CN111274431A - Image retrieval processing method and device - Google Patents
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- CN111274431A CN111274431A CN202010080014.4A CN202010080014A CN111274431A CN 111274431 A CN111274431 A CN 111274431A CN 202010080014 A CN202010080014 A CN 202010080014A CN 111274431 A CN111274431 A CN 111274431A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/50—Information retrieval; Database structures therefor; File system structures therefor of still image data
- G06F16/58—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
- G06F16/583—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/172—Classification, e.g. identification
Abstract
The invention provides an image retrieval processing method and device, wherein the method comprises the following steps: acquiring one or more entity objects in a target image, and marking the one or more entity objects in the target image; selecting one or more target entity objects from the one or more entity objects; determining a target search condition according to the one or more target entity objects; the image retrieval is carried out based on the target search condition, the problem that in the related technology, the identification efficiency is low when a single search object with the highest identification degree is automatically selected for searching can be solved, and the image searching efficiency is improved through the batch searching of multiple objects in the target image.
Description
Technical Field
The invention relates to the field of image processing, in particular to an image retrieval processing method and device.
Background
Face recognition technology has very wide application in many fields, such as video surveillance, intelligent business, access control systems, etc. Therefore, the database has a billion-level large-scale face database, a dynamic database stored in real time and a static database used for verifying the identity of the user exist in the huge database, and the user cannot customize the database to inquire the required pictures according to the self-demand. And the pose of the face and the environment factor of the face in the database are very different, especially the factors such as illumination, resolution, shielding and the like. When the face picture is searched, the face picture (the face picture with poor light and the face picture with a hat) in a complex environment is difficult to search, and the searching precision is not high. Thus, the search requirement of the user cannot be met.
In the related technology, a face picture to be retrieved is obtained; according to the face picture to be retrieved, retrieving a similar face picture from a target database; outputting a retrieval result; providing an object with the highest algorithm identification degree in the process of identifying the object, and being incapable of customizing a target object for retrieval; after the retrieval is completed, the target objects cannot be reserved and freely combined to serve as a new condition.
In the algorithm identification process, one object with the highest identification degree is automatically selected, and the requirement of multi-object batch search cannot be met. The invention displays all entity objects which can be identified, gives more freedom to users, and artificially judges whether to select single or multiple objects for searching the images.
Under the single-graph uploading condition, the search result is based on a single search object. The multi-image uploading can search the objects from the same or different snapshots, so that the range of search results is enlarged, and the problem that the user cannot backtrack the image data when more results are provided and the identified objects are not stored is solved.
Aiming at the problem of low identification efficiency in the related art that a single search object with the highest identification degree is automatically selected for searching, no solution is provided.
Disclosure of Invention
The embodiment of the invention provides an image retrieval processing method and device, which are used for at least solving the problem of low identification efficiency in the process of automatically selecting a single search object with highest identification degree to search in the related technology.
According to an embodiment of the present invention, there is provided an image retrieval processing method including:
acquiring one or more entity objects in a target image, and marking the one or more entity objects in the target image;
selecting one or more target entity objects from the one or more entity objects;
determining a target search condition according to the one or more target entity objects;
and performing image retrieval based on the target search condition.
Optionally, the image retrieval based on the target search condition comprises:
and acquiring one or more images with the similarity of the image characteristics of the one or more target entity objects larger than or equal to a preset threshold value from a database according to the target search condition.
Optionally, the obtaining, from the database, one or more images with similarity greater than or equal to a predetermined threshold with the image features of the one or more target entity objects according to the target search condition includes:
comparing the image characteristics of the one or more target entity objects in the target search condition with the entity objects of all the images in the database respectively;
acquiring one or more images with similarity of image features of the one or more target solid objects greater than or equal to the predetermined threshold.
Optionally, after performing image retrieval based on the target search condition, the method further includes:
storing the one or more images into a set of images corresponding to the one or more target entity objects.
Optionally, storing the one or more images into an image set corresponding to the one or more target entity objects comprises:
and under the condition that the target entity objects are multiple, respectively storing one or more images corresponding to the multiple target entity objects into corresponding image subsets, wherein the image set comprises multiple image subsets, and each target entity object corresponds to one image subset.
Optionally, the selecting a target entity object from the one or more entity objects includes:
receiving the one or more target entity objects selected through interactive operation with a display interface; alternatively, the first and second electrodes may be,
selecting the one or more target entity objects from the one or more entity objects according to a preset rule;
and displaying the one or more target entity objects at a preset position of the display interface.
Optionally, after determining the target search condition according to the one or more target entity objects, the method further includes:
and storing the target search condition into a historical retrieval record according to the time sequence.
Optionally, the target image is acquired by a camera or is obtained from a video.
According to another embodiment of the present invention, there is also provided an image retrieval processing apparatus including:
the system comprises an acquisition module, a display module and a display module, wherein the acquisition module is used for acquiring one or more entity objects in a target image and marking the one or more entity objects in the target image;
a selecting module for selecting one or more target entity objects from the one or more entity objects;
a determining module, configured to determine a target search condition according to the one or more target entity objects;
and the image retrieval module is used for carrying out image retrieval based on the target search condition.
Optionally, the image retrieval module is also used for
And acquiring one or more images with the similarity of the image characteristics of the one or more target entity objects larger than or equal to a preset threshold value from a database according to the target search condition.
Optionally, the image retrieval module comprises:
a comparison sub-module, configured to compare image features of the one or more target entity objects in the target search condition with entity objects of all images in the database, respectively;
and the acquisition sub-module is used for acquiring one or more images with the similarity of the image characteristics of the one or more target entity objects being larger than or equal to the preset threshold.
Optionally, the apparatus further comprises:
a storage module to store the one or more images into an image collection corresponding to the one or more target entity objects.
Optionally, the memory module is further used for
And under the condition that the target entity objects are multiple, respectively storing one or more images corresponding to the multiple target entity objects into corresponding image subsets, wherein the image set comprises multiple image subsets, and each target entity object corresponds to one image subset.
Optionally, the selecting module includes:
receiving the one or more target entity objects selected through interactive operation with a display interface; alternatively, the first and second electrodes may be,
selecting the one or more target entity objects from the one or more entity objects according to a preset rule;
and displaying the one or more target entity objects at a preset position of the display interface.
Optionally, the apparatus further comprises:
and the storage module is used for storing the target search condition into a historical retrieval record according to the time sequence.
Optionally, the target image is acquired by a camera or is obtained from a video.
According to a further embodiment of the present invention, a computer-readable storage medium is also provided, in which a computer program is stored, wherein the computer program is configured to perform the steps of any of the above-described method embodiments when executed.
According to yet another embodiment of the present invention, there is also provided an electronic device, including a memory in which a computer program is stored and a processor configured to execute the computer program to perform the steps in any of the above method embodiments.
According to the invention, one or more entity objects in a target image are obtained, and the one or more entity objects are marked in the target image; selecting one or more target entity objects from the one or more entity objects; determining a target search condition according to the one or more target entity objects; the image retrieval is carried out based on the target search condition, the problem that in the related technology, the identification efficiency is low when a single search object with the highest identification degree is automatically selected for searching can be solved, and the image searching efficiency is improved through the batch searching of multiple objects in the target image.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention. In the drawings:
fig. 1 is a block diagram of a hardware configuration of a mobile terminal of an image retrieval processing method according to an embodiment of the present invention;
FIG. 2 is a flow chart of an image retrieval processing method according to an embodiment of the present invention;
FIG. 3 is a flow diagram of a graph search graph according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of a user uploading an image according to an embodiment of the invention;
FIG. 5 is a first diagram illustrating selection of a target entity object according to an embodiment of the present invention;
FIG. 6 is a second schematic diagram of selecting a target entity object according to an embodiment of the present invention;
fig. 7 is a block diagram of an image retrieval processing apparatus according to an embodiment of the present invention.
Detailed Description
The invention will be described in detail hereinafter with reference to the accompanying drawings in conjunction with embodiments. It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order.
Example 1
The method provided by the first embodiment of the present application may be executed in a mobile terminal, a computer terminal, or a similar computing device. Taking a mobile terminal as an example, fig. 1 is a hardware structure block diagram of a mobile terminal of an image retrieval processing method according to an embodiment of the present invention, as shown in fig. 1, a mobile terminal 10 may include one or more processors 102 (only one is shown in fig. 1) (the processor 102 may include, but is not limited to, a processing device such as a microprocessor MCU or a programmable logic device FPGA), and a memory 104 for storing data, and optionally, the mobile terminal may further include a transmission device 106 for communication function and an input/output device 108. It will be understood by those skilled in the art that the structure shown in fig. 1 is only an illustration, and does not limit the structure of the mobile terminal. For example, the mobile terminal 10 may also include more or fewer components than shown in FIG. 1, or have a different configuration than shown in FIG. 1.
The memory 104 may be used to store a computer program, for example, a software program of application software and a module, such as a computer program corresponding to the message receiving method in the embodiment of the present invention, and the processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, so as to implement the method described above. The memory 104 may include high speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory located remotely from the processor 102, which may be connected to the mobile terminal 10 via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The transmission device 106 is used for receiving or transmitting data via a network. Specific examples of the network described above may include a wireless network provided by a communication provider of the mobile terminal 10. In one example, the transmission device 106 includes a Network adapter (NIC), which can be connected to other Network devices through a base station so as to communicate with the internet. In one example, the transmission device 106 may be a Radio Frequency (RF) module, which is used for communicating with the internet in a wireless manner.
In this embodiment, an image retrieval processing method operating in the mobile terminal or the network architecture is provided, and fig. 2 is a flowchart of an image retrieval processing method according to an embodiment of the present invention, as shown in fig. 2, the flowchart includes the following steps:
step S202, one or more entity objects in a target image are obtained, and the one or more entity objects are marked in the target image;
the target image in the embodiment of the invention is acquired by a camera or acquired from a video.
Specifically, the one or more entity objects in the target image are identified and marked through a box mark, a circle, and the like, and the same marking mode is adopted for the same entity object. The target image may be one or a plurality of images.
Step S204, selecting one or more target entity objects from the one or more entity objects;
in the step S204, one or more target entity objects may be manually selected, or the system may automatically select according to a preset rule, and specifically, receive the one or more target entity objects selected through an interactive operation with the display interface; or, selecting the one or more target entity objects from the one or more entity objects according to a predetermined rule; and displaying the one or more target entity objects at a preset position of the display interface.
Step S206, determining target searching conditions according to the one or more target entity objects;
optionally, the target search condition is stored in a history retrieval record according to a time sequence, so that the target search condition is convenient to be called subsequently.
And step S208, carrying out image retrieval based on the target search condition.
Through the above S202 to S208, one or more entity objects in the target image are obtained, and the one or more entity objects are marked in the target image; selecting one or more target entity objects from the one or more entity objects; determining a target search condition according to the one or more target entity objects; the image retrieval is carried out based on the target search condition, the problem that in the related technology, the identification efficiency is low when a single search object with the highest identification degree is automatically selected for searching can be solved, and the image searching efficiency is improved through the batch searching of multiple objects in the target image.
Optionally, the step S208 may specifically include: and acquiring one or more images with the similarity of the image characteristics of the one or more target entity objects larger than or equal to a preset threshold value from a database according to the target search condition. Further, comparing the image features of the one or more target entity objects in the target search condition with the entity objects of all the images in the database respectively; acquiring one or more images with similarity of image features of the one or more target solid objects greater than or equal to the predetermined threshold.
In the embodiment of the present invention, after the image retrieval is performed based on the target search condition, the one or more images are stored in the image set corresponding to the one or more target entity objects. Further, when the target entity objects are multiple, one or more images corresponding to the multiple target entity objects are stored in corresponding image subsets, respectively, where the image set includes multiple image subsets, and each target entity object corresponds to one image subset.
The embodiment of the invention displays all entity objects which can be identified, gives more freedom to a user, and artificially judges whether to select a single object or a plurality of objects for searching the image. Under the single-graph uploading condition, the search result is based on a single search object. The multi-graph uploading can search for objects from the same or different snapshots, so that the range of search results is increased, and more results are provided for a user. And the search records corresponding to the identification objects are stored, and the storage of the cutout objects can help to backtrack the history records.
Fig. 3 is a flowchart of searching a graph according to an embodiment of the present invention, as shown in fig. 3, including:
step S301, acquiring a snapshot or a video material, which may be a plurality of snapshots and/or a plurality of video materials; fig. 4 is a schematic diagram of a user uploading an image, as shown in fig. 4, after the user clicks the uploading image, a snapshot or a video material is displayed in a display interface.
Step S302, identifying entity objects in the material, wherein one or more entity objects are identified;
step S303, judging whether the user selects the marked entity object, if not, executing step S304, otherwise, executing step S305;
step S304, automatically selecting a target entity object according to a preset rule, for example, preferentially selecting a human face as the target entity object, and then selecting a motor vehicle, a non-motor vehicle and the like;
step S305, acquiring a target entity object selected by a user through interactive operation in a display interface; fig. 5 is a first schematic diagram of selecting a target entity object according to an embodiment of the present invention, as shown in fig. 5, an entity object in a material is automatically identified and marked, a user selects an entity object a as the target entity object, and the target entity object is displayed on the right side of a display interface. Fig. 6 is a schematic diagram of selecting a target entity object according to an embodiment of the present invention, and as shown in fig. 6, the user continues to upload the material, selects entity object 1 and entity object 2 from the entity objects marked in the material as target entity objects, and displays the target entity objects on the right side of the display interface. Optionally, the user may also change the selected target entity object in the target entity object area on the right side, which may be reduced or increased.
Step S306, displaying one or more target entity objects;
step S307, performing multi-target search based on the search condition generated by the target entity object;
and step S308, displaying the search result and recording historical search conditions.
According to the embodiment of the invention, picture materials in a snapshot scene are analyzed, information of entity objects is obtained, and the position of each object in a picture is positioned; and filling the entry search condition according to the selected entity object, and searching the image by using the image, thereby avoiding the problem that the update condition covers the last operation condition when the single image is uploaded. The multi-graph condition uploading can combine the objects from the same or different snapshots for searching, increase the number of search results and provide more choices for the user.
Example 2
According to another embodiment of the present invention, there is also provided an image retrieval processing apparatus, and fig. 7 is a block diagram of the image retrieval processing apparatus according to the embodiment of the present invention, as shown in fig. 7, including:
an obtaining module 72, configured to obtain one or more entity objects in a target image, and mark the one or more entity objects in the target image;
a selecting module 74, configured to select one or more target entity objects from the one or more entity objects;
a determining module 76, configured to determine a target search condition according to the one or more target entity objects;
and an image retrieval module 78, configured to perform image retrieval based on the target search condition.
Optionally, the image retrieval module 78 is further configured to
And acquiring one or more images with the similarity of the image characteristics of the one or more target entity objects larger than or equal to a preset threshold value from a database according to the target search condition.
Optionally, the image retrieval module 78 includes:
a comparison sub-module, configured to compare image features of the one or more target entity objects in the target search condition with entity objects of all images in the database, respectively;
and the acquisition sub-module is used for acquiring one or more images with the similarity of the image characteristics of the one or more target entity objects being larger than or equal to the preset threshold.
Optionally, the apparatus further comprises:
a storage module to store the one or more images into an image collection corresponding to the one or more target entity objects.
Optionally, the memory module is further used for
And under the condition that the target entity objects are multiple, respectively storing one or more images corresponding to the multiple target entity objects into corresponding image subsets, wherein the image set comprises multiple image subsets, and each target entity object corresponds to one image subset.
Optionally, the selecting module 74 includes:
receiving the one or more target entity objects selected through interactive operation with a display interface; alternatively, the first and second electrodes may be,
selecting the one or more target entity objects from the one or more entity objects according to a preset rule;
and displaying the one or more target entity objects at a preset position of the display interface.
Optionally, the apparatus further comprises:
and the storage module is used for storing the target search condition into a historical retrieval record according to the time sequence.
Optionally, the target image is acquired by a camera or is obtained from a video.
It should be noted that, the above modules may be implemented by software or hardware, and for the latter, the following may be implemented, but not limited to: the modules are all positioned in the same processor; alternatively, the modules are respectively located in different processors in any combination.
Example 3
Embodiments of the present invention also provide a computer-readable storage medium, in which a computer program is stored, wherein the computer program is configured to perform the steps of any of the above method embodiments when executed.
Alternatively, in the present embodiment, the storage medium may be configured to store a computer program for executing the steps of:
s1, acquiring one or more entity objects in the target image, and marking the one or more entity objects in the target image;
s2, selecting one or more target entity objects from the one or more entity objects;
s3, determining target search conditions according to the one or more target entity objects;
and S4, performing image retrieval based on the target search condition.
Optionally, in this embodiment, the storage medium may include, but is not limited to: various media capable of storing computer programs, such as a usb disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic disk, or an optical disk.
Example 4
Embodiments of the present invention also provide an electronic device comprising a memory having a computer program stored therein and a processor arranged to run the computer program to perform the steps of any of the above method embodiments.
Optionally, the electronic apparatus may further include a transmission device and an input/output device, wherein the transmission device is connected to the processor, and the input/output device is connected to the processor.
Optionally, in this embodiment, the processor may be configured to execute the following steps by a computer program:
s1, acquiring one or more entity objects in the target image, and marking the one or more entity objects in the target image;
s2, selecting one or more target entity objects from the one or more entity objects;
s3, determining target search conditions according to the one or more target entity objects;
and S4, performing image retrieval based on the target search condition.
Optionally, the specific examples in this embodiment may refer to the examples described in the above embodiments and optional implementation manners, and this embodiment is not described herein again.
It will be apparent to those skilled in the art that the modules or steps of the present invention described above may be implemented by a general purpose computing device, they may be centralized on a single computing device or distributed across a network of multiple computing devices, and alternatively, they may be implemented by program code executable by a computing device, such that they may be stored in a storage device and executed by a computing device, and in some cases, the steps shown or described may be performed in an order different than that described herein, or they may be separately fabricated into individual integrated circuit modules, or multiple ones of them may be fabricated into a single integrated circuit module. Thus, the present invention is not limited to any specific combination of hardware and software.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the principle of the present invention should be included in the protection scope of the present invention.
Claims (11)
1. An image retrieval processing method, comprising:
acquiring one or more entity objects in a target image, and marking the one or more entity objects in the target image;
selecting one or more target entity objects from the one or more entity objects;
determining a target search condition according to the one or more target entity objects;
and performing image retrieval based on the target search condition.
2. The method of claim 1, wherein performing image retrieval based on the target search criteria comprises:
and acquiring one or more images with the similarity of the image characteristics of the one or more target entity objects larger than or equal to a preset threshold value from a database according to the target search condition.
3. The method of claim 2, wherein obtaining one or more images from a database having a similarity to the image features of the one or more target physical objects greater than or equal to a predetermined threshold according to the target search criteria comprises:
comparing the image characteristics of the one or more target entity objects in the target search condition with the entity objects of all the images in the database respectively;
acquiring one or more images with similarity of image features of the one or more target solid objects greater than or equal to the predetermined threshold.
4. The method of claim 2, wherein after performing image retrieval based on the target search criteria, the method further comprises:
storing the one or more images into a set of images corresponding to the one or more target entity objects.
5. The method of claim 4, wherein storing the one or more images into a set of images corresponding to the one or more target physical objects comprises:
and under the condition that the target entity objects are multiple, respectively storing one or more images corresponding to the multiple target entity objects into corresponding image subsets, wherein the image set comprises multiple image subsets, and each target entity object corresponds to one image subset.
6. The method of claim 1, wherein selecting a target entity object from the one or more entity objects comprises:
receiving the one or more target entity objects selected through interactive operation with a display interface; alternatively, the first and second electrodes may be,
selecting the one or more target entity objects from the one or more entity objects according to a preset rule;
and displaying the one or more target entity objects at a preset position of the display interface.
7. The method of any one of claims 1 to 6, wherein after determining the target search criteria from the one or more target entity objects, the method further comprises:
and storing the target search condition into a historical retrieval record according to the time sequence.
8. The method according to any one of claims 1 to 6, wherein the target image is captured by a camera or is obtained from a video.
9. An image search processing device characterized by comprising:
the system comprises an acquisition module, a display module and a display module, wherein the acquisition module is used for acquiring one or more entity objects in a target image and marking the one or more entity objects in the target image;
a selecting module for selecting one or more target entity objects from the one or more entity objects;
a determining module, configured to determine a target search condition according to the one or more target entity objects;
and the image retrieval module is used for carrying out image retrieval based on the target search condition.
10. A computer-readable storage medium, in which a computer program is stored, wherein the computer program is configured to carry out the method of any one of claims 1 to 8 when executed.
11. An electronic device comprising a memory and a processor, wherein the memory has stored therein a computer program, and wherein the processor is arranged to execute the computer program to perform the method of any of claims 1 to 8.
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