresponding LBP feature vector of the target image, determines the topography and be stored in advance
Target image between similarity.
Optionally, first determination unit, for according to the corresponding LBP feature vector of the topography and the mesh
The corresponding LBP feature vector of logo image determines the topography and pre-stored target figure using cosine similarity algorithm
Similarity as between.
The third aspect provides a kind of computing device, including at least one processor and at least one processor, wherein
The memory is stored with computer program, when described program is executed by the processor, so that the processor executes
State either step described in the recognition methods of target object in image.
Fourth aspect provides a kind of computer-readable medium, is stored with the computer program that can be executed by computing device,
When described program is run on the computing device, so that the computing device executes the recognition methods of target object in above-mentioned image
The either step.
In image provided in an embodiment of the present invention in the method, apparatus and claim of recongnition of objects, extract in advance
Include the target image of target object, on this basis, a frame image is selected from the video of acquisition, and according to the step of setting
It is long to traverse selected image, for each topography of traversal, by determining that the topography is similar to target image
Whether degree judges in topography to include target object, compared to the target pair used in deep learning algorithm detection image
As computation complexity being significantly reduced, to reduce the resource overhead of recongnition of objects.
Other features and advantages of the present invention will be illustrated in the following description, also, partly becomes from specification
It obtains it is clear that understand through the implementation of the invention.The objectives and other advantages of the invention can be by written explanation
Specifically noted structure is achieved and obtained in book, claims and attached drawing.
Detailed description of the invention
The drawings described herein are used to provide a further understanding of the present invention, constitutes a part of the invention, this hair
Bright illustrative embodiments and their description are used to explain the present invention, and are not constituted improper limitations of the present invention.In the accompanying drawings:
Fig. 1 is that the application scenarios of the embodiment of the present invention are schematic diagrames；
Fig. 2 is to intercept and upload the flow diagram of the target image comprising target object in the embodiment of the present invention；
Fig. 3 is the recognition methods implementation process diagram of target object in image in the embodiment of the present invention；
Fig. 4 is the identification device structural schematic diagram of target object in image in the embodiment of the present invention；
Fig. 5 is the structural schematic diagram of computing device in the embodiment of the present invention.
Specific embodiment
In order to reduce the resource overhead of target object in identification image, the embodiment of the invention provides targets in a kind of image
Recognition methods, device and the storage medium of object.
Terminal device in the present invention can be PC (full name in English: Personal Computer, PC), plate
Computer, personal digital assistant (Personal Digita l Assistant, PDA), personal communication service (full name in English:
Personal Communication Service, PCS) terminal devices such as phone, notebook and mobile phone, it is also possible to have and moves
The computer of dynamic terminal, for example, it may be portable, pocket, hand-held, built-in computer or vehicle-mounted mobile dress
Set, the equipment that they can provide a user voice and/or data connectivity, and exchange with wireless access network language and/or
Data.
In addition, the specification and claims in the embodiment of the present invention and the term " first " in above-mentioned attached drawing, "
Two " etc. be to be used to distinguish similar objects, without being used to describe a particular order or precedence order.It should be understood that using in this way
Data be interchangeable under appropriate circumstances, so that the embodiments described herein can be in addition to illustrating herein or describing
Sequence other than appearance is implemented.
Referenced herein " multiple or several " refer to two or more."and/or" describes affiliated partner
Incidence relation, indicate may exist three kinds of relationships, for example, A and/or B, can indicate: individualism A exists simultaneously A and B,
These three situations of individualism B.Character "/" typicallys represent the relationship that forward-backward correlation object is a kind of "or".
Below in conjunction with Figure of description, preferred embodiment of the present invention will be described, it should be understood that described herein
Preferred embodiment only for the purpose of illustrating and explaining the present invention and is not intended to limit the present invention, and in the absence of conflict, this hair
The feature in embodiment and embodiment in bright can be combined with each other.
As shown in Figure 1, it is the application scenarios schematic diagram of the embodiment of the present invention.User 10 passes through the visitor installed in terminal 11
Family end login service device 12, wherein client can be the browser of webpage, or be installed in terminal, such as mobile phone, put down
Client in plate computer etc..
It is communicatively coupled between terminal 11 and server 12 by network, which can be local area network, wide area network etc..
Terminal 11 can be portable equipment (such as: mobile phone, plate, laptop etc.), or PC (PC,
Personal Computer), server 12 can be any equipment for being capable of providing Internet service.
Wherein, user 10 obtains user name by registering to server 12 using terminal 11, and server 12 is carried out in user
User name and the user password being arranged with user 10 are stored after succeeding in registration as authentication information, subsequent user 10 utilizes terminal
11 when logging on server 12, and server 12 returns to login page, the login page that user shows in client to client
Input authentication information (i.e. user name and user password) simultaneously submits to server 12, and server 12 compares user and submits authentication information
Whether the authentication information that stores one is shown and determines whether that user logs in when with from user's registration.
After user 10 succeeds in registration, associated intelligent camera head apparatus can be added, by client with binding registration
User name and device identification, in this way, by client, user 10 can control and grasp to the intelligent camera head apparatus of binding
Make.
In order to reduce the complexity of recongnition of objects in image, in the embodiment of the present invention, user 10 can be in client
Middle upload one includes the target image of target object, preferably, user can intercept comprising target image obvious characteristic
Topography uploads, to further decrease the complexity of identification.
It should be noted that target object involved in the embodiment of the present invention can be the personage in image, animal etc. is used
The specified object in family.
By taking target object to be identified is animal shown in Fig. 2 as an example, include to intercepting and uploading in the embodiment of the present invention
The process of the target image of target object is illustrated, and may comprise steps of:
S21, the image comprising target object is obtained.
When it is implemented, image shoot in advance, comprising target object can be read from terminal local, or call eventually
The camera at end implements the image that shooting includes target object.
S22, interception parts of images obtains target image from the image obtained.
In this step, sectional drawing softwares can be called to intercept target image from the image obtained, when it is implemented, can be with
The size of target image is preset, for example, the size of target image can be set as 100*100.
It should be noted that in order to improve the accuracy of recongnition of objects, in the embodiment of the present invention, in interception target figure
When picture, all target objects of the object region preferably intercepted, and preferably include the characteristic of target object
Image, as shown in Figure 3.
The target image that S23, storage intercept.
In this way, client can be obtained target image.For the target image of acquisition, in the embodiment of the present invention, client
It can be handled according to following either type:
The target image of interception is sent to the intelligent video camera head of binding by the first embodiment, client by server
Equipment.
Under this embodiment, client sends image upload request after obtaining target image, to server,
The device identification of target image and intelligent video camera head to be uploaded is carried in image upload request.Server is according to equipment mark
Know, the target image received is sent to corresponding intelligent camera head apparatus, reception is being locally stored in intelligent camera head apparatus
The target image arrived.
Second of embodiment, client determine the feature vector of target image and are sent to intelligent camera by server
Head apparatus.
Under this embodiment, client determines the LBP (local binary of target image after obtaining target image
Mode) feature vector, for example, the feature vector of 128 dimensions can be extracted.Obtained target image feature vector it
Afterwards, data sending request is sent to server, wherein carrying the feature vector of target image and the equipment mark of intelligent video camera head
Know.Server is sent to corresponding intelligent camera head apparatus according to device identification, by the LBP feature vector received, intelligently takes the photograph
As the LBP feature vector received is being locally stored in head apparatus.
Based on this, the embodiment of the invention provides a kind of recognition methods of target object in image, as shown in figure 3, can be with
The following steps are included:
S31, a frame image is selected from the video of acquisition.
When it is implemented, intelligent camera head apparatus during acquiring video flowing, can be selected according to the sample rate of setting
A frame image is selected, for example, can preset every 15 frame image selection, one frame image.
S32, selected image is traversed according to the step-length of setting.
When it is implemented, the image of selection can be traversed using certain step-length, for example, the template using 100*100 walks
It is long to traverse selected image.
S33, the image for traversal, determine the similarity between the topography and target image.
S34, if it is determined that similarity be greater than preset threshold, it is determined that there are target objects in selected image.
When it is implemented, being directed to above two embodiment, in step S33, intelligent video camera head can also be respectively adopted
Following two mode is handled:
Target image has been locally stored in the first embodiment, intelligent camera head apparatus.
Under this embodiment, intelligent camera head apparatus needs to determine topography LBP corresponding with target image respectively
Feature vector；According to the corresponding LBP feature vector of topography and the corresponding LBP feature vector of target image, Local map is determined
Picture and the similarity between target image.
The LBP feature vector of target image is locally stored in second of embodiment, intelligent camera head apparatus.
Under this embodiment, intelligent camera head apparatus only it needs to be determined that the corresponding LBP feature vector of topography, according to
The corresponding LBP feature vector of topography and the corresponding LBP feature vector of the target image determine the topography and pre-
The similarity between target image first stored.
It determines topography when it is implemented, intelligent camera head apparatus can use cosine similarity algorithm and is stored in advance
Target image between similarity.Specifically, topography and pre-stored target figure can be determined according to following formula
Similarity as between:Wherein: x indicates the LBP feature vector of target image, y
Indicate the LBP feature vector of topography.
When it is implemented, if the similarity in selected image between any topography and target image is greater than in advance
If threshold value, it is determined that include target object in selected image.Determine in selected image include target object it
Afterwards, then it extracts selected image and exports.
If being to identify target object, it is determined that selected after all topographies for having traversed selected image
Target object is not included in the image selected.
In image provided in an embodiment of the present invention in the method, apparatus and claim of recongnition of objects, extract in advance
Include the target image of target object, on this basis, a frame image is selected from the video of acquisition, and according to the step of setting
It is long to traverse selected image, for each topography of traversal, by determining that the topography is similar to target image
Whether degree judges in topography to include target object, compared to the target pair used in deep learning algorithm detection image
As computation complexity being significantly reduced, to reduce the resource overhead of recongnition of objects.
Based on the same inventive concept, a kind of device of recongnition of objects in image is additionally provided in the embodiment of the present invention,
Since the principle that above-mentioned apparatus solves the problems, such as is similar to the method for recongnition of objects in image, the implementation of above-mentioned apparatus can
With referring to the implementation of method, overlaps will not be repeated.
As shown in figure 4, its identification device for target object in image provided in an embodiment of the present invention, comprising:
Selecting unit 41, for selecting a frame image from the video of acquisition；
Traversal Unit 42, for traversing selected image according to preset step-length；
First determination unit 43 determines the topography and target image for each topography for traversal
Between similarity, include the target object in the target image；
Second determination unit 44, if being greater than preset threshold for the similarity, it is determined that deposited in selected image
In target object.
Optionally, the target image is that user intercepts in advance by client and is sent to video acquisition device；And
First determination unit, for determining topography local binary corresponding with the target image respectively
Mode LBP feature vector；According to the corresponding LBP feature vector of the topography and the corresponding LBP feature of the target image
Vector determines the similarity between the topography and pre-stored target image.
Optionally, in image provided in an embodiment of the present invention target object identification device, further include receiving unit,
In:
The receiving unit determines the office for each topography in first determination unit for traversal
Before similarity between portion's image and target image, receive client send the corresponding LBP feature of the target image to
Amount, the target image are what user intercepted in advance；
First determination unit, for determining the corresponding LBP feature vector of the topography；According to the Local map
As corresponding LBP feature vector and the corresponding LBP feature vector of the target image, determines the topography and be stored in advance
Target image between similarity.
Optionally, first determination unit, for according to the corresponding LBP feature vector of the topography and the mesh
The corresponding LBP feature vector of logo image determines the topography and pre-stored target figure using cosine similarity algorithm
Similarity as between.
For convenience of description, above each section is divided by function describes respectively for each module (or unit).Certainly, exist
Implement to realize the function of each module (or unit) in same or multiple softwares or hardware when the present invention.
In the image for describing exemplary embodiment of the invention after the recognition methods of target object and device, connect down
Come, introduces the computing device of another exemplary embodiment according to the present invention.
Person of ordinary skill in the field it is understood that various aspects of the invention can be implemented as system, method or
Program product.Therefore, various aspects of the invention can be embodied in the following forms, it may be assumed that complete hardware embodiment, complete
The embodiment combined in terms of full Software Implementation (including firmware, microcode etc.) or hardware and software, can unite here
Referred to as circuit, " module " or " system ".
In some possible embodiments, computing device according to the present invention can include at least at least one processing
Device and at least one processor.Wherein, the memory is stored with program code, when said program code is by the processing
When device executes, so that the processor executes the figure of the illustrative embodiments various according to the present invention of this specification foregoing description
Step as in the recognition methods of target object.For example, the processor can execute step S31 as shown in Figure 3, from
A frame image is selected in the video of acquisition；And step S32, the selected image of step-length traversal according to setting；Step S33,
For the image of traversal, the similarity between the topography and target image is determined；S34, if it is determined that similarity
Greater than preset threshold, it is determined that there are target objects in selected image.
The computing device 50 of this embodiment according to the present invention is described referring to Fig. 5.The calculating dress that Fig. 5 is shown
Setting 50 is only an example, should not function to the embodiment of the present invention and use scope bring any restrictions.
As shown in figure 5, computing device 50 is showed in the form of universal computing device.The component of computing device 50 may include
But it is not limited to: at least one above-mentioned processor 51, above-mentioned at least one processor 52, (including the storage of the different system components of connection
Device 52 and processor 51) bus 53.
Bus 53 indicates one of a few class bus structures or a variety of, including memory bus or Memory Controller,
Peripheral bus, processor or the local bus using any bus structures in a variety of bus structures.
Memory 52 may include the readable medium of form of volatile memory, such as random access memory (RAM) 521
And/or cache memory 522, it can further include read-only memory (ROM) 523.
Memory 52 can also include program/utility 525 with one group of (at least one) program module 524, this
The program module 524 of sample includes but is not limited to: operating system, one or more application program, other program modules and journey
It may include the realization of network environment in ordinal number evidence, each of these examples or certain combination.
Computing device 50 can also be communicated with one or more external equipments 54 (such as keyboard, sensing equipment etc.), may be used also
Enable a user to the equipment interacted with computing device 50 communication with one or more, and/or with enable the computing device 50
Any equipment (such as router, modem etc.) communicated with one or more of the other calculating equipment communicates.This
Kind communication can be carried out by input/output (I/O) interface 55.Also, computing device 50 can also pass through network adapter 56
With one or more network (such as local area network (LAN), wide area network (WAN) and/or public network, such as internet) communication.
As shown, network adapter 56 is communicated by bus 53 with other modules for computing device 50.It will be appreciated that though figure
In be not shown, can in conjunction with computing device 50 use other hardware and/or software module, including but not limited to: microcode, equipment
Driver, redundant processor, external disk drive array, RAID system, tape drive and data backup storage system etc..
In some possible embodiments, in image provided by the invention the recognition methods of target object various aspects
It is also implemented as a kind of form of program product comprising program code, when described program product is transported on a computing device
When row, said program code is for making the computer equipment execute the examples various according to the present invention of this specification foregoing description
Step in the image of property embodiment in the recognition methods of target object, for example, the computer equipment can be executed such as Fig. 5
Shown in step S51, obtain according to recalling of searching for of search key as a result, including with step S52, to recalling result
Resource clustered to obtain the resource of multiple classifications；And step S53, according to comprising the most a kind of resource of resource quantity with
Whether the total number resource amount for including in all categories resource, the judgement a kind of resource most comprising resource quantity are burst thing
Part；Step S54, according to judging result, the emergency event resource different with non-burst EventSelect is shown.
Described program product can be using any combination of one or more readable mediums.Readable medium can be readable letter
Number medium or readable storage medium storing program for executing.Readable storage medium storing program for executing for example may be-but not limited to-electricity, magnetic, optical, electromagnetic, red
The system of outside line or semiconductor, device or device, or any above combination.The more specific example of readable storage medium storing program for executing
(non exhaustive list) includes: the electrical connection with one or more conducting wires, portable disc, hard disk, random access memory
(RAM), read-only memory (ROM), erasable programmable read only memory (EPROM or flash memory), optical fiber, portable compact disc
Read memory (CD-ROM), light storage device, magnetic memory device or above-mentioned any appropriate combination.
The program product for the identification of target object in image of embodiments of the present invention can be using portable tight
It gathers disk read-only memory (CD-ROM) and including program code, and can run on the computing device.However, program of the invention
Product is without being limited thereto, and in this document, readable storage medium storing program for executing can be any tangible medium for including or store program, the program
Execution system, device or device use or in connection can be commanded.
Readable signal medium may include in a base band or as the data-signal that carrier wave a part is propagated, wherein carrying
Readable program code.The data-signal of this propagation can take various forms, including --- but being not limited to --- electromagnetism letter
Number, optical signal or above-mentioned any appropriate combination.Readable signal medium can also be other than readable storage medium storing program for executing it is any can
Read medium, the readable medium can send, propagate or transmit for by instruction execution system, device or device use or
Program in connection.
The program code for including on readable medium can transmit with any suitable medium, including --- but being not limited to ---
Wirelessly, wired, optical cable, RF etc. or above-mentioned any appropriate combination.
The program for executing operation of the present invention can be write with any combination of one or more programming languages
Code, described program design language include object oriented program language-Java, C++ etc., further include conventional
Procedural programming language-such as " C " language or similar programming language.Program code can be fully in user
It calculates and executes in equipment, partly executes on a user device, being executed as an independent software package, partially in user's calculating
Upper side point is executed on a remote computing or is executed in remote computing device or server completely.It is being related to far
Journey calculates in the situation of equipment, and remote computing device can pass through the network of any kind --- including local area network (LAN) or extensively
Domain net (WAN)-be connected to user calculating equipment, or, it may be connected to external computing device (such as utilize Internet service
Provider is connected by internet).
It should be noted that although being referred to several unit or sub-units of device in the above detailed description, this stroke
It point is only exemplary not enforceable.In fact, embodiment according to the present invention, it is above-described two or more
The feature and function of unit can embody in a unit.Conversely, the feature and function of an above-described unit can
It is to be embodied by multiple units with further division.
In addition, although describing the operation of the method for the present invention in the accompanying drawings with particular order, this do not require that or
Hint must execute these operations in this particular order, or have to carry out shown in whole operation be just able to achieve it is desired
As a result.Additionally or alternatively, it is convenient to omit multiple steps are merged into a step and executed by certain steps, and/or by one
Step is decomposed into execution of multiple steps.
It should be understood by those skilled in the art that, the embodiment of the present invention can provide as method, system or computer program
Product.Therefore, complete hardware embodiment, complete software embodiment or reality combining software and hardware aspects can be used in the present invention
Apply the form of example.Moreover, it wherein includes the computer of computer usable program code that the present invention, which can be used in one or more,
The computer program implemented in usable storage medium (including but not limited to magnetic disk storage, CD-ROM, optical memory etc.) produces
The form of product.
The present invention be referring to according to the method for the embodiment of the present invention, the process of equipment (system) and computer program product
Figure and/or block diagram describe.It should be understood that every one stream in flowchart and/or the block diagram can be realized by computer program instructions
The combination of process and/or box in journey and/or box and flowchart and/or the block diagram.It can provide these computer programs
Instruct the processor of general purpose computer, special purpose computer, Embedded Processor or other programmable data processing devices to produce
A raw machine, so that being generated by the instruction that computer or the processor of other programmable data processing devices execute for real
The device for the function of being specified in present one or more flows of the flowchart and/or one or more blocks of the block diagram.
These computer program instructions, which may also be stored in, is able to guide computer or other programmable data processing devices with spy
Determine in the computer-readable memory that mode works, so that it includes referring to that instruction stored in the computer readable memory, which generates,
Enable the manufacture of device, the command device realize in one box of one or more flows of the flowchart and/or block diagram or
The function of being specified in multiple boxes.
These computer program instructions also can be loaded onto a computer or other programmable data processing device, so that counting
Series of operation steps are executed on calculation machine or other programmable devices to generate computer implemented processing, thus in computer or
The instruction executed on other programmable devices is provided for realizing in one or more flows of the flowchart and/or block diagram one
The step of function of being specified in a box or multiple boxes.
Although preferred embodiments of the present invention have been described, it is created once a person skilled in the art knows basic
Property concept, then additional changes and modifications can be made to these embodiments.So it includes excellent that the following claims are intended to be interpreted as
It selects embodiment and falls into all change and modification of the scope of the invention.
Obviously, various changes and modifications can be made to the invention without departing from essence of the invention by those skilled in the art
Mind and range.In this way, if these modifications and changes of the present invention belongs to the range of the claims in the present invention and its equivalent technologies
Within, then the present invention is also intended to include these modifications and variations.
Claims (10)
1. the recognition methods of target object in a kind of image characterized by comprising
A frame image is selected from the video of acquisition；
Selected image is traversed according to preset step-length；
For each topography of traversal, the similarity between the topography and target image, the target figure are determined
It include the target object as in；
If the similarity is greater than preset threshold, it is determined that there are target objects in selected image.
2. the method as described in claim 1, which is characterized in that the target image intercepts concurrent by client in advance for user
Give video acquisition device；And
It determines the similarity between the topography and pre-stored target image, specifically includes:
Topography local binary patterns LBP feature vector corresponding with the target image is determined respectively；
According to the corresponding LBP feature vector of the topography and the corresponding LBP feature vector of the target image, determine described in
Similarity between topography and pre-stored target image.
3. the method as described in claim 1, which is characterized in that in each topography for traversal, determine the part
Before similarity between image and target image, further includes:
The corresponding LBP feature vector of the target image that client is sent is received, the target image is that user intercepts in advance
's；And
It determines the similarity between the topography and pre-stored target image, specifically includes:
Determine the corresponding LBP feature vector of the topography；
According to the corresponding LBP feature vector of the topography and the corresponding LBP feature vector of the target image, determine described in
Similarity between topography and pre-stored target image.
4. method as claimed in claim 2 or claim 3, which is characterized in that according to the corresponding LBP feature vector of the topography and
The corresponding LBP feature vector of the target image, determines similar between the topography and pre-stored target image
Degree, specifically includes:
According to the corresponding LBP feature vector of the topography and the corresponding LBP feature vector of the target image, cosine is utilized
Similarity algorithm determines the similarity between the topography and pre-stored target image.
5. the identification device of target object in a kind of image characterized by comprising
Selecting unit, for selecting a frame image from the video of acquisition；
Traversal Unit, for traversing selected image according to preset step-length；
First determination unit determines between the topography and target image for each topography for traversal
Similarity includes the target object in the target image；
Second determination unit, if being greater than preset threshold for the similarity, it is determined that there are targets in selected image
Object.
6. device as claimed in claim 5, which is characterized in that the target image intercepts concurrent by client in advance for user
Give video acquisition device；And
First determination unit, for determining topography local binary patterns corresponding with the target image respectively
LBP feature vector；According to the corresponding LBP feature vector of the topography and the corresponding LBP feature vector of the target image,
Determine the similarity between the topography and pre-stored target image.
7. method as claimed in claim 5, which is characterized in that further include receiving unit, in which:
The receiving unit determines the Local map for each topography in first determination unit for traversal
As receiving the corresponding LBP feature vector of the target image of client transmission, institute with before the similarity between target image
Stating target image is what user intercepted in advance；
First determination unit, for determining the corresponding LBP feature vector of the topography；According to the topography pair
The corresponding LBP feature vector of LBP feature vector and the target image answered, determines the topography and pre-stored mesh
Similarity between logo image.
8. device as claimed in claims 6 or 7, which is characterized in that
First determination unit, for corresponding according to the corresponding LBP feature vector of the topography and the target image
LBP feature vector, determine the phase between the topography and pre-stored target image using cosine similarity algorithm
Like degree.
9. a kind of computing device, which is characterized in that including at least one processor and at least one processor, wherein described
Memory is stored with computer program, when described program is executed by the processor, so that the processor perform claim is wanted
The step of seeking 1~4 any claim the method.
10. a kind of computer-readable medium, which is characterized in that it is stored with the computer program that can be executed by computing device, when
When described program is run on the computing device, so that the computing device perform claim requires the step of 1~4 any the method
Suddenly.
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