CN107203638B - Monitoring video processing method, device and system - Google Patents
Monitoring video processing method, device and system Download PDFInfo
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- CN107203638B CN107203638B CN201710429732.6A CN201710429732A CN107203638B CN 107203638 B CN107203638 B CN 107203638B CN 201710429732 A CN201710429732 A CN 201710429732A CN 107203638 B CN107203638 B CN 107203638B
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- G06F16/70—Information retrieval; Database structures therefor; File system structures therefor of video data
- G06F16/78—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
- G06F16/7867—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using information manually generated, e.g. tags, keywords, comments, title and artist information, manually generated time, location and usage information, user ratings
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- G06F16/70—Information retrieval; Database structures therefor; File system structures therefor of video data
- G06F16/78—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
- G06F16/783—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
- G06F16/7847—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content using low-level visual features of the video content
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Abstract
The invention provides a monitoring video processing method, a monitoring video processing device and a monitoring video processing system, which relate to the technical field of image processing, wherein the monitoring video processing method comprises the following steps: acquiring a video image, and decoding the video image into an RGB video image; carrying out structuring processing on the RGB video image to generate a structured video image, wherein the structured video image comprises a contour of a preset target object and a characteristic value corresponding to the contour; identifying preset target objects of the structured video image frame by frame according to the characteristic values; identifying the identified preset target object; the identified structured video images are classified and stored, so that the technical problem of low accuracy of video image feature extraction in the prior art is solved, and the technical effect of improving the accuracy of video image feature extraction is achieved.
Description
Technical Field
The present invention relates to the field of image processing technologies, and in particular, to a method, an apparatus, and a system for processing a surveillance video.
Background
Most of the existing video processing technologies adopt a traditional method for image feature detection, and different extraction methods are selected according to different feature requirements, such as a common color histogram based on color features or a gray level co-occurrence matrix based on texture, wavelet transformation and the like. Because the original features may have high dimensionality or include a large number of redundant features and irrelevant features, the calculation complexity of a subsequent algorithm becomes high, the problem of low accuracy is also caused, and specific attribute information of an object to be detected is difficult to acquire.
Disclosure of Invention
In view of the above, the present invention provides a method, an apparatus, and a system for processing a surveillance video, so as to solve the technical problem in the prior art that the accuracy of image feature extraction is low.
In a first aspect, an embodiment of the present invention provides a method for processing a surveillance video, including:
acquiring a video image, and decoding the video image into an RGB video image;
carrying out structuring processing on the RGB video image to generate a structured video image, wherein the structured video image comprises the outline of a preset target object and a characteristic value corresponding to the outline;
identifying preset target objects frame by frame of the structured video image through the characteristic values;
identifying the identified preset target object;
and storing the identified structured video images in a classified manner.
With reference to the first aspect, an embodiment of the present invention provides a first possible implementation manner of the first aspect, where after identifying the identified preset target object, the method further includes:
copying a preset target object of each frame of the structured video image to one side of the frame of the structured video image;
and identifying the copied preset target object.
With reference to the first aspect, an embodiment of the present invention provides a second possible implementation manner of the first aspect, where the classifying and storing the identified structured video image includes:
judging whether the identification of the structured video image after each frame identification comprises the characteristic information of a certain preset database;
and if so, storing the identified structured video image into the preset database.
With reference to the first aspect, an embodiment of the present invention provides a third possible implementation manner of the first aspect, where after storing the identified structured video images in a classified manner, the method further includes:
receiving a query condition, wherein the query condition comprises a characteristic value of a preset target object or associated information of the characteristic value;
searching a preset database for a structured video image carrying an identifier matched with the query condition;
and arranging the search results according to the similarity.
With reference to the first aspect, an embodiment of the present invention provides a fourth possible implementation manner of the first aspect, where the query condition is a text description, a code, or a picture.
With reference to the first aspect, an embodiment of the present invention provides a fifth possible implementation manner of the first aspect, where when the query condition is a feature picture, the method includes the following steps:
receiving the uploaded characteristic picture;
carrying out structuralization processing on the characteristic picture;
extracting a characteristic value of a preset target object of the characteristic picture after the structural processing;
searching a structural video image carrying an identifier matched with the characteristic value in a preset database;
and arranging the search results according to the similarity.
In a second aspect, an embodiment of the present invention further provides a surveillance video processing apparatus, including:
the video image acquisition and decoding module is used for acquiring a video image and decoding the video image into an RGB video image;
the video image structuring module is used for carrying out structuring processing on the RGB video image to generate a structured video image, and the structured video image comprises the outline of a preset target object and a characteristic value corresponding to the outline of the preset target object;
the preset target object identification module is used for identifying preset target objects on the structured video image frame by frame through the characteristic values;
the preset target object identification module is used for identifying the identified preset target object;
and the classified storage module is used for storing the identified structured video images in a classified manner.
With reference to the second aspect, an embodiment of the present invention provides a first possible implementation manner of the second aspect, wherein the classification storage module is specifically configured to determine whether an identifier of the identified structured video image of each frame includes feature information of a certain preset database;
and if so, storing the identified structured video image into the preset database.
With reference to the second aspect, an embodiment of the present invention provides a second possible implementation manner of the second aspect, where the method further includes:
the query condition receiving module is used for receiving query conditions, and the query conditions comprise characteristic values of preset target objects or associated information of the characteristic values;
the searching module is used for searching the structural video image carrying the identifier matched with the query condition in a preset database;
and the display module is used for arranging the search results according to the similarity.
In a third aspect, an embodiment of the present invention further provides a surveillance video processing system, including: a camera and the surveillance video processing apparatus of embodiment 2;
the camera is used for acquiring a video image;
the monitoring video processing device is used for storing and inquiring the video images.
The embodiment of the invention has the following beneficial effects:
the surveillance video processing method provided by this embodiment decodes a video image into an RGB video image, and performs a structured processing on the RGB video image, where the structured video image includes a contour of a preset target object and a feature value corresponding to the contour; the method comprises the steps of identifying a preset target object frame by frame through a feature value of a structured video image, identifying the identified preset target object, identifying the preset target object through the feature value after the video is structured, and achieving high operation speed and high identification accuracy; and the identified structured video images are classified and stored, so that the query speed of the preset target object is increased.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
In order to make the aforementioned and other objects, features and advantages of the present invention comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a flowchart of a surveillance video processing method according to embodiment 1 of the present invention;
fig. 2 is a flowchart of another implementation of a surveillance video processing method according to embodiment 1 of the present invention;
fig. 3 is a schematic diagram of a surveillance video processing apparatus according to embodiment 2 of the present invention;
fig. 4 is a schematic diagram of another embodiment of a surveillance video processing apparatus according to embodiment 2 of the present invention;
fig. 5 is a schematic diagram of a surveillance video processing system according to embodiment 3 of the present invention.
Icon: 1-a surveillance video processing device; 11-video image acquisition and decoding module; 12-a video image structuring module; 13-presetting a target object identification module; 14-presetting a target object identification module; 15-a classification storage module; 16-query condition receiving module; 17-a search module; 18-a display module; 2-camera.
Detailed Description
To make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some, but not all embodiments of the present 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 method, the device and the system for processing the monitoring video, provided by the embodiment of the invention, can reduce the operation complexity and improve the identification accuracy of the target object.
To facilitate understanding of the embodiment, first, a method, an apparatus, and a system for processing a surveillance video are disclosed in the embodiments of the present invention.
Example 1
As shown in fig. 1, the present embodiment provides a surveillance video processing method, including the following steps:
s11, acquiring a video image, and decoding the video image into an RGB video image.
And acquiring a monitoring video image shot by the camera, and decoding the video image into a video image in an RGB mode.
And S12, carrying out structuring processing on the RGB video image to generate a structured video image, wherein the structured video image comprises the outline of a preset target object and a characteristic value corresponding to the outline.
The method comprises the steps of structuring an RGB video image, circling out the outline of a preset target object in the video image, and simultaneously generating the characteristic value of each preset target object, wherein the characteristic values of different preset target objects are different.
And S13, identifying the preset target object frame by frame of the structured video image through the characteristic value.
And identifying a preset target object corresponding to the preset target object outline in each frame of the structured video image according to the characteristic value.
And S14, identifying the identified preset target object.
In the step, the preset target object can be directly identified in the original structured video image; the preset target of the structured video image can also be copied to one side of the frame of the structured video image, then the copied preset target is identified, and when the method is used specifically, the preset target object can be copied to the left side, the right side, the bottom and the upper part of the structured video image.
And S15, storing the identified structured video images in a classified manner.
The present embodiment preferably classifies and stores the identified structured video image by the following steps:
judging whether the identification of the structured video image after each frame identification comprises the characteristic information of a certain preset database;
and if so, storing the identified structured video image into the preset database.
Through the classified storage in the step, the speed of searching the preset target object in the structured video image can be greatly improved.
As shown in fig. 2, as another implementation manner of this embodiment, step S15 is followed by the following steps:
and S16, receiving a query condition, wherein the query condition comprises a characteristic value of a preset target object or associated information of the characteristic value.
Receiving a query condition input by a user, wherein the query condition can be a text description or a code, and either of the text description and the code comprises a characteristic value of a preset target object or associated information of the characteristic value. If the query condition is the associated information of the characteristic value, the feature value is associated through the associated information.
S17, searching the structural video image carrying the identifier matched with the query condition in a preset database.
The preset target object outline in the structured video image stored in the monitoring video processing device contains identification information, and the video image of the preset target object can be inquired according to the matching degree of the inquiry condition and the identification information.
Or firstly obtaining the characteristic value associated with the query condition, and then searching the related structured video image in the monitoring video processing device through the characteristic value.
Preferably, it is determined which preset database in the surveillance video processing apparatus the structured video image to be searched is stored in according to the query condition, and then the relevant structured video image is searched in the preset database by the feature value.
And S18, arranging the search results according to the similarity.
Preferably, in this step, the feature value information carried by the query condition is ranked according to the similarity of the feature value information associated with the identification information, and preferably, the feature value information is ranked according to the descending order of the similarity.
Example 2
As shown in fig. 3, the present embodiment provides a surveillance video processing apparatus, including a video image obtaining and decoding module 11, a video image structuring module 12, a preset object identifying module 13, a preset object identifying module 14, and a classification storage module 15, where the video image obtaining and decoding module 11 is configured to obtain a video image and decode the video image into an RGB video image; the video image structuring module 12 is configured to perform structuring processing on the RGB video image to generate a structured video image, where the structured video image includes a contour of a preset target object and a feature value corresponding to the contour of the preset target object; the preset target object identification module 13 is used for performing preset target object identification on the structured video image frame by frame through the characteristic value; the preset target object identification module 14 is configured to identify the identified preset target object; the classification storage module 15 is used for classifying and storing the identified structured video images.
The classification storage module 15 in this embodiment is specifically configured to determine whether the identifier of the identified structured video image of each frame includes feature information of a preset database, where there are multiple preset databases; and if so, storing the identified structured video image into the preset database.
As shown in fig. 4, as another embodiment of this embodiment, the method further includes: the query condition receiving module 16 is used for receiving a query condition, wherein the query condition comprises a feature value of a preset target object or associated information of the feature value; the searching module 17 is configured to search the preset database for a structured video image carrying an identifier matching the query condition; the display module 18 is used for arranging the search results according to the similarity.
The surveillance video processing apparatus provided by the embodiment of the present invention has the same technical features as the surveillance video processing method provided by the above embodiment, so that the same technical problems can be solved, and the same technical effects can be achieved.
Example 3
As shown in fig. 5, the present embodiment provides a surveillance video processing system, including: a camera 2, and the monitoring video processing apparatus 1 according to embodiment 2; the camera 2 is used for acquiring video images; the monitoring video processing device 1 is used for storing and inquiring the video images.
The computer program product of the monitoring video processing method, device and system provided by the embodiments of the present invention includes a computer readable storage medium storing a program code, where instructions included in the program code may be used to execute the method described in the foregoing method embodiments, and specific implementation may refer to the method embodiments, and will not be described herein again.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the system and the apparatus described above may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In addition, in the description of the embodiments of the present invention, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are only for convenience of description and simplicity of description, but do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
Finally, it should be noted that: the above-mentioned embodiments are only specific embodiments of the present invention, which are used for illustrating the technical solutions of the present invention and not for limiting the same, and the protection scope of the present invention is not limited thereto, although the present invention is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: any person skilled in the art can modify or easily conceive the technical solutions described in the foregoing embodiments or equivalent substitutes for some technical features within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the embodiments of the present invention, and they should be construed as being included therein. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (5)
1. A surveillance video processing method, comprising:
acquiring a video image, and decoding the video image into an RGB video image;
carrying out structuring processing on the RGB video image to generate a structured video image, wherein the structured video image comprises a contour of a preset target object and a characteristic value corresponding to the contour;
identifying preset target objects of the structured video image frame by frame according to the characteristic values;
identifying the identified preset target object;
classifying and storing the identified structured video images;
after the identification of the identified preset target object, the method further comprises: copying a preset target object of each frame of the structured video image to one side of the frame of the structured video image; identifying the copied preset target object;
the classified storage of the identified structured video images comprises the following steps: judging whether the identification of each frame of the identified structured video image comprises the characteristic information of a certain preset database; if yes, storing the identified structured video image into the preset database;
after the identified structured video image is classified and stored, the method further comprises the following steps: receiving a query condition, wherein the query condition comprises a characteristic value of a preset target object or associated information of the characteristic value; searching the preset database for the structured video image carrying the identifier matched with the query condition; and arranging the search results according to the similarity.
2. The surveillance video processing method according to claim 1,
the query condition is a text description, a code or a picture.
3. The surveillance video processing method according to claim 2, when the query condition is a feature picture, comprising the steps of:
receiving the uploaded feature picture;
carrying out structuring processing on the characteristic picture;
extracting a characteristic value of a preset target object of the characteristic picture after the structural processing;
searching the preset database for the structured video image carrying the identifier matched with the characteristic value;
and arranging the search results according to the similarity.
4. A surveillance video processing apparatus, comprising:
the video image acquisition and decoding module is used for acquiring a video image and decoding the video image into an RGB video image;
the video image structuring module is used for carrying out structuring processing on the RGB video image to generate a structured video image, and the structured video image comprises the outline of a preset target object and a characteristic value corresponding to the outline;
the preset target object identification module is used for carrying out preset target object identification on the structured video image frame by frame through the characteristic value;
the preset target object identification module is used for identifying the identified preset target object;
the classified storage module is used for classified storage of the identified structured video images;
the preset target object identification module is also used for copying a preset target object of each frame of the structured video image to one side of the frame of the structured video image; identifying the copied preset target object;
the classified storage module is specifically used for judging whether the identification of the identified structured video image of each frame comprises the characteristic information of a certain preset database; if yes, storing the identified structured video image into the preset database;
the device further comprises: the query condition receiving module is used for receiving a query condition, wherein the query condition comprises a characteristic value of a preset target object or associated information of the characteristic value;
the searching module is used for searching the structural video image carrying the identifier matched with the query condition in the preset database;
and the display module is used for arranging the search results according to the similarity.
5. A surveillance video processing system, comprising: a camera and a surveillance video processing apparatus according to claim 4;
the camera is used for acquiring a video image;
the monitoring video processing device is used for storing and inquiring the video images.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710429732.6A CN107203638B (en) | 2017-06-08 | 2017-06-08 | Monitoring video processing method, device and system |
| PCT/CN2018/089963 WO2018223960A1 (en) | 2017-06-08 | 2018-06-05 | Method, device, system, electronic terminal, and readable storage medium for processing surveillance video |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
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| CN201710429732.6A CN107203638B (en) | 2017-06-08 | 2017-06-08 | Monitoring video processing method, device and system |
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| CN107203638A CN107203638A (en) | 2017-09-26 |
| CN107203638B true CN107203638B (en) | 2020-09-25 |
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| WO (1) | WO2018223960A1 (en) |
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| CN107203638B (en) * | 2017-06-08 | 2020-09-25 | 北京深瞐科技有限公司 | Monitoring video processing method, device and system |
| CN108984799A (en) * | 2018-08-21 | 2018-12-11 | 北京深瞐科技有限公司 | A kind of video data handling procedure and device |
| CN109271949A (en) * | 2018-09-28 | 2019-01-25 | 中国科学院长春光学精密机械与物理研究所 | Multispectral image data extraction method, device, equipment and readable storage medium storing program for executing |
| CN110597114A (en) * | 2019-09-04 | 2019-12-20 | 上海新储集成电路有限公司 | Monitoring system |
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| Publication number | Publication date |
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| WO2018223960A1 (en) | 2018-12-13 |
| CN107203638A (en) | 2017-09-26 |
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