CN108882145A - Sight spot recognition methods and device - Google Patents
Sight spot recognition methods and device Download PDFInfo
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- CN108882145A CN108882145A CN201810568064.XA CN201810568064A CN108882145A CN 108882145 A CN108882145 A CN 108882145A CN 201810568064 A CN201810568064 A CN 201810568064A CN 108882145 A CN108882145 A CN 108882145A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/14—Travel agencies
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
- H04W4/35—Services specially adapted for particular environments, situations or purposes for the management of goods or merchandise
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W76/00—Connection management
- H04W76/10—Connection setup
Abstract
This application involves a kind of sight spot recognition methods and devices.Method therein includes the sight spot image to be identified for receiving tourist's client and sending；Obtain the current location of tourist's client；The current location of tourist's client is establishing obtained in connection request from tourist's client in advance；The corresponding relationship of network model is identified according to each geographical position range and each sight spot, and the current location of the tourist's client obtained, determine required sight spot identification network model；The determining sight spot of the image input in sight spot to be identified is identified into network model, sight spot identification is carried out, the recommended information at the sight spot of identification is fed back into tourist's client.In this way, as long as the photo upload at guest taken sight spot, provides the information at more sight spots without tourist, sight spot identifies rapidly and efficiently.
Description
Technical field
This application involves sight spot identification technology field more particularly to a kind of sight spot recognition methods and devices.
Background technique
The it is proposed of artificial intelligence concept provides soil for the wisdom of life, smart travel big data with it is intelligentized
Also it has been put on schedule today, for example in order to allow tourist to better understand sight spot information, many tourism softwares has occurred.
In current some tourism softwares, tourist is needed to manually select sight spot, still, for tourist, known to them
Information and scenic spot information it is usually asymmetric, scenic spot be for tourist it is strange, tourist can not quick obtaining arrive
The information at sight spot also can not just select corresponding sight spot in software, lead to not acquisition sight spot and be discussed in detail.
Summary of the invention
To be overcome the problems, such as present in the relevant technologies at least to a certain extent, the application provides a kind of sight spot recognition methods
And device.
According to the embodiment of the present application in a first aspect, provide a kind of sight spot recognition methods, including：
Receive the sight spot image to be identified that tourist's client is sent；
Obtain the current location of tourist's client；The current location of tourist's client is in advance from the tourist
Client is established obtained in connection request；
According to the corresponding relationship of each geographical position range and each sight spot identification network model, and the tourist visitor obtained
The current location at family end determines required sight spot identification network model；
The determining sight spot of the image input in sight spot to be identified is identified into network model, sight spot identification is carried out, will know
The recommended information at other sight spot feeds back to tourist's client.
Optionally, the recommended information at the sight spot by identification feeds back to tourist's client, including：
The recommended information at the sight spot of identification is fed back into tourist's client with speech form or written form.
Optionally, the method for the present embodiment further includes：
Obtain multiple images, the label information at each sight spot that scenic spot management person's client uploads；
According to multiple images, the label information at each sight spot, training sight spot identifies network model.
Optionally, the angle of multiple images at each sight spot is different, light and shade is different.
Optionally, the trained sight spot identifies network model, including：
Network model is identified based on YOLOv2 model training sight spot；Feature Selection Model in the YOLOv2 model is
Darknet19 network model.
According to the second aspect of the embodiment of the present application, a kind of sight spot identification device is provided, including：
Receiving module, for receiving the sight spot image to be identified of tourist's client transmission；
Module is obtained, for obtaining the current location of tourist's client；The current location of tourist's client is
Establishing obtained in connection request from tourist's client in advance；
Determining module for the corresponding relationship according to each geographical position range and each sight spot identification network model, and obtains
The current location of the tourist's client taken determines required sight spot identification network model；
Identification module is carried out for the determining sight spot of the image input in sight spot to be identified to be identified network model
Sight spot identification, feeds back to tourist's client for the recommended information at the sight spot of identification.
Optionally, when the recommended information at the sight spot by identification feeds back to tourist's client, the identification module,
It is specifically used for：
The recommended information at the sight spot of identification is fed back into tourist's client with speech form or written form.
Optionally, the device of the present embodiment further includes：
Training module, multiple images, the label information at each sight spot for obtaining the upload of scenic spot management person's client；Root
According to multiple images, the label information at each sight spot, training sight spot identifies network model.
Optionally, the angle of multiple images at each sight spot is different, light and shade is different.
Optionally, when the trained sight spot identification network model, the training module is specifically used for：
Network model is identified based on YOLOv2 model training sight spot；Feature Selection Model in the YOLOv2 model is
Darknet19 network model.
According to the third aspect of the embodiment of the present application, a kind of non-transitorycomputer readable storage medium is provided, when described
When instruction in storage medium is executed by processor, enable a processor to execute a kind of sight spot recognition methods, the method packet
It includes：
Receive the sight spot image to be identified that tourist's client is sent；
Obtain the current location of tourist's client；The current location of tourist's client is in advance from the tourist
Client is established obtained in connection request；
According to the corresponding relationship of each geographical position range and each sight spot identification network model, and the tourist visitor obtained
The current location at family end determines required sight spot identification network model；
The determining sight spot of the image input in sight spot to be identified is identified into network model, sight spot identification is carried out, will know
The recommended information at other sight spot feeds back to tourist's client.
Optionally, the recommended information at the sight spot by identification feeds back to tourist's client, including：
The recommended information at the sight spot of identification is fed back into tourist's client with speech form or written form.
Optionally, the method for the present embodiment further includes：
Obtain multiple images, the label information at each sight spot that scenic spot management person's client uploads；
According to multiple images, the label information at each sight spot, training sight spot identifies network model.
Optionally, the angle of multiple images at each sight spot is different, light and shade is different.
Optionally, the trained sight spot identifies network model, including：
Network model is identified based on YOLOv2 model training sight spot；Feature Selection Model in the YOLOv2 model is
Darknet19 network model.
According to the fourth aspect of the embodiment of the present application, a kind of sight spot identification device is provided, including：Processor；For storing
The memory of processor-executable instruction；Wherein, the processor is configured to：
Receive the sight spot image to be identified that tourist's client is sent；
Obtain the current location of tourist's client；The current location of tourist's client is in advance from the tourist
Client is established obtained in connection request；
According to the corresponding relationship of each geographical position range and each sight spot identification network model, and the tourist visitor obtained
The current location at family end determines required sight spot identification network model；
The determining sight spot of the image input in sight spot to be identified is identified into network model, sight spot identification is carried out, will know
The recommended information at other sight spot feeds back to tourist's client.
Optionally, the recommended information at the sight spot by identification feeds back to tourist's client, the processing implement body
It is configured as：
The recommended information at the sight spot of identification is fed back into tourist's client with speech form or written form.
Optionally, the processor is additionally configured to：
Obtain multiple images, the label information at each sight spot that scenic spot management person's client uploads；
According to multiple images, the label information at each sight spot, training sight spot identifies network model.
Optionally, the angle of multiple images at each sight spot is different, light and shade is different.
Optionally, when the trained sight spot identification network model, the processor is specifically configured to：
Network model is identified based on YOLOv2 model training sight spot；Feature Selection Model in the YOLOv2 model is
Darknet19 network model.
The technical solution that embodiments herein provides can include the following benefits：
Due to only needing tourist's client to upload sight spot image to be identified, building from tourist's client in advance is then obtained
The current location of tourist's client obtained in vertical connection request, so that it may which net is identified according to each geographical position range and each sight spot
The corresponding relationship of network module, and the current location of tourist's client obtained, determine required sight spot identification network module, contracting
Sight spot image to be identified is input in sight spot identification network model, so that it may identify sight spot and by scape by small search range
The recommended information of point feeds back to tourist's client, as long as in this way, the photo upload at guest taken sight spot, provides without tourist
The information at more sight spots, sight spot identify rapidly and efficiently.
It should be understood that above general description and following detailed description be only it is exemplary and explanatory, not
The application can be limited.
Detailed description of the invention
The drawings herein are incorporated into the specification and forms part of this specification, and shows the implementation for meeting the application
Example, and together with specification it is used to explain the principle of the application.
Fig. 1 is the flow chart for the sight spot recognition methods that the application one embodiment provides.
Fig. 2 is the structure chart for the sight spot identification device that the application one embodiment provides.
Fig. 3 is the structure chart for the sight spot identification device that the application one embodiment provides.
Specific embodiment
Example embodiments are described in detail here, and the example is illustrated in the accompanying drawings.Following description is related to
When attached drawing, unless otherwise indicated, the same numbers in different drawings indicate the same or similar elements.Following exemplary embodiment
Described in embodiment do not represent all embodiments consistent with the application.On the contrary, they be only with it is such as appended
The example of the consistent device and method of some aspects be described in detail in claims, the application.
Fig. 1 is a kind of flow chart for sight spot recognition methods that the application one embodiment provides.
As shown in Figure 1, the method for the present embodiment is executed by server side, the method for the present embodiment includes：
Step 11 receives the sight spot image to be identified that tourist's client is sent；
Step 12, the current location for obtaining tourist's client；The current location of tourist's client is in advance from tourist client
End is established obtained in connection request；
Generally, after tourist's client is opened, it can all be sent to server and establish connection request, wherein position letter can be carried
Breath, it is possible to obtain the current location of tourist's client from establishing in connection request for tourist's client in advance；
Step 13, the corresponding relationship that network model is identified according to each geographical position range and each sight spot, and the trip obtained
The current location of objective client determines required sight spot identification network model；
The determining sight spot of sight spot image to be identified input is identified network model by step 14, is carried out sight spot identification, will be identified
The recommended information at sight spot feed back to tourist's client.
Wherein, the recommended information at sight spot may include the title at sight spot, brief introduction etc..
Due to only needing tourist's client to upload sight spot image to be identified, building from tourist's client in advance is then obtained
The current location of tourist's client obtained in vertical connection request, so that it may which net is identified according to each geographical position range and each sight spot
The corresponding relationship of network module, and the current location of tourist's client obtained, determine required sight spot identification network module, contracting
Sight spot image to be identified is input in sight spot identification network model, so that it may identify sight spot and by scape by small search range
The recommended information of point feeds back to tourist's client, as long as in this way, the photo upload at guest taken sight spot, provides without tourist
The information at more sight spots, sight spot identify rapidly and efficiently.
In above-mentioned steps 13, according to the corresponding relationship of each geographical position range and each sight spot identification network model, and obtain
The current location of the tourist's client taken determines required sight spot identification network model, specifically, searching working as tourist's client
Geographical position range belonging to front position is identified according to the geographical position range of lookup and each geographical position range and each sight spot
The corresponding relationship of network model finds required sight spot identification network module.
In above-mentioned steps 14, the recommended information at the sight spot of identification is fed back into tourist's client, specific implementation can be with
It is：The recommended information at the sight spot of identification is fed back into tourist's client with speech form or written form.The present embodiment provides not
Same feedback form, can select as needed for tourist.
When it is implemented, needing training sight spot identification network model in advance, it is based on this, sight spot identification provided in this embodiment
Method further includes：Obtain multiple images, the label information at each sight spot that scenic spot management person's client uploads；According to each sight spot
Multiple images, label information, training sight spot identify network model.
For example, have 10 sight spots for the A of scenic spot, if the administrator of scenic spot A by multiple images at 10 sight spots,
Label information is uploaded to server by scenic spot management person's client, and server will generate the training sample database of scenic spot A,
It is then based on the training sample database of scenic spot A, the sight spot of training scenic spot A identifies network model.
Wherein, the angle of multiple images at each sight spot is different, light and shade is different.So, it is ensured that know at trained sight spot
The accuracy of other network model.
Wherein, the label information at sight spot can be the recommended informations such as the title at above-mentioned sight spot, brief introduction.
Optionally, after multiple images, label information at each sight spot of acquisition scenic spot management person's client upload, according to
Multiple images, the label information at each sight spot before training sight spot identifies network model, can also carry out the image received
Pretreatment, including adjusting the size of image, light and shade to seeking unity of standard, and according to the recommended information at sight spot by the name of image according to
Pre-set specifications adjustment, generates the picture database at scenic spot.
There are many specific implementations of above-mentioned trained sight spot identification network model.Optionally, training sight spot identifies network
Model, specific implementation can be：Network model is identified based on YOLOv2 model training sight spot；Feature in YOLOv2 model
Extraction model is Darknet19 network model.Specifically, feature extraction is carried out to image first, then to the spy extracted
Sign is normalized, and carries out model training using the feature after normalization.
In identification process, after sight spot image to be identified is input in sight spot identification network model, it can obtain to be identified
Sight spot image belongs to the probability of each scene types, by the highest one kind of probability as sight spot belonging to sight spot image to be identified
Classification obtains the corresponding sight spot of image.
Fig. 2 is a kind of structure chart for sight spot identification device that the application one embodiment provides.
Referring to fig. 2, a kind of sight spot identification device provided in this embodiment, including：
Receiving module 201, for receiving the sight spot image to be identified of tourist's client transmission；
Module 202 is obtained, for obtaining the current location of tourist's client；The current location of tourist's client be in advance from
Tourist's client is established obtained in connection request；
Determining module 203, for the corresponding relationship according to each geographical position range and each sight spot identification network model, and
The current location of tourist's client of acquisition determines required sight spot identification network model；
Identification module 204 carries out sight spot knowledge for the determining sight spot of sight spot image to be identified input to be identified network model
Not, the recommended information at the sight spot of identification is fed back into tourist's client.
Optionally, when the recommended information at the sight spot of identification being fed back to tourist's client, identification module is specifically used for：
The recommended information at the sight spot of identification is fed back into tourist's client with speech form or written form.
Optionally, the device of the present embodiment further includes：
Training module, multiple images, the label information at each sight spot for obtaining the upload of scenic spot management person's client；Root
According to multiple images, the label information at each sight spot, training sight spot identifies network model.
Optionally, the angle of multiple images at each sight spot is different, light and shade is different.
Optionally, when training sight spot identification network model, training module is specifically used for：
Network model is identified based on YOLOv2 model training sight spot；Feature Selection Model in YOLOv2 model is
Darknet19 network model.
According to the third aspect of the embodiment of the present application, a kind of non-transitorycomputer readable storage medium is provided, storage is worked as
When instruction in medium is executed by processor, enable a processor to execute a kind of sight spot recognition methods, the method for the present embodiment
Including：
Receive the sight spot image to be identified that tourist's client is sent；
Obtain the current location of tourist's client；The current location of tourist's client is in advance from the foundation of tourist's client
Obtained in connection request；
According to the corresponding relationship of each geographical position range and each sight spot identification network model, and the tourist's client obtained
Current location, determine required sight spot identification network model；
The determining sight spot of sight spot image to be identified input is identified into network model, sight spot identification is carried out, by the sight spot of identification
Recommended information feed back to tourist's client.
Optionally, the recommended information at the sight spot of identification is fed back into tourist's client, including：
The recommended information at the sight spot of identification is fed back into tourist's client with speech form or written form.
Optionally, the method for the present embodiment further includes：
Obtain multiple images, the label information at each sight spot that scenic spot management person's client uploads；
According to multiple images, the label information at each sight spot, training sight spot identifies network model.
Optionally, the angle of multiple images at each sight spot is different, light and shade is different.
Optionally, training sight spot identifies network model, including：
Network model is identified based on YOLOv2 model training sight spot；Feature Selection Model in YOLOv2 model is
Darknet19 network model.
Fig. 3 is a kind of structure chart for sight spot identification device that the application one embodiment provides.
Referring to Fig. 3, a kind of sight spot identification device provided in this embodiment, including：Processor 301；For storage processor
The memory 302 of executable instruction；Wherein, processor is configured as：
Receive the sight spot image to be identified that tourist's client is sent；
Worked as according to what the corresponding relationship and received tourist's client of location information and sight spot identification network model were sent
Preceding location information determines that current location information corresponds to sight spot identification network model；
The determining sight spot of sight spot image to be identified input is identified into network model, sight spot identification is carried out, by the sight spot of identification
Recommended information feed back to tourist's client.
Optionally, the recommended information at the sight spot of identification is fed back into tourist's client, processor is specifically configured to：
The recommended information at the sight spot of identification is fed back into tourist's client with speech form or written form.
Optionally, processor is additionally configured to：
Obtain multiple images, the label information at each sight spot that scenic spot management person's client uploads；
According to multiple images, the label information at each sight spot, training sight spot identifies network model.
Optionally, the angle of multiple images at each sight spot is different, light and shade is different.
Optionally, when training sight spot identification network model, processor is specifically configured to：
Network model is identified based on YOLOv2 model training sight spot；Feature Selection Model in YOLOv2 model is
Darknet19 network model.
About the device in above-described embodiment, wherein modules execute the concrete mode of operation in related this method
Embodiment in be described in detail, no detailed explanation will be given here.
It is understood that same or similar part can mutually refer in the various embodiments described above, in some embodiments
Unspecified content may refer to the same or similar content in other embodiments.
It should be noted that term " first ", " second " etc. are used for description purposes only in the description of the present application, without
It can be interpreted as indication or suggestion relative importance.In addition, in the description of the present application, unless otherwise indicated, the meaning of " multiple "
Refer at least two.
Any process described otherwise above or method description are construed as in flow chart or herein, and expression includes
It is one or more for realizing specific logical function or process the step of executable instruction code module, segment or portion
Point, and the range of the preferred embodiment of the application includes other realization, wherein can not press shown or discussed suitable
Sequence, including according to related function by it is basic simultaneously in the way of or in the opposite order, to execute function, this should be by the application
Embodiment person of ordinary skill in the field understood.
It should be appreciated that each section of the application can be realized with hardware, software, firmware or their combination.Above-mentioned
In embodiment, software that multiple steps or method can be executed in memory and by suitable instruction execution system with storage
Or firmware is realized.It, and in another embodiment, can be under well known in the art for example, if realized with hardware
Any one of column technology or their combination are realized：With for realizing the logic gates of logic function to data-signal
Discrete logic, with suitable combinational logic gate circuit specific integrated circuit, programmable gate array (PGA), scene
Programmable gate array (FPGA) etc..
Those skilled in the art are understood that realize all or part of step that above-described embodiment method carries
It suddenly is that relevant hardware can be instructed to complete by program, the program can store in a kind of computer-readable storage medium
In matter, which when being executed, includes the steps that one or a combination set of embodiment of the method.
It, can also be in addition, can integrate in a processing module in each functional unit in each embodiment of the application
It is that each unit physically exists alone, can also be integrated in two or more units in a module.Above-mentioned integrated mould
Block both can take the form of hardware realization, can also be realized in the form of software function module.The integrated module is such as
Fruit is realized and when sold or used as an independent product in the form of software function module, also can store in a computer
In read/write memory medium.
Storage medium mentioned above can be read-only memory, disk or CD etc..
In the description of this specification, reference term " one embodiment ", " some embodiments ", " example ", " specifically show
The description of example " or " some examples " etc. means specific features, structure, material or spy described in conjunction with this embodiment or example
Point is contained at least one embodiment or example of the application.In the present specification, schematic expression of the above terms are not
Centainly refer to identical embodiment or example.Moreover, particular features, structures, materials, or characteristics described can be any
One or more embodiment or examples in can be combined in any suitable manner.
Although embodiments herein has been shown and described above, it is to be understood that above-described embodiment is example
Property, it should not be understood as the limitation to the application, those skilled in the art within the scope of application can be to above-mentioned
Embodiment is changed, modifies, replacement and variant.
Claims (10)
1. a kind of sight spot recognition methods, which is characterized in that including：
Receive the sight spot image to be identified that tourist's client is sent；
Obtain the current location of tourist's client；The current location of tourist's client is in advance from the tourist client
End is established obtained in connection request；
According to the corresponding relationship of each geographical position range and each sight spot identification network model, and the tourist's client obtained
Current location, determine required sight spot identification network model；
The determining sight spot of the image input in sight spot to be identified is identified into network model, sight spot identification is carried out, by identification
The recommended information at sight spot feeds back to tourist's client.
2. the method according to claim 1, wherein the recommended information at the sight spot by identification feed back to it is described
Tourist's client, including：
The recommended information at the sight spot of identification is fed back into tourist's client with speech form or written form.
3. the method according to claim 1, wherein the method also includes：
Obtain multiple images, the label information at each sight spot that scenic spot management person's client uploads；
According to multiple images, the label information at each sight spot, training sight spot identifies network model.
4. according to the method described in claim 3, it is characterized in that, the angle of multiple images at each sight spot is different, light and shade not
Together.
5. according to the method described in claim 3, it is characterized in that, the trained sight spot identifies network model, including：
Network model is identified based on YOLOv2 model training sight spot；Feature Selection Model in the YOLOv2 model is
Darknet19 network model.
6. a kind of sight spot identification device, which is characterized in that including：
Receiving module, for receiving the sight spot image to be identified of tourist's client transmission；
Module is obtained, for obtaining the current location of tourist's client；The current location of tourist's client is preparatory
From establishing obtained in connection request for tourist's client；
Determining module, for the corresponding relationship according to each geographical position range and each sight spot identification network model, and obtain
The current location of tourist's client determines required sight spot identification network model；
Identification module carries out sight spot for the determining sight spot of the image input in sight spot to be identified to be identified network model
Identification, feeds back to tourist's client for the recommended information at the sight spot of identification.
7. device according to claim 6, which is characterized in that the recommended information at the sight spot by identification feeds back to described
When tourist's client, the identification module is specifically used for：
The recommended information at the sight spot of identification is fed back into tourist's client with speech form or written form.
8. device according to claim 6, which is characterized in that described device further includes：
Training module, multiple images, the label information at each sight spot for obtaining the upload of scenic spot management person's client；According to every
Multiple images, the label information at a sight spot, training sight spot identify network model.
9. device according to claim 8, which is characterized in that the angles of multiple images at each sight spot is different, light and shade not
Together.
10. device according to claim 8, which is characterized in that when the trained sight spot identification network model, the training
Module is specifically used for：
Network model is identified based on YOLOv2 model training sight spot；Feature Selection Model in the YOLOv2 model is
Darknet19 network model.
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| CN112733593A (en) * | 2021-03-18 | 2021-04-30 | 成都中科大旗软件股份有限公司 | Method and system for realizing image information identification based on image position |
| CN112967641A (en) * | 2020-10-22 | 2021-06-15 | 太极计算机股份有限公司 | Automatic identification explanation and enhanced display method for scenic spot based on AR technology |
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| CN102915326A (en) * | 2012-08-30 | 2013-02-06 | 杭州藕根科技有限公司 | Mobile terminal scenery identifying system based on GPS (Global Positioning System) and image search technique |
| CN103064980A (en) * | 2013-01-15 | 2013-04-24 | 广东欧珀移动通信有限公司 | Method and system for inquiring information of scenic spots on basis of mobile terminal and GPS (global positioning system) |
| CN103514265A (en) * | 2013-09-04 | 2014-01-15 | 一派视觉（北京）数字科技有限公司 | Panorama interactive digital enhancement experiential intelligent tourism system and method |
| CN104657509A (en) * | 2015-03-18 | 2015-05-27 | 苏州大学 | Method and system for recommending tourist destinations based on historical photo information |
| KR20170027020A (en) * | 2015-09-01 | 2017-03-09 | 유주현 | Tourism system that deal with photo and video contents |
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| CN112967641A (en) * | 2020-10-22 | 2021-06-15 | 太极计算机股份有限公司 | Automatic identification explanation and enhanced display method for scenic spot based on AR technology |
| CN112967641B (en) * | 2020-10-22 | 2023-02-17 | 太极计算机股份有限公司 | Automatic identification explanation and enhanced display method for scenic spot based on AR technology |
| CN112733593A (en) * | 2021-03-18 | 2021-04-30 | 成都中科大旗软件股份有限公司 | Method and system for realizing image information identification based on image position |
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