CN110597863B - Retrieval system and method for keeping stable performance in control library through dynamic threshold - Google Patents
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- CN110597863B CN110597863B CN201910909891.5A CN201910909891A CN110597863B CN 110597863 B CN110597863 B CN 110597863B CN 201910909891 A CN201910909891 A CN 201910909891A CN 110597863 B CN110597863 B CN 110597863B
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Abstract
The invention discloses a retrieval system capable of keeping stable performance in a control library through a dynamic threshold, which comprises: the system comprises a retrieval database, a dynamic threshold testing module and a retrieval module. The dynamic threshold testing module is used for testing the retrieval database and forming a dynamic threshold of the retrieval database. And the retrieval module retrieves the retrieval database according to the retrieval request, and forms a retrieval result according to the dynamic threshold value in the retrieval process. The invention also provides a retrieval method for keeping stable performance in the control library through the dynamic threshold. The invention can improve the retrieval stability.
Description
Technical Field
The invention relates to database retrieval, in particular to a retrieval system, and particularly relates to a retrieval system which keeps stable performance in a deployment control library through a dynamic threshold. The invention also relates to a retrieval method for keeping stable performance in the control library through the dynamic threshold.
Background
The retrieval system is used for retrieving required contents in a retrieval database, generally inputting characteristics related to the contents to be retrieved, then comparing in the retrieval database, listing out data similar to the comparison and obtaining a retrieval result.
With the development of Artificial Intelligence (AI), retrieval has also become important. For example, a control library for face recognition may be formed, a large number of face features may be stored in a retrieval database corresponding to the control library for face recognition, the face features to be retrieved may be acquired by cameras arranged at different region positions, and after a retrieval request is input to the retrieval system, face recognition may be performed and a corresponding retrieval result may be output.
In the prior art, when a control library is searched by using a request, all search results are sorted in a similarity comparison mode, and then post-filtering is performed by using a threshold value. The result above the threshold is output as a positive example of the search.
In the existing method, the threshold value adopted by the retrieval is usually fixed and unchanged, but the structural characteristics of the deployment and control library are changed, so that the retrieval performance is unstable. The reason is that the structural structure of the deployment and control library comprises data distribution and data scale, wherein the semantics represented by the threshold value are unstable under different data distributions, such as different data sources and different data scales. Meaning that the same threshold does not have generalization under different data distributions, if the same threshold is used, the performance of retrieval is unstable.
Disclosure of Invention
The invention aims to provide a retrieval system which keeps stable performance in a control library through a dynamic threshold value, and can improve the retrieval stability. Therefore, the invention also provides a retrieval method for keeping stable performance in the deployment and control library through the dynamic threshold.
In order to solve the above technical problem, the retrieval system provided by the present invention, which maintains stable performance in a deployment and control library through dynamic threshold values, comprises: the system comprises a retrieval database, a dynamic threshold testing module and a retrieval module.
The dynamic threshold test module is used for testing the retrieval database and forming a dynamic threshold of the retrieval database.
And the retrieval module retrieves the retrieval database according to the retrieval request, and forms a retrieval result according to the dynamic threshold value in the retrieval process.
In a further improvement, the search database comprises a plurality of search databases, and the structural characteristics of each search database comprise data distribution and data scale.
The dynamic threshold value of the retrieval database is adaptively and dynamically changed according to the structural feature change of the retrieval database.
In a further refinement, the data distribution of the search database includes a distribution formed from data from different sources.
In a further improvement, the structural characteristics of the data distribution and the data scale of the search database have dynamically changing characteristics.
The dynamic threshold test module obtains the dynamic threshold by detecting structural features of the search database.
The further improvement is that after receiving the retrieval request, the retrieval module firstly detects all preliminary retrieval results by a similarity comparison method and sorts the preliminary retrieval results, and then filters the preliminary retrieval results by adopting the dynamic threshold to obtain the retrieval results, wherein the filtering is to use the preliminary retrieval results with the retrieval values higher than the dynamic threshold as the retrieval results.
The further improvement is that the retrieval database is a control database for face recognition, a plurality of face information are stored in the retrieval database, and the retrieval module receives the retrieved face information while receiving the retrieval request.
In a further improvement, the retrieved face information is input through a controlled camera.
In a further improvement, the dynamic threshold test module forms the dynamic threshold by:
and querying the structural feature information of the retrieval database.
And carrying out retrieval test on the retrieval database based on the structural characteristic information, wherein a series of test thresholds are adopted in the retrieval test, and different test thresholds obtain corresponding false alarm rates to form a one-to-one corresponding relation between the test thresholds and the false alarm rates.
And calculating the required accuracy rate when searching is carried out based on the structural characteristics and calculating the corresponding required false alarm rate based on the accuracy rate.
And taking the test threshold corresponding to the required false alarm rate as the dynamic threshold.
In order to solve the technical problem, the retrieval method for maintaining stable performance in the control library through the dynamic threshold comprises the following steps:
step one, providing a dynamic threshold value testing module, testing a retrieval database by using the dynamic threshold value testing module and forming a dynamic threshold value table of the retrieval database.
And step two, the retrieval module retrieves the retrieval database according to the retrieval request, and a retrieval result is formed according to the dynamic threshold value in the retrieval process.
In a further improvement, the search database comprises a plurality of search databases, and the structural characteristics of each search database comprise data distribution and data scale.
The dynamic threshold value of the retrieval database is adaptively and dynamically changed according to the structural feature change of the retrieval database.
In a further refinement, the data distribution of the search database includes a distribution formed from data from different sources.
In a further improvement, the structural characteristics of the data distribution and the data scale of the search database have dynamically changing characteristics.
The dynamic threshold test module obtains the dynamic threshold by detecting structural features of the search database.
The further improvement is that after receiving the retrieval request, the retrieval module firstly detects all preliminary retrieval results by a similarity comparison method and sorts the preliminary retrieval results, and then filters the preliminary retrieval results by adopting the dynamic threshold value to obtain the retrieval results, wherein the filtering is to use the preliminary retrieval results with retrieval values higher than the dynamic threshold value as the retrieval results.
The further improvement is that the retrieval database is a control database for face recognition, a plurality of face information are stored in the retrieval database, and the retrieval module receives the retrieved face information while receiving the retrieval request.
In a further improvement, the retrieved face information is input through a controlled camera.
In a further improvement, the dynamic threshold test module forms the dynamic threshold by:
and querying the structural feature information of the retrieval database.
And carrying out retrieval test on the retrieval database based on the structural characteristic information, wherein a series of test thresholds are adopted in the retrieval test, and different test thresholds obtain corresponding false alarm rates to form a one-to-one corresponding relation between the test thresholds and the false alarm rates.
And calculating the required accuracy rate when searching is carried out based on the structural characteristics and calculating the corresponding required false alarm rate based on the accuracy rate.
And taking the test threshold corresponding to the required false alarm rate as the dynamic threshold.
The invention sets dynamic threshold value testing module in the searching system, which can detect the dynamic threshold value of the searching database, and uses the dynamic threshold value to form the searching result and output it in the searching process, therefore, the invention can realize the dynamic threshold value following the structure characteristic change of the searching database, when the structure characteristic of the searching database changes, such as the data distribution and the data scale, the invention can still realize the accurate output, thereby improving the searching stability.
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The invention is described in further detail below with reference to the following figures and detailed description:
FIG. 1 is a block diagram of a retrieval system in accordance with an embodiment of the present invention;
FIG. 2 is a flow chart of the dynamic threshold test module in the retrieval system for calculating the dynamic threshold according to the embodiment of the present invention.
Detailed Description
FIG. 1 is a block diagram of a search system according to an embodiment of the present invention; the retrieval system which keeps stable performance in a deployment control library through a dynamic threshold comprises the following components: the system comprises a retrieval database 1, a dynamic threshold testing module 2 and a retrieval module 3.
The dynamic threshold test module 2 is configured to test the search database 1 and form a dynamic threshold of the search database 1.
And the retrieval module 3 retrieves the retrieval database 1 according to the retrieval request, and forms a retrieval result according to the dynamic threshold value in the retrieval process.
The search database 1 includes a plurality of search databases, and the structural characteristics of each search database 1 include data distribution and data size. The data distribution of the search database 1 includes a distribution formed by data from different sources, for example, data from different provinces. The retrieval database 1 can be used as a control library for face recognition, a plurality of face information are stored in the retrieval database 1, and the retrieval module 3 receives the retrieved face information while receiving the retrieval request. The retrieved face information is input through a controlled camera, and the retrieved face information can also be manually input. Wherein, the manual input can input text information; the input of the camera through control is to input graphic information, and the graphic information needs to be subjected to feature extraction through an identification module and converted into text information.
The structural features of the data distribution and data scale of the search database 1 have dynamically changing features, such as: the data source corresponding to the data distribution can be continuously expanded, so that the data distribution is wider and wider; the data scale is also expanded continuously, so that the data scale is larger and larger; and vice versa.
The dynamic threshold of the search database 1 is adaptively and dynamically changed according to the structural feature change of the search database 1.
The dynamic threshold test module 2 obtains the dynamic threshold by detecting the structural features of the search database 1.
After receiving the retrieval request, the retrieval module 3 firstly detects all preliminary retrieval results by a similarity comparison method and sorts the preliminary retrieval results, and then filters the preliminary retrieval results by using the dynamic threshold to obtain the retrieval results, wherein the filtering is to use the preliminary retrieval results with retrieval values higher than the dynamic threshold as the retrieval results.
Fig. 2 is a flowchart illustrating the dynamic threshold value test module in the search system according to an embodiment of the present invention calculating the dynamic threshold value. The dynamic threshold testing module 2 forms the dynamic threshold by adopting the following steps:
and inquiring the structural feature information of the retrieval database 1.
And carrying out retrieval test on the retrieval database 1 based on the structural characteristic information, wherein a series of test thresholds are adopted in the retrieval test, and different test thresholds obtain corresponding false alarm rates to form a one-to-one corresponding relation between the test thresholds and the false alarm rates.
And calculating the required accuracy rate when searching is carried out based on the structural characteristics and calculating the corresponding required false alarm rate based on the accuracy rate.
And taking the test threshold corresponding to the required false alarm rate as the dynamic threshold.
In other embodiments can also be: providing the retrieval database corresponding to a series of structural features in advance, and then testing the dynamic threshold corresponding to each structural feature according to the above process to form a dynamic threshold table; then, in the actual retrieval process, the dynamic threshold test module 2 only needs to detect the structural feature information of the retrieval database, and select the corresponding dynamic threshold from the dynamic threshold table according to the structural feature obtained by detection.
The embodiment of the invention is provided with the dynamic threshold testing module 2 in the retrieval system, the dynamic threshold of the retrieval database 1 can be detected by the dynamic threshold testing module 2, and the retrieval result is formed and output by adopting the dynamic threshold in the retrieval process, so that the embodiment of the invention can realize that the threshold dynamically follows the structural characteristic change of the retrieval database 1, and when the structural characteristic of the retrieval database 1 changes, such as the data distribution, the data scale and the like, the embodiment of the invention can still realize accurate output, thereby improving the retrieval stability.
The retrieval method provided by the embodiment of the invention comprises the following steps of:
step one, providing a dynamic threshold value testing module 2, testing a retrieval database 1 by using the dynamic threshold value testing module 2 and forming a dynamic threshold value table of the retrieval database 1.
The search database 1 includes a plurality of search databases, and the structural characteristics of each search database 1 include data distribution and data size. The data distribution of the search database 1 includes a distribution formed by data from different sources, for example, data from different provinces. The retrieval database 1 can be used as a control database for face recognition, a plurality of face information are stored in the retrieval database 1, and the retrieval module 3 receives the retrieved face information while receiving the retrieval request. The retrieved face information is input through a controlled camera, and the retrieved face information can also be input manually. Wherein, the manual input can input text information; the input of the camera through control is to input graphic information, and the graphic information needs to be subjected to feature extraction through an identification module and converted into text information.
The structural features of the data distribution and data scale of the search database 1 have dynamically changing features, such as: the data source corresponding to the data distribution can be continuously expanded, so that the data distribution is wider and wider; the data scale is also expanded continuously, so that the data scale is larger and larger; and vice versa.
The dynamic threshold of the search database 1 is adaptively and dynamically changed according to the structural feature change of the search database 1.
The dynamic threshold test module 2 obtains the dynamic threshold by detecting the structural features of the search database 1.
Fig. 2 is a flowchart illustrating the dynamic threshold value test module in the search system according to an embodiment of the present invention calculating the dynamic threshold value. The dynamic threshold testing module 2 forms the dynamic threshold by adopting the following steps:
and inquiring the structural feature information of the retrieval database 1.
And carrying out retrieval test on the retrieval database 1 based on the structural characteristic information, wherein a series of test thresholds are adopted in the retrieval test, and different test thresholds obtain corresponding false alarm rates to form a one-to-one corresponding relation between the test thresholds and the false alarm rates.
And calculating the required accuracy rate when searching is carried out based on the structural characteristics and calculating the corresponding required false alarm rate based on the accuracy rate.
And taking the test threshold corresponding to the required false alarm rate as the dynamic threshold.
In other embodiments can also be: providing the retrieval database corresponding to a series of structural features in advance, and then testing the dynamic threshold corresponding to each structural feature according to the above process to form a dynamic threshold table; then, in the actual retrieval process, the dynamic threshold test module 2 only needs to detect the structural feature information of the retrieval database, and select the corresponding dynamic threshold from the dynamic threshold table according to the structural feature obtained by detection.
And step two, the retrieval module 3 retrieves the retrieval database 1 according to the retrieval request, and forms a retrieval result according to the dynamic threshold value in the retrieval process.
Preferably, after receiving the search request, the search module 3 first detects all preliminary search results by a similarity comparison method and sorts the preliminary search results, and then filters the preliminary search results by using the dynamic threshold to obtain the search results, where the filtering is to use the preliminary search results with a search value higher than the dynamic threshold as the search results.
The present invention has been described in detail with reference to the specific embodiments, but these should not be construed as limitations of the present invention. Many variations and modifications may be made by one of ordinary skill in the art without departing from the principles of the present invention, which should also be considered as within the scope of the present invention.
Claims (12)
1. A retrieval system for maintaining stable performance in a deployed library through dynamic thresholds, comprising: the system comprises a retrieval database, a dynamic threshold testing module and a retrieval module;
the dynamic threshold test module is used for testing the retrieval database and forming a dynamic threshold of the retrieval database;
the retrieval module retrieves the retrieval database according to the retrieval request, and a retrieval result is formed according to the dynamic threshold in the retrieval process;
the structural characteristics of the retrieval database comprise data distribution and data scale;
the dynamic threshold value of the retrieval database is adaptively and dynamically changed according to the structural feature change of the retrieval database;
the structural characteristics of the data distribution and the data scale of the retrieval database have the characteristics of dynamic change;
the dynamic threshold testing module obtains the dynamic threshold by detecting the structural characteristics of the retrieval database;
the dynamic threshold testing module forms the dynamic threshold by adopting the following steps:
inquiring the structural feature information of the retrieval database;
carrying out retrieval test on the retrieval database based on the structural feature information, wherein a series of test thresholds are adopted in the retrieval test, and different test thresholds obtain corresponding false alarm rates to form a one-to-one corresponding relation between the test thresholds and the false alarm rates;
calculating the required accuracy rate when searching is carried out based on the structural features and calculating the corresponding required false alarm rate based on the accuracy rate;
and taking the test threshold corresponding to the required false alarm rate as the dynamic threshold.
2. The retrieval system of claim 1, wherein: the retrieval database includes a plurality of databases.
3. A retrieval system as claimed in claim 2, wherein: the data distribution of the search database includes a distribution formed by data from different sources.
4. A retrieval system as recited in claim 3, wherein: after receiving the retrieval request, the retrieval module firstly detects all preliminary retrieval results through a similarity comparison method and sorts the preliminary retrieval results, and then filters the preliminary retrieval results by adopting the dynamic threshold to obtain the retrieval results, wherein the filtering is to take the preliminary retrieval results with retrieval values higher than the dynamic threshold as the retrieval results.
5. The retrieval system of claim 1, wherein: the retrieval database is a control database for face recognition, a plurality of face information are stored in the retrieval database, and the retrieval module receives the retrieval request and the retrieved face information at the same time.
6. The retrieval system of claim 5, wherein: and the retrieved face information is input through the arranged camera.
7. A retrieval method for keeping stable performance in a deployment control library through a dynamic threshold is characterized by comprising the following steps:
providing a dynamic threshold testing module, testing a retrieval database by using the dynamic threshold testing module and forming a dynamic threshold table of the retrieval database;
secondly, the retrieval module retrieves the retrieval database according to the retrieval request, and a retrieval result is formed according to the dynamic threshold in the retrieval process;
the structural characteristics of the retrieval database comprise data distribution and data scale;
the dynamic threshold value of the retrieval database is adaptively and dynamically changed according to the structural feature change of the retrieval database;
the structural characteristics of the data distribution and the data scale of the retrieval database have the characteristics of dynamic change;
the dynamic threshold testing module obtains the dynamic threshold by detecting the structural characteristics of the retrieval database;
the dynamic threshold testing module forms the dynamic threshold by adopting the following steps:
inquiring the structural feature information of the retrieval database;
carrying out retrieval test on the retrieval database based on the structural feature information, wherein a series of test thresholds are adopted in the retrieval test, and different test thresholds obtain corresponding false alarm rates to form a one-to-one corresponding relation between the test thresholds and the false alarm rates;
calculating the required accuracy rate when searching is carried out based on the structural features and calculating the corresponding required false alarm rate based on the accuracy rate;
and taking the test threshold corresponding to the required false alarm rate as the dynamic threshold.
8. The retrieval method of claim 7, wherein: the retrieval database includes a plurality of databases.
9. The retrieval method of claim 8, wherein: the data distribution of the search database includes a distribution formed by data from different sources.
10. The retrieval method of claim 8, wherein: after receiving the retrieval request, the retrieval module firstly detects all preliminary retrieval results through a similarity comparison method and sorts the preliminary retrieval results, and then filters the preliminary retrieval results by adopting the dynamic threshold to obtain the retrieval results, wherein the filtering is to take the preliminary retrieval results with retrieval values higher than the dynamic threshold as the retrieval results.
11. The retrieval method of claim 7, wherein: the retrieval database is a control database for face recognition, a plurality of face information are stored in the retrieval database, and the retrieval module receives the retrieval request and the retrieved face information at the same time.
12. The retrieval method of claim 11, wherein: and the retrieved face information is input through the controlled camera.
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