CN111428544B - Scene recognition method and device, electronic equipment and storage medium - Google Patents
Scene recognition method and device, electronic equipment and storage medium Download PDFInfo
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- CN111428544B CN111428544B CN201910022938.6A CN201910022938A CN111428544B CN 111428544 B CN111428544 B CN 111428544B CN 201910022938 A CN201910022938 A CN 201910022938A CN 111428544 B CN111428544 B CN 111428544B
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/10—Terrestrial scenes
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/23—Clustering techniques
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management
Abstract
The embodiment of the invention discloses a scene recognition method, a scene recognition device, electronic equipment and a storage medium. The method comprises the following steps: acquiring at least one peripheral picture of a current user; identifying current wear meta-information corresponding to each wear type according to the at least one peripheral picture and a preset wear degree value corresponding to each wear type; and determining the use scene of the current user according to the current wear meta-information corresponding to each wear type and the preset wear cluster value of each use scene. Not only can the daily use scene of user be accurately identified, but also new use scene of user can be conveniently expanded, the defects of scene singleness and scene limitation are effectively avoided, and the application scene is richer.
Description
Technical Field
The embodiment of the invention relates to the technical field of Internet, in particular to a scene recognition method, a scene recognition device, electronic equipment and a storage medium.
Background
With the continuous popularization of information technology, electronic devices such as computers have become an indispensable ring in daily life. People use various marks left by a computer, such as abrasion marks on a keyboard, a mouse and other peripheral devices, and the abrasion marks can represent different use scenes of users. Thus, from these wear marks, very much valuable information can be mined, such as which software the user uses frequently, how often functions are used, how often, etc. Through a combination of these information, which can be used as the basis data for portrayal of a user, such a function is very useful in analyzing the scenes of the daily behavior and characteristics of criminal suspects.
In the prior art, some application software has self-contained statistical functions to mine services potentially needed by users, such as news software can record what type of news the users click on, and then such software recommends the same or similar type of information more frequently. However, such statistical functions are generally only suitable for the current application, so that the applicable scenario of such statistical functions is very single and has no universality.
Disclosure of Invention
In view of the above, the embodiment of the invention provides a scene recognition method, a device, an electronic device and a storage medium, which not only can accurately recognize the daily use scene of a user, but also can conveniently expand the new use scene of the user, effectively avoid the defects of single scene and limited scene, and are more suitable for scenes.
In a first aspect, an embodiment of the present invention provides a scene recognition method, where the method includes:
acquiring at least one peripheral picture of a current user;
identifying current wear meta-information corresponding to each wear type according to the at least one peripheral picture and a preset wear degree value corresponding to each wear type;
And determining the use scene of the current user according to the current wear meta-information corresponding to each wear type and the preset wear cluster value of each use scene.
In the foregoing embodiment, the identifying, according to the at least one peripheral image, current wear meta-information corresponding to each wear type includes:
identifying the current wear degree value corresponding to each wear type according to the at least one peripheral picture;
and calculating the current abrasion meta-information corresponding to each abrasion type according to the current abrasion degree value corresponding to each abrasion type and the preset abrasion degree value corresponding to each abrasion type.
In the foregoing embodiment, the identifying, according to the at least one peripheral image, the current wear level value corresponding to the respective wear type includes:
performing fuzzy recognition on each peripheral picture to obtain a fuzzy position area and a fuzzy degree value of each peripheral picture; performing damage identification on each peripheral picture, and acquiring a damage position area and a damage degree value of each peripheral picture; carrying out reflection recognition on each peripheral picture to obtain a reflection position area and a reflection degree value of each peripheral picture;
Determining a current wear degree value corresponding to each wear type according to the fuzzy position area and the fuzzy degree value of each peripheral picture; or determining the current wear degree value corresponding to each wear type according to the damage position area and the damage degree value of each peripheral picture; or determining the current wear degree value corresponding to each wear type according to the reflective position area and the reflective degree value of each peripheral picture; or determining the current wear degree value corresponding to each wear type according to the fuzzy position area and the fuzzy degree value, and the damage position area and the damage degree value of each peripheral picture; or determining the current wear degree value corresponding to each wear type according to the fuzzy position area and the fuzzy degree value, and the reflective position area and the reflective degree value of each peripheral picture; or determining the current wear degree value corresponding to each wear type according to the damage position area and the damage degree value, and the reflection position area and the reflection degree value of each peripheral picture; or determining the current wear degree value corresponding to each wear type according to the fuzzy position area and the fuzzy degree value, the damage position area and the damage degree value, and the reflective position area and the reflective degree value of each peripheral image.
In the foregoing embodiment, the determining, according to the current wear meta information corresponding to each wear type and the preset wear cluster value of each usage scenario, the usage scenario of the current user includes:
calculating the matching value of the current wear meta-information corresponding to all the wear types and each use scene according to the current wear meta-information corresponding to each wear type and the preset wear cluster value of each use scene;
and determining the use scene of the current user according to the matching values of the current wear meta-information corresponding to all the wear types and each use scene.
In the foregoing embodiment, the calculating, according to the current wear meta-information corresponding to each wear type and the preset wear cluster value of each usage scenario, a matching value of the current wear meta-information corresponding to all wear types and each usage scenario includes:
calculating current wear cluster values corresponding to all the wear types according to the current wear meta-information corresponding to each wear type and the predetermined weight corresponding to each wear type;
and calculating the matching value of the current abrasion meta-information corresponding to all the abrasion types and each use scene according to the current abrasion cluster value corresponding to all the abrasion types and the preset abrasion cluster value of each use scene.
In a second aspect, an embodiment of the present invention provides a scene recognition apparatus, including: the device comprises an acquisition module, an identification module and a determination module; wherein, the liquid crystal display device comprises a liquid crystal display device,
the acquisition module is used for acquiring at least one peripheral picture of the current user;
the identification module is used for identifying current abrasion meta-information corresponding to each abrasion type according to the at least one peripheral picture and a preset abrasion degree value corresponding to each abrasion type;
and the determining module is used for determining the use scene of the current user according to the current wear meta information corresponding to each wear type and the preset wear cluster value of each use scene.
In the foregoing embodiment, the identifying module is specifically configured to identify, according to the at least one peripheral image, a current wear level value corresponding to each wear type; and calculating the current abrasion meta-information corresponding to each abrasion type according to the current abrasion degree value corresponding to each abrasion type and the preset abrasion degree value corresponding to each abrasion type.
In the foregoing embodiment, the identification module is specifically configured to perform fuzzy identification on each peripheral image, and obtain a fuzzy position area and a fuzzy degree value of each peripheral image; performing damage identification on each peripheral picture, and acquiring a damage position area and a damage degree value of each peripheral picture; carrying out reflection recognition on each peripheral picture to obtain a reflection position area and a reflection degree value of each peripheral picture; determining a current wear degree value corresponding to each wear type according to the fuzzy position area and the fuzzy degree value of each peripheral picture; or determining the current wear degree value corresponding to each wear type according to the damage position area and the damage degree value of each peripheral picture; or determining the current wear degree value corresponding to each wear type according to the reflective position area and the reflective degree value of each peripheral picture; or determining the current wear degree value corresponding to each wear type according to the fuzzy position area and the fuzzy degree value, and the damage position area and the damage degree value of each peripheral picture; or determining the current wear degree value corresponding to each wear type according to the fuzzy position area and the fuzzy degree value, and the reflective position area and the reflective degree value of each peripheral picture; or determining the current wear degree value corresponding to each wear type according to the damage position area and the damage degree value, and the reflection position area and the reflection degree value of each peripheral picture; or determining the current wear degree value corresponding to each wear type according to the fuzzy position area and the fuzzy degree value, the damage position area and the damage degree value, and the reflective position area and the reflective degree value of each peripheral image.
In the above embodiment, the determining module includes: a calculation submodule and a determination submodule; wherein, the liquid crystal display device comprises a liquid crystal display device,
the calculating submodule is used for calculating matching values of the current wear meta-information corresponding to all the wear types and each use scene according to the current wear meta-information corresponding to each wear type;
and the determining submodule is used for determining the use scene of the current user according to the matching values of the current wear meta information corresponding to all the wear types and the use scenes.
In the foregoing embodiment, the calculating submodule is specifically configured to calculate, according to the current wear meta information corresponding to each wear type and a predetermined weight corresponding to each wear type, a current wear cluster value corresponding to all wear types; and calculating the matching value of the current abrasion meta-information corresponding to all the abrasion types and each use scene according to the current abrasion cluster value corresponding to all the abrasion types and the preset abrasion cluster value of each use scene.
In a third aspect, an embodiment of the present invention provides an electronic device, including:
one or more processors;
a memory for storing one or more programs,
The one or more programs, when executed by the one or more processors, cause the one or more processors to implement the scene recognition method described in any of the embodiments of the present invention.
In a fourth aspect, an embodiment of the present invention provides a storage medium having stored thereon a computer program which, when executed by a processor, implements the scene recognition method according to any embodiment of the present invention.
The embodiment of the invention provides a scene recognition method, a scene recognition device, electronic equipment and a storage medium, wherein at least one peripheral picture of a current user is acquired firstly; then, according to at least one peripheral picture and preset wear degree values corresponding to each wear type, identifying current wear meta-information corresponding to each wear type; and determining the use scene of the current user according to the current wear meta-information corresponding to each wear type and the preset wear cluster value of each use scene. That is, in the technical scheme of the present invention, the current wear meta-information corresponding to each wear type can be identified according to at least one peripheral picture and the preset wear degree value corresponding to each wear type; and determining the use scene of the current user according to the current wear meta-information corresponding to each wear type and the preset wear cluster value of each use scene. In the existing scene recognition method, although some application software has a self-contained statistical function to mine services potentially required by users, the statistical function can only be generally adapted to the current application, so that the applicable scene of the statistical function is very single and has no universality. Therefore, compared with the prior art, the scene recognition method, the device, the electronic equipment and the storage medium provided by the embodiment of the invention not only can accurately recognize the daily use scene of the user, but also can conveniently expand the new use scene of the user, effectively avoid the defects of single scene and limitation of the scene, and are more suitable for the scene; in addition, the technical scheme of the embodiment of the invention is simple and convenient to realize, convenient to popularize and wider in application range.
Drawings
Fig. 1 is a flowchart of a scene recognition method according to a first embodiment of the present invention;
fig. 2 is a flowchart of a scene recognition method according to a second embodiment of the present invention;
fig. 3 is a flowchart of a scene recognition method according to a third embodiment of the present invention;
fig. 4 is a first schematic structural diagram of a scene recognition device according to a fourth embodiment of the present invention;
fig. 5 is a second schematic structural diagram of a scene recognition device according to a fourth embodiment of the present invention;
fig. 6 is a schematic structural diagram of an electronic device according to a fifth embodiment of the present invention.
Detailed Description
The invention is described in further detail below with reference to the drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting thereof. It should be further noted that, for convenience of description, only some, but not all of the matters related to the present invention are shown in the accompanying drawings.
Example 1
Fig. 1 is a flowchart of a scene recognition method according to an embodiment of the present invention. The method may be performed by a scene recognition device or electronic equipment, which may be implemented in software and/or hardware, and which may be integrated in any intelligent device having network communication functionality. As shown in fig. 1, the scene recognition method may include the steps of:
S101, acquiring at least one peripheral picture of a current user.
In a specific embodiment of the present invention, the electronic device may obtain at least one peripheral picture of the current user. Specifically, the electronic device may obtain a keyboard picture of the current user; or the electronic equipment can also acquire the mouse picture of the current user; or the electronic equipment can also acquire the sound box picture of the current user; alternatively, the electronic device may also obtain a headset picture of the current user, etc.
S102, identifying current abrasion meta-information corresponding to each abrasion type according to at least one peripheral picture and a preset abrasion degree value corresponding to each abrasion type.
In a specific embodiment of the present invention, the electronic device may identify current wear meta-information corresponding to each wear type according to at least one peripheral image and a preset wear level value corresponding to each wear type. Specifically, the electronic device may define N wear types in advance, including: wear type 1, wear type 2, … wear type N; wherein N is a natural number greater than or equal to 1. For example, a keycap blur type wear, a keycap reflection type wear, a keycap damage type wear, a mouse scratch type wear, a mouse damage type wear, and the like. In this step, the electronic device may identify, according to at least one peripheral image, a current wear level value corresponding to each wear type; and then calculating the current wear meta-information corresponding to each wear type according to the current wear degree value corresponding to each wear type and the preset wear degree value corresponding to each wear type.
S103, determining the use scene of the current user according to the current wear meta-information corresponding to each wear type and the preset wear cluster value of each use scene.
In a specific embodiment of the present invention, the electronic device may determine a usage scenario of the current user according to the current wear meta information corresponding to each wear type and a preset wear cluster value of each usage scenario. Specifically, the electronic device may calculate, according to the current wear meta information corresponding to each wear type and the preset wear cluster value of each usage scenario, a matching value of the current wear meta information corresponding to all wear types and each usage scenario; and then determining the use scene of the current user according to the matching values of the current wear meta-information corresponding to all the wear types and each use scene.
The scene recognition method provided by the embodiment of the invention comprises the steps of firstly, acquiring at least one peripheral picture of a current user; then, according to at least one peripheral picture and preset wear degree values corresponding to each wear type, identifying current wear meta-information corresponding to each wear type; and determining the use scene of the current user according to the current wear meta-information corresponding to each wear type and the preset wear cluster value of each use scene. That is, in the technical scheme of the present invention, the current wear meta-information corresponding to each wear type can be identified according to at least one peripheral picture and the preset wear degree value corresponding to each wear type; and determining the use scene of the current user according to the current wear meta-information corresponding to each wear type and the preset wear cluster value of each use scene. In the existing scene recognition method, although some application software has a self-contained statistical function to mine services potentially required by users, the statistical function can only be generally adapted to the current application, so that the applicable scene of the statistical function is very single and has no universality. Therefore, compared with the prior art, the scene recognition method provided by the embodiment of the invention not only can accurately recognize the daily use scene of the user, but also can conveniently expand the new use scene of the user, effectively avoid the defects of single scene and scene limitation, and is more suitable for scenes; in addition, the technical scheme of the embodiment of the invention is simple and convenient to realize, convenient to popularize and wider in application range.
Example two
Fig. 2 is a flowchart of a scene recognition method according to a second embodiment of the present invention. As shown in fig. 2, the scene recognition method may include:
s201, at least one peripheral picture of the current user is acquired.
In a specific embodiment of the present invention, the electronic device may obtain at least one peripheral picture of the current user. Specifically, the electronic device may obtain a keyboard picture of the current user; or the electronic equipment can also acquire the mouse picture of the current user; or the electronic equipment can also acquire the sound box picture of the current user; alternatively, the electronic device may also obtain a headset picture of the current user, etc.
S202, identifying the current wear degree value corresponding to each wear type according to at least one peripheral picture.
In a specific embodiment of the present invention, the electronic device may identify, according to at least one peripheral image, a current wear level value corresponding to each wear type. Specifically, the electronic device may perform fuzzy recognition on each peripheral image, and obtain a fuzzy position area and a fuzzy degree value of each peripheral image; the damage identification can be carried out on each peripheral picture, and the damage position area and the damage degree value of each peripheral picture are obtained; the reflection identification can be carried out on each peripheral picture, and the reflection position area and the reflection degree value of each peripheral picture are obtained; and then determining the current wear degree value corresponding to each wear type according to the fuzzy position area and the fuzzy degree value, the damage position area and the damage degree value, and the reflective position area and the reflective degree value of each peripheral picture. Specifically, the electronic device may identify, according to at least one peripheral image, a current wear level value 1 corresponding to the wear type 1; the electronic equipment can also identify the current wear degree value 2 corresponding to the wear type 2 according to at least one peripheral picture; and so on; the electronic device may further identify a current wear level value N corresponding to the wear type N according to the at least one peripheral image.
S203, calculating current abrasion meta-information corresponding to each abrasion type according to the current abrasion degree value corresponding to each abrasion type and the preset abrasion degree value corresponding to each abrasion type.
In a specific embodiment of the present invention, the electronic device may calculate the current wear meta-information corresponding to each wear type according to the current wear degree value corresponding to each wear type and the preset wear degree value corresponding to each wear type. Specifically, the electronic device may input the current wear degree value corresponding to each wear type and the preset wear degree value corresponding to each wear type into a predetermined calculation model, and the calculation model may output the current wear meta-information corresponding to each wear type. Specifically, the electronic device may calculate, according to the current wear degree value 1 and a preset wear degree value 1 corresponding to the wear type 1, current wear meta-information 1 corresponding to the wear type 1; the electronic equipment can also calculate the current abrasion meta-information 2 corresponding to the abrasion type 2 according to the current abrasion degree value 2 and the preset abrasion degree value 2 corresponding to the abrasion type 2; and so on; the electronic device may further calculate current wear meta-information N corresponding to the wear type N according to the current wear degree value N and a preset wear degree value N corresponding to the wear type N.
S204, determining the use scene of the current user according to the current wear meta-information corresponding to each wear type and the preset wear cluster value of each use scene.
In a specific embodiment of the present invention, the electronic device may determine a usage scenario of the current user according to the current wear meta information corresponding to each wear type and a preset wear cluster value of each usage scenario. Specifically, the electronic device may calculate, according to the current wear meta information corresponding to each wear type and the preset wear cluster value of each usage scenario, a matching value of the current wear meta information corresponding to all wear types and each usage scenario; and then determining the use scene of the current user according to the matching values of the current wear meta-information corresponding to all the wear types and each use scene. Specifically, the electronic device may calculate current wear cluster values corresponding to all wear types according to current wear meta information corresponding to each wear type and a predetermined weight corresponding to each wear type; and then calculating the matching value of the current wear meta-information corresponding to all the wear types and each use scene according to the current wear cluster value corresponding to all the wear types and the preset wear cluster value of each use scene.
The scene recognition method provided by the embodiment of the invention comprises the steps of firstly, acquiring at least one peripheral picture of a current user; then, according to at least one peripheral picture and preset wear degree values corresponding to each wear type, identifying current wear meta-information corresponding to each wear type; and determining the use scene of the current user according to the current wear meta-information corresponding to each wear type and the preset wear cluster value of each use scene. That is, in the technical scheme of the present invention, the current wear meta-information corresponding to each wear type can be identified according to at least one peripheral picture and the preset wear degree value corresponding to each wear type; and determining the use scene of the current user according to the current wear meta-information corresponding to each wear type and the preset wear cluster value of each use scene. In the existing scene recognition method, although some application software has a self-contained statistical function to mine services potentially required by users, the statistical function can only be generally adapted to the current application, so that the applicable scene of the statistical function is very single and has no universality. Therefore, compared with the prior art, the scene recognition method provided by the embodiment of the invention not only can accurately recognize the daily use scene of the user, but also can conveniently expand the new use scene of the user, effectively avoid the defects of single scene and scene limitation, and is more suitable for scenes; in addition, the technical scheme of the embodiment of the invention is simple and convenient to realize, convenient to popularize and wider in application range.
Example III
Fig. 3 is a flowchart of a scene recognition method according to a third embodiment of the present invention. As shown in fig. 3, the scene recognition method may include:
s301, acquiring at least one peripheral picture of a current user.
In a specific embodiment of the present invention, the electronic device may obtain at least one peripheral picture of the current user. Specifically, the electronic device may obtain a keyboard picture of the current user; or the electronic equipment can also acquire the mouse picture of the current user; or the electronic equipment can also acquire the sound box picture of the current user; alternatively, the electronic device may also obtain a headset picture of the current user, etc.
S302, identifying the current wear degree value corresponding to each wear type according to at least one peripheral picture.
In a specific embodiment of the present invention, the electronic device may identify, according to at least one peripheral image, a current wear level value corresponding to each wear type. Specifically, the electronic device may perform fuzzy recognition on each peripheral image, and obtain a fuzzy position area and a fuzzy degree value of each peripheral image; the damage identification can be carried out on each peripheral picture, and the damage position area and the damage degree value of each peripheral picture are obtained; the reflection identification can be carried out on each peripheral picture, and the reflection position area and the reflection degree value of each peripheral picture are obtained; then determining the current wear degree value corresponding to each wear type according to the fuzzy position area and the fuzzy degree value of each peripheral picture; or determining the current wear degree value corresponding to each wear type according to the damage position area and the damage degree value of each peripheral picture; or determining the current wear degree value corresponding to each wear type according to the reflective position area and the reflective degree value of each peripheral picture; or determining the current wear degree value corresponding to each wear type according to the fuzzy position area and the fuzzy degree value, and the damage position area and the damage degree value of each peripheral picture; or determining the current wear degree value corresponding to each wear type according to the fuzzy position area and the fuzzy degree value, and the reflective position area and the reflective degree value of each peripheral picture; or determining the current wear degree value corresponding to each wear type according to the damage position area and the damage degree value of each peripheral picture and the light reflection position area and the light reflection degree value; or determining the current wear degree value corresponding to each wear type according to the fuzzy position area and the fuzzy degree value, the damage position area and the damage degree value, and the reflective position area and the reflective degree value of each peripheral picture. Specifically, the electronic device may identify, according to at least one peripheral image, a current wear level value 1 corresponding to the wear type 1; the electronic equipment can also identify the current wear degree value 2 corresponding to the wear type 2 according to at least one peripheral picture; and so on; the electronic device may further identify a current wear level value N corresponding to the wear type N according to the at least one peripheral image.
S303, calculating current abrasion meta-information corresponding to each abrasion type according to the current abrasion degree value corresponding to each abrasion type and the preset abrasion degree value corresponding to each abrasion type.
In a specific embodiment of the present invention, the electronic device may calculate the current wear meta-information corresponding to each wear type according to the current wear degree value corresponding to each wear type and the preset wear degree value corresponding to each wear type. Specifically, the electronic device may input the current wear degree value corresponding to each wear type and the preset wear degree value corresponding to each wear type into a predetermined calculation model, and the calculation model may output the current wear meta-information corresponding to each wear type. Specifically, the electronic device may calculate, according to the current wear degree value 1 and a preset wear degree value 1 corresponding to the wear type 1, current wear meta-information 1 corresponding to the wear type 1; the electronic equipment can also calculate the current abrasion meta-information 2 corresponding to the abrasion type 2 according to the current abrasion degree value 2 and the preset abrasion degree value 2 corresponding to the abrasion type 2; and so on; the electronic device may further calculate current wear meta-information N corresponding to the wear type N according to the current wear degree value N and a preset wear degree value N corresponding to the wear type N.
S304, calculating the matching value of the current abrasion meta-information corresponding to all abrasion types and each usage scene according to the current abrasion meta-information corresponding to each abrasion type and the preset abrasion cluster value of each usage scene.
In a specific embodiment of the present invention, the electronic device may calculate, according to the current wear meta information corresponding to each wear type and the preset wear cluster value of each usage scenario, a matching value of the current wear meta information corresponding to all the wear types and each usage scenario. Specifically, the electronic device may calculate current wear cluster values corresponding to all wear types according to current wear meta information corresponding to each wear type and weights corresponding to each wear type; and then calculating the matching value of the current wear meta-information corresponding to all the wear types and each use scene according to the current wear cluster value corresponding to all the wear types and the preset wear cluster value of each use scene. Specifically, the electronic device may input the current wear cluster value corresponding to all the wear types and the preset wear cluster value of each usage scenario into a predetermined matching model, and may calculate the matching value of the current wear meta-information corresponding to all the wear types and each usage scenario through the matching model.
S305, determining the use scene of the current user according to the matching values of the current wear meta information corresponding to all the wear types and each use scene.
In a specific embodiment of the present invention, the electronic device may determine a usage scenario of the current user according to a matching value between the current wear meta information corresponding to all the wear types and each usage scenario. For example, if the matching value of the current wear meta information corresponding to all the wear types and the usage scenario 1 is greater than a preset threshold, the electronic device may determine that the usage scenario of the current user is the usage scenario 1; for another example, if the matching value of the current wear meta information corresponding to all the wear types and the usage scenario 2 is greater than the preset threshold, the electronic device may determine that the usage scenario of the current user is the usage scenario 2.
The scene recognition method provided by the embodiment of the invention comprises the steps of firstly, acquiring at least one peripheral picture of a current user; then, according to at least one peripheral picture and preset wear degree values corresponding to each wear type, identifying current wear meta-information corresponding to each wear type; and determining the use scene of the current user according to the current wear meta-information corresponding to each wear type and the preset wear cluster value of each use scene. That is, in the technical scheme of the present invention, the current wear meta-information corresponding to each wear type can be identified according to at least one peripheral picture and the preset wear degree value corresponding to each wear type; and determining the use scene of the current user according to the current wear meta-information corresponding to each wear type and the preset wear cluster value of each use scene. In the existing scene recognition method, although some application software has a self-contained statistical function to mine services potentially required by users, the statistical function can only be generally adapted to the current application, so that the applicable scene of the statistical function is very single and has no universality. Therefore, compared with the prior art, the scene recognition method provided by the embodiment of the invention not only can accurately recognize the daily use scene of the user, but also can conveniently expand the new use scene of the user, effectively avoid the defects of single scene and scene limitation, and is more suitable for scenes; in addition, the technical scheme of the embodiment of the invention is simple and convenient to realize, convenient to popularize and wider in application range.
Example IV
Fig. 4 is a schematic diagram of a first structure of a scene recognition device according to a fourth embodiment of the present invention. As shown in fig. 4, a scene recognition device according to an embodiment of the present invention includes: an acquisition module 401, an identification module 402, and a determination module 403; wherein, the liquid crystal display device comprises a liquid crystal display device,
the acquiring module 401 is configured to acquire at least one peripheral image of a current user;
the identifying module 402 is configured to identify current wear meta-information corresponding to each wear type according to the at least one peripheral image and a preset wear level value corresponding to each wear type;
the determining module 403 is configured to determine a usage scenario of the current user according to the current wear meta information corresponding to each wear type and a preset wear cluster value of each usage scenario.
Further, the identifying module 402 is specifically configured to identify, according to the at least one peripheral image, a current wear level value corresponding to each wear type; and calculating the current abrasion meta-information corresponding to each abrasion type according to the current abrasion degree value corresponding to each abrasion type and the preset abrasion degree value corresponding to each abrasion type.
Further, the identifying module 402 is specifically configured to perform fuzzy identification on the peripheral pictures, and obtain fuzzy position areas and fuzzy degree values of the peripheral pictures; performing damage identification on each peripheral picture, and acquiring a damage position area and a damage degree value of each peripheral picture; carrying out reflection recognition on each peripheral picture to obtain a reflection position area and a reflection degree value of each peripheral picture; determining a current wear degree value corresponding to each wear type according to the fuzzy position area and the fuzzy degree value of each peripheral picture; or determining the current wear degree value corresponding to each wear type according to the damage position area and the damage degree value of each peripheral picture; or determining the current wear degree value corresponding to each wear type according to the reflective position area and the reflective degree value of each peripheral picture; or determining the current wear degree value corresponding to each wear type according to the fuzzy position area and the fuzzy degree value, and the damage position area and the damage degree value of each peripheral picture; or determining the current wear degree value corresponding to each wear type according to the fuzzy position area and the fuzzy degree value, and the reflective position area and the reflective degree value of each peripheral picture; or determining the current wear degree value corresponding to each wear type according to the damage position area and the damage degree value, and the reflection position area and the reflection degree value of each peripheral picture; or determining the current wear degree value corresponding to each wear type according to the fuzzy position area and the fuzzy degree value, the damage position area and the damage degree value, and the reflective position area and the reflective degree value of each peripheral image.
Fig. 5 is a second schematic structural diagram of a scene recognition device according to a fourth embodiment of the present invention. As shown in fig. 5, the determining module 403 includes: a calculation submodule 4031 and a determination submodule 4032; wherein, the liquid crystal display device comprises a liquid crystal display device,
the calculating submodule 4031 is configured to calculate a matching value of the current wear meta information corresponding to all wear types and each usage scenario according to the current wear meta information corresponding to each wear type and the preset wear cluster value of each usage scenario;
the determining submodule 4032 is configured to determine a usage scenario of the current user according to a matching value of the current wear meta information corresponding to each wear type and each usage scenario.
Further, the calculating submodule 4031 is specifically configured to calculate current wear cluster values corresponding to all wear types according to the current wear meta information corresponding to each wear type and a predetermined weight corresponding to each wear type; and calculating the matching value of the current abrasion meta-information corresponding to all the abrasion types and each use scene according to the current abrasion cluster value corresponding to all the abrasion types and the preset abrasion cluster value of each use scene.
The scene recognition device can execute the scene recognition method provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method. Technical details which are not described in detail in this embodiment can be referred to the scene recognition method provided in any embodiment of the present invention.
Example five
Fig. 6 is a schematic diagram of a composition structure of an electronic device according to a fifth embodiment of the present invention. Fig. 6 shows a block diagram of an exemplary electronic device suitable for use in implementing embodiments of the invention. The electronic device 12 shown in fig. 6 is merely an example and should not be construed as limiting the functionality and scope of use of embodiments of the present invention.
As shown in fig. 6, the electronic device 12 is in the form of a general purpose computing device. Components of the electronic device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, a bus 18 that connects the various system components, including the system memory 28 and the processing units 16.
The system memory 28 may include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM) 30 and/or cache memory 32. The electronic device 12 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 34 may be used to read from or write to non-removable, nonvolatile magnetic media (not shown in FIG. 6, commonly referred to as a "hard disk drive"). Although not shown in fig. 6, a magnetic disk drive for reading from and writing to a removable non-volatile magnetic disk (e.g., a "floppy disk"), and an optical disk drive for reading from or writing to a removable non-volatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In such cases, each drive may be coupled to bus 18 through one or more data medium interfaces. Memory 28 may include at least one program product having a set (e.g., at least one) of program modules configured to carry out the functions of embodiments of the invention.
A program/utility 40 having a set (at least one) of program modules 42 may be stored in, for example, memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each or some combination of which may include an implementation of a network environment. Program modules 42 generally perform the functions and/or methods of the embodiments described herein.
The electronic device 12 may also communicate with one or more external devices 14 (e.g., keyboard, pointing device, display 24, etc.), one or more devices that enable a user to interact with the electronic device 12, and/or any devices (e.g., network card, modem, etc.) that enable the electronic device 12 to communicate with one or more other computing devices. Such communication may occur through an input/output (I/O) interface 22. Also, the electronic device 12 may communicate with one or more networks such as a Local Area Network (LAN), a Wide Area Network (WAN) and/or a public network, such as the Internet, through a network adapter 20. As shown, the network adapter 20 communicates with other modules of the electronic device 12 over the bus 18. It should be appreciated that although not shown, other hardware and/or software modules may be used in connection with electronic device 12, including, but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, data backup storage systems, and the like.
The processing unit 16 executes various functional applications and data processing by running programs stored in the system memory 28, for example, implementing the scene recognition method provided by the embodiment of the present invention.
Example six
The sixth embodiment of the invention provides a storage medium.
The computer-readable storage media of embodiments of the present invention may take the form of any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the computer-readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
The computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, either in baseband or as part of a carrier wave. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, smalltalk, C ++ and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider).
Note that the above is only a preferred embodiment of the present invention and the technical principle applied. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, while the invention has been described in connection with the above embodiments, the invention is not limited to the embodiments, but may be embodied in many other equivalent forms without departing from the spirit or scope of the invention, which is set forth in the following claims.
Claims (8)
1. A method of scene recognition, the method comprising:
acquiring at least one peripheral picture of a current user;
identifying current wear meta-information corresponding to each wear type according to the at least one peripheral picture and a preset wear degree value corresponding to each wear type;
calculating current wear cluster values corresponding to all the wear types according to the current wear meta-information corresponding to each wear type and the predetermined weight corresponding to each wear type;
calculating the matching value of the current abrasion meta-information corresponding to all abrasion types and each use scene according to the current abrasion cluster value corresponding to all abrasion types and the preset abrasion cluster value of each use scene;
And determining the use scene of the current user according to the matching values of the current wear meta-information corresponding to all the wear types and each use scene.
2. The method according to claim 1, wherein the identifying the current wear meta-information corresponding to each wear type according to the at least one peripheral picture and the preset wear level value corresponding to each wear type includes:
identifying the current wear degree value corresponding to each wear type according to the at least one peripheral picture;
and calculating the current abrasion meta-information corresponding to each abrasion type according to the current abrasion degree value corresponding to each abrasion type and the preset abrasion degree value corresponding to each abrasion type.
3. The method according to claim 2, wherein the identifying the current wear level value corresponding to the respective wear type according to the at least one peripheral picture includes:
performing fuzzy recognition on each peripheral picture to obtain a fuzzy position area and a fuzzy degree value of each peripheral picture; performing damage identification on each peripheral picture, and acquiring a damage position area and a damage degree value of each peripheral picture; carrying out reflection recognition on each peripheral picture to obtain a reflection position area and a reflection degree value of each peripheral picture;
Determining a current wear degree value corresponding to each wear type according to the fuzzy position area and the fuzzy degree value of each peripheral picture; or determining the current wear degree value corresponding to each wear type according to the damage position area and the damage degree value of each peripheral picture; or determining the current wear degree value corresponding to each wear type according to the reflective position area and the reflective degree value of each peripheral picture; or determining the current wear degree value corresponding to each wear type according to the fuzzy position area and the fuzzy degree value, and the damage position area and the damage degree value of each peripheral picture; or determining the current wear degree value corresponding to each wear type according to the fuzzy position area and the fuzzy degree value, and the reflective position area and the reflective degree value of each peripheral picture; or determining the current wear degree value corresponding to each wear type according to the damage position area and the damage degree value, and the reflection position area and the reflection degree value of each peripheral picture; or determining the current wear degree value corresponding to each wear type according to the fuzzy position area and the fuzzy degree value, the damage position area and the damage degree value, and the reflective position area and the reflective degree value of each peripheral image.
4. A scene recognition device, the device comprising: the device comprises an acquisition module, an identification module, a calculation submodule and a determination submodule; wherein, the liquid crystal display device comprises a liquid crystal display device,
the acquisition module is used for acquiring at least one peripheral picture of the current user;
the identification module is used for identifying current abrasion meta-information corresponding to each abrasion type according to the at least one peripheral picture and a preset abrasion degree value corresponding to each abrasion type;
the calculating submodule is used for calculating current wear cluster values corresponding to all the wear types according to the current wear meta-information corresponding to each wear type and the preset weight corresponding to each wear type; calculating the matching value of the current abrasion meta-information corresponding to all abrasion types and each use scene according to the current abrasion cluster value corresponding to all abrasion types and the preset abrasion cluster value of each use scene;
and the determining submodule is used for determining the use scene of the current user according to the matching values of the current wear meta information corresponding to all the wear types and the use scenes.
5. The apparatus according to claim 4, wherein:
The identification module is specifically configured to identify a current wear degree value corresponding to each wear type according to the at least one peripheral image; and calculating the current abrasion meta-information corresponding to each abrasion type according to the current abrasion degree value corresponding to each abrasion type and the preset abrasion degree value corresponding to each abrasion type.
6. The apparatus according to claim 5, wherein:
the identification module is specifically configured to perform fuzzy identification on the peripheral pictures, and obtain fuzzy position areas and fuzzy degree values of the peripheral pictures; performing damage identification on each peripheral picture, and acquiring a damage position area and a damage degree value of each peripheral picture; carrying out reflection recognition on each peripheral picture to obtain a reflection position area and a reflection degree value of each peripheral picture; determining a current wear degree value corresponding to each wear type according to the fuzzy position area and the fuzzy degree value of each peripheral picture; or determining the current wear degree value corresponding to each wear type according to the damage position area and the damage degree value of each peripheral picture; or determining the current wear degree value corresponding to each wear type according to the reflective position area and the reflective degree value of each peripheral picture; or determining the current wear degree value corresponding to each wear type according to the fuzzy position area and the fuzzy degree value, and the damage position area and the damage degree value of each peripheral picture; or determining the current wear degree value corresponding to each wear type according to the fuzzy position area and the fuzzy degree value, and the reflective position area and the reflective degree value of each peripheral picture; or determining the current wear degree value corresponding to each wear type according to the damage position area and the damage degree value, and the reflection position area and the reflection degree value of each peripheral picture; or determining the current wear degree value corresponding to each wear type according to the fuzzy position area and the fuzzy degree value, the damage position area and the damage degree value, and the reflective position area and the reflective degree value of each peripheral image.
7. An electronic device, comprising:
one or more processors;
a memory for storing one or more programs,
the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the scene recognition method of any of claims 1-3.
8. A storage medium having stored thereon a computer program, which when executed by a processor implements the scene recognition method according to any of claims 1 to 3.
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