TW202213169A - Method, apparatus and device for identifying recognition object, and storage medium - Google Patents

Abstract

A method, apparatus and device for identifying a recognition object, and a storage medium. The method comprises: acquiring a photographing preview image which comprises at least two human faces; extracting the feature information of each of the at least two human faces in the photographing preview image, wherein the feature information comprises a face size value; and according to the face size value of each human face, determining the human face with face size value satisfying a preset recognition condition to be the recognition object. During the human face acquisition process, a suitable target human face can be selected as the recognition object from the at least two human faces, and the accuracy of recognition object identification can be improved.

Description

Identification object determination method, device, device and storage medium

The present invention relates to the technical field of computer vision, and in particular, to a method, device, device and storage medium for determining a recognition object.

At present, face recognition is widely used in production, finance, security, transportation and other fields due to its accuracy, safety, convenience and many other characteristics. For example, attendance machines, unmanned retail machines, access control systems, etc.

However, due to the open use environment of face recognition, in the process of face collection, multiple faces often appear, especially in queuing scenes, such as face-swiping payment, gate crossing, personnel check-in, etc. Scenes. Therefore, it is easy to cause errors in the determination of the recognized objects, and the accuracy of the determination of the recognized objects is poor.

Embodiments of the present invention provide a method, apparatus, device, and storage medium for determining an identification object, which can improve the accuracy of determining an identification object.

In a first aspect, an embodiment of the present invention provides a method for determining an identification object, the method comprising:

acquiring a shooting preview image, wherein the shooting preview image includes at least two faces;

extracting feature information of each of the at least two faces in the shot preview image, wherein the feature information includes a face size value;

According to the face size value of each face, it is determined that the face whose face size value satisfies the preset recognition condition is the recognition object.

In a second aspect, an embodiment of the present invention provides an apparatus for determining an identification object, The device includes:

an acquisition module for acquiring a shooting preview image, wherein the shooting preview image includes at least two faces;

an extraction module for extracting feature information of each of the at least two faces in the shot preview image, wherein the feature information includes a face size value;

The determining module is used for determining, according to the face size value of each face, the face whose face size value satisfies the preset recognition condition as the recognition object.

In a third aspect, an embodiment of the present invention provides a device for determining an identification object, the device includes: a processor and a memory storing computer program instructions; when the processor executes the computer program instructions, the first aspect or any of the first aspects can be implemented The identification object determination method described in the method.

In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, where computer program instructions are stored on the computer-readable storage medium, and when the computer program instructions are executed by a processor, the first aspect or any of the first aspects can be implemented. The identification object determination method.

An embodiment of the present invention provides a method, device, device, and storage medium for determining a recognition object. By extracting the face size value of each face in the shot preview image, and determining the face size value according to the face size value of each face The face that meets the preset recognition conditions is the recognition object. A suitable target face can be selected as the recognition object in the face collection process, so as to realize the accurate determination of the recognition object and improve the accuracy of the recognition object determination.

10: Quadrant 1

11: Quadrant 1

110: Shooting equipment

120: Electronic Equipment

20: Quadrant 2

21: Quadrant 2

30: The third quadrant

31: The third quadrant

40: Fourth quadrant

41: Quadrant 4

600: Recognition object determination device

610: Get Mods

620: Extract Mods

630: Determine the module

700: Identify the object to determine the device

701: Input device

702: Input interface

703: CPU

704: Memory

705: Output interface

706: Output device

710: Busbar

A: Relative position

C: Central area

G: Whether the coordinates of the center point of the face are located in the central area C

L: Quadrant where the coordinates of the center point of the face are located

LC: absolute position

LG: location marker

S210, S220, S230, S301, S302, S303, S304, S305, S306, S307, S308, S309, S310, S311, S312, S313, S314, S315, S316, S317: Steps

In order to describe the technical solutions of the embodiments of the present invention more clearly, the following briefly introduces the drawings that need to be used in the embodiments of the present invention. For those of ordinary skill in the art, under the premise of no creative work, the Other schemas can be obtained from these schemas.

1 is a schematic diagram of the architecture of a system for determining an identification object provided by an embodiment of the present invention;

2 is a schematic flowchart of a method for determining an identification object provided by an embodiment of the present invention;

3 is a schematic flowchart of another method for determining an identification object provided by an embodiment of the present invention;

4 is a schematic diagram of a region division provided by an embodiment of the present invention;

5 is a schematic diagram of a relative position provided by an embodiment of the present invention;

6 is a schematic structural diagram of an apparatus for determining an identification object provided by an embodiment of the present invention;

FIG. 7 is a schematic structural diagram of a device for determining an identification object according to an embodiment of the present invention.

The features and exemplary embodiments of various aspects of the present invention will be described in detail below. In order to make the objectives, technical solutions and advantages of the present invention more clear, the present invention will be further described in detail below with reference to the drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present invention, rather than limiting. It will be apparent to those skilled in the art that the present invention may be practiced without some of these specific details. The following description of the embodiments is only intended to provide a better understanding of the present invention by illustrating examples of the invention.

It should be noted that, in this document, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any relationship between these entities or operations. any such actual relationship or sequence exists. Moreover, the terms "comprising", "comprising" or any other variation thereof are intended to encompass non-exclusive inclusion such that a process, method, article or device comprising a list of elements includes not only those elements, but also includes not explicitly listed or other elements inherent to such a process, method, article or apparatus. Without further limitation, an element defined by the phrase "comprises" does not preclude the presence of additional identical elements in a process, method, article, or device that includes the element.

At present, the traditional identification object determination scheme mainly reduces the occurrence of multiple faces on the display screen by optimizing the business process and adjusting the angle of deployment of the shooting equipment. Generally, the first face that appears on the screen is obtained as a follow-up business execution. Identify objects in the process. However, in face recognition scenarios with high traffic flow, such as face-swiping payment, face-swiping entry, and face-swiping through gates, multiple faces often appear on the display screen. Therefore, misrecognition may occur, that is, the "bystander" or "behind" face is used as the recognition object, which affects the user experience.

Therefore, in order to solve the problems of the prior art, the embodiments of the present invention provide a An identification object determination method, apparatus, device and storage medium. By extracting the face size value of each face in the shot preview image, and according to the face size value of each face, it is determined that the face whose face size value satisfies the preset recognition condition is the recognition object. A suitable target face can be selected as the recognition object in the face collection process, so as to realize the accurate determination of the recognition object and improve the accuracy of the recognition object determination.

The method, apparatus, device, and storage medium for determining an identification object provided by the embodiments of the present invention will be described in detail below with reference to the drawings, through specific embodiments and application scenarios thereof.

FIG. 1 is a schematic structural diagram of a recognition object determination system provided by an embodiment of the present invention. As shown in FIG. 1 , the recognition object determination system may include a photographing device 110 and an electronic device 120 . The photographing device 110 may be a lens, a device equipped with a lens module, and the like. The electronic device 120 may be a mobile electronic device or a non-mobile electronic device. For example, the mobile electronic device may be a mobile phone, a tablet computer, a notebook computer, a palmtop computer, an Ultra-Mobile Personal Computer (UMPC), a small notebook or a Personal Digital Assistant (PDA), etc. , the non-mobile electronic device may be a server, a Network Attached Storage (NAS), a Personal Computer (PC), an ATM or a self-service machine, and so on. There is a communication connection between the photographing device 110 and the electronic device 120 . For example, the communication takes place via a network, wherein the network can be a wired communication network or a wireless communication network. Exemplarily, the photographing device 110 may be integrated into the electronic device 120 as a module.

As an example, the recognition object determination system can be applied to face recognition scenarios such as face-swiping payment, face-swiping entry, and face-swiping check-in. In these scenarios, due to the rapid collection of faces and the large flow of people, it is easy for multiple faces to gather on the display screen.

Referring to FIG. 1 , the electronic device 120 may acquire a shooting preview image of the user by the shooting device 110 , wherein the shooting preview image includes at least two users, that is, at least two human faces. Then, feature information of each face in the shot preview image is extracted, wherein the feature information includes a face size value. Then according to the face size value of each face, determine that the face size value satisfies The face of the preset recognition condition is the recognition object to perform the subsequent face recognition business.

The following will introduce the identification object determination method provided by the embodiment of the present invention. Wherein, the execution subject of the identification object determination method may be the electronic device 120 in the identification object determination system shown in FIG. 1 , or a module in the electronic device 120 .

FIG. 2 is a schematic flowchart of a method for determining an identification object provided by an embodiment of the present invention. As shown in FIG. 2 , the method for determining an identification object may include the following steps:

S210, acquiring a shooting preview image.

Wherein, the shooting preview image includes at least two faces, which can be collected by the shooting device on site. For example, the shooting preview image may be a previewed screen input frame, that is, an image displayed on the display screen when the shooting device shoots.

S220: Extract feature information of each of the at least two faces in the shot preview image.

The feature information includes a face size value. Exemplarily, the face size value may include the face-eye distance value or the number of face pixels, etc., wherein the face size value is represented by the face-eye distance value, which can reduce the noise of the face size difference.

In one embodiment, a face recognition algorithm may be used to perform preliminary face recognition on the captured preview image, and recognize the face therein. Then perform feature extraction on the recognized faces to obtain feature information of each face.

S230, according to the face size value of each face, determine the face whose face size value satisfies the preset recognition condition as the recognition object.

Among them, the recognition object will be used for face recognition as the main body of subsequent face recognition business execution.

The face that is the object of recognition is usually the closest to the photographing device than other photographed faces. Therefore, in one embodiment, the face with the largest face size value may be determined as the recognition object, so as to realize accurate determination of the recognition object.

In addition, the face as the recognition target has a size advantage over other faces. In another embodiment, the face size value of the at least two faces can be calculated separately The ratio of the face size value to the largest face size value for each face except the largest face. When at least one of the ratios is less than or equal to the first preset ratio threshold, the face corresponding to the maximum face size value is determined as the recognition object, which improves the accuracy of the recognition object determination. It can be understood that the first preset ratio threshold can be flexibly set according to the actual situation, for example, it can be 60%.

It can be seen that usually the user will not leave the current position during the recognition and use process, and the face will always appear on the screen. Therefore, in an example, when the at least one ratio is less than or equal to the first preset ratio threshold, the duration of displaying the face corresponding to the maximum face size value on the display screen can be obtained. When the display duration of the face corresponding to the maximum face size value is greater than or equal to the preset duration threshold, the face corresponding to the maximum face size value is determined as the recognition object. By introducing the display duration as a judgment factor on the basis of the face size value, the precise determination of the recognized object can be further improved.

As a specific example, face tracking of consecutive frames may be performed on the face corresponding to the maximum face size value. Exemplarily, a unique face identification can be assigned to the face corresponding to the maximum face size value. During the face tracking process of consecutive frames, the face identification remains unchanged when the same face does not leave, so The continuous display duration of the face corresponding to the maximum face size value can be counted. Further, when the continuous display duration is greater than or equal to T, the face corresponding to the maximum face size value is used as the recognition object. Wherein, T represents a preset duration threshold, which may be an absolute duration, such as 800ms. It can also be a relative duration, such as the time to complete a period of business processing. For example, in the scene of swiping your face and entering the station, the duration of passing through the channel of the designated shooting area, that is, the duration of the user from entering to leaving the specific shooting area (without leaving the coverage of the shooting equipment); for example, collecting continuous frame images to a certain number ( Such as 5) time; another example is the transaction response time (the time to obtain a recognition transaction result), that is, when starting to track the face corresponding to the maximum face size value, the recognition is initiated until the duration of the response result is received, During this time, the face corresponding to the maximum face size value is always displayed on the display screen.

In another embodiment, the first position of the face corresponding to the maximum face size value may be obtained. When the first position satisfies the preset position condition, the face corresponding to the maximum face size value is determined as the recognition object, that is, the position is introduced as a judgment factor on the basis of the face size value, Improve the precise determination of recognized objects. The preset position condition may include: the first position matches the preset position, or the first position is located in a preset area. It can be understood that the preset position and the preset area can be flexibly set according to the actual situation, for example, they can be preselected according to the debugging experience when the scene layout is implemented.

In the embodiment of the present invention, by extracting the face size value of each face in the shot preview image, and according to the face size value of each face, it is determined that the face whose face size value satisfies the preset recognition conditions is the recognition object. A suitable target face can be selected as the recognition object during the face collection process, and the accuracy of the recognition object determination can be improved.

In one embodiment, when any one of the at least one ratio is greater than the first preset ratio threshold, the method may further include:

First, when at least one ratio is less than or equal to the second preset ratio threshold, the first position of the face corresponding to the maximum face size value is acquired. The second preset ratio threshold is greater than the first preset ratio threshold, for example, the first preset ratio threshold is 60%, and the second preset ratio threshold is 80%. Moreover, the first preset ratio threshold and the second preset ratio threshold can be adjusted according to the accuracy rate determined by the identification object after a period of time. Exemplarily, completing the business process, that is, identifying the object and determining the correct face picture, can be selected as a positive sample. Select the face image in which the user manually cancels the business process to identify the wrong object as a negative sample. According to the proportion of positive and negative samples to the total samples, the accuracy rate determined by the recognition object is counted, and the first preset ratio threshold and the second preset ratio threshold are adjusted according to the accuracy, so as to realize dynamic adjustment of the threshold.

Then, when the first position satisfies the preset position condition, the face corresponding to the maximum face size value is determined as the recognition object. In this embodiment, the second preset ratio threshold and the position are introduced for further judgment, and the conditions for determining the identification object are refined, which can further improve the accuracy of determining the identification object.

It can be understood that in the face recognition scene, the user who is the target of recognition usually actively approaches the shooting device, and the face is directly facing on the display screen, and generally has the characteristics of clearly visible, unobstructed, and open eyes. In one embodiment, the feature information may further include face angle, face occlusion information, face eye information, and so on. Then, according to the face angle, Face occlusion information and face and eye information screen at least two faces, that is, the face angle, face occlusion information, and face and eye information are used as judging factors to filter the faces in the captured preview image and keep them Faces that meet the corresponding conditions.

Further, at least two faces can be screened according to face size value, face angle, face occlusion information, and face eye information. And according to the face size value of the screened face, it is determined that the face whose face size value satisfies the preset recognition condition is the recognition object. In this example, by screening faces in multiple dimensions, and selecting an appropriate face from the screened faces as the recognition object, the accuracy of determining the recognition object can be improved.

In the following, the method for determining an identification object is applied to a face-swiping payment scenario as an example, and the method for determining an identification object provided by an embodiment of the present invention will be described in detail. As shown in FIG. 3 , the method may include the following steps:

S301. Acquire a shooting preview image of a user shot by a shooting device on-site.

S302. Identify the face in the shot preview image according to the face recognition algorithm.

S303. Screen the faces in the shot preview image.

Specifically, the feature information of each face can be extracted first. The feature information includes face size value, face angle, face occlusion information, and face eye information.

Secondly, the face size value can be judged for each face, and the faces whose face size value is greater than or equal to the preset size threshold are retained. As an example, the face size value is represented by the number of face pixels, and the preset size threshold may be set to 100*100, where 100*100 represents the width and height of the face pixels.

Then, face angle judgment may be performed, and faces whose face angles are less than or equal to a preset angle threshold are retained. As an example, the face angle includes a roll angle (roll), a pitch angle (pitch), and a yaw angle (yaw), the preset angle thresholds corresponding to the three types of angles may be ±20°, and the three types of angles are reserved to be less than or equal to A face equal to ±20°.

Then, the face occlusion information can be judged, and the faces whose face occlusion information meets the face occlusion condition are reserved. As an example, the face occlusion conditions can be flexibly set according to business requirements, such as no occlusion at all, no occlusion at key points, no occlusion area exceeding a certain percentage, etc. Wait.

Furthermore, it is possible to judge the face and eye information to judge whether the face has closed eyes, so as to retain the face that has not closed eyes. It is worth noting that the above judgment steps can be flexibly adjusted according to business needs, for example, it can be appropriately increased or decreased, the order of changes, etc., which are not limited here.

S304. Determine whether the filtered face is unique.

If yes, execute S305, otherwise, execute S308.

S305. Acquire the duration that the unique face is displayed on the display screen.

S306. Determine whether the display duration of the unique face is greater than or equal to a preset duration threshold.

If yes, execute S307, otherwise, execute S317.

S307. Determine the unique face as the recognition object.

S308: Calculate the ratio of the face size value to the maximum face size value of each face except the face with the largest face size value.

S309. Determine whether the ratios are all less than or equal to the first preset ratio threshold.

If yes, execute S310, otherwise, execute S313.

S310. Acquire the duration that the face corresponding to the maximum face size value is displayed on the display screen.

S311. Determine whether the display duration is greater than or equal to a preset duration threshold.

If yes, execute S312, otherwise, execute S317.

S312. Determine the face corresponding to the maximum face size value as the recognition object.

S313. Determine whether the ratios are all less than or equal to a second preset ratio threshold.

If yes, execute S314, otherwise, execute S317.

S314: Obtain the first position of the face corresponding to the maximum face size value.

The first position may include an absolute position of the face corresponding to the largest face size value, and a relative position using the face corresponding to the second largest face size value as a reference point.

Specifically, the shooting preview image can be divided according to the preset area division rules, the position mark of the face can be determined according to the divided area, and the absolute position of the face can be represented by the position mark. Location. Referring to FIG. 4 , the area division rule may be to divide the shot preview image according to the center point, and divide it into four quadrants: the first quadrant, the second quadrant, the third quadrant, and the fourth quadrant according to the mathematical plane coordinate system. At the same time, taking the center point as the origin, taking half the width of the preview image as the width, and taking half the height of the preview image as the height, as the central area C. Among them, the central area C coincides with the quadrant area.

As an example, a plane coordinate system can be constructed with the center point as the origin (0, 0). For the face in the shot preview image, calculate the coordinates (x, y) of the center point of the face, and determine the position mark of the face according to the coordinates of the center point of the face and the divided area. The location marker can be LG. Among them, L represents the quadrant where the coordinates of the center point of the face are located, and takes a value of 1, 2, 3, or 4, and when L is 1, it means that it is located in the first quadrant. G indicates whether the coordinates of the center point of the face are located in the central area C, and takes a value of 0 or 1. When G is 0, it means that it is not located in the central area C, and when G is 1, it means that it is located in the central area C. Among them, the location here includes the coordinates of the center point on the boundary. Specifically, the position marks may be as follows: not located in the central area C: the first quadrant: 10, the second quadrant: 20, the third quadrant: 30, the fourth quadrant: 40; located in the central area C: the first quadrant: 11, the first Second quadrant: 21, third quadrant: 31, fourth quadrant: 41. Specifically, taking the position marker 10 as an example, it indicates that the coordinates of the center point of the face are located in the first quadrant and not located in the center area. Taking the position marker 11 as an example, it indicates that the coordinates of the center point of the face are located in the center area and the first quadrant. As shown in FIG. 4 , the center coordinate of the face 1 is located in the third quadrant, and is not located in the center area C, so the position is marked as 30 . The center coordinates of the face 2 are located in the first and second quadrants, and are located in the center area C, the positions are marked as 11 and 21. The center coordinate of the face 3 is located in the first quadrant, and is located in the center area C, the position is marked as 11. It can be understood that the area division rules can be flexibly adjusted according to actual needs, which is not limited here.

Among them, the relative position can be calculated by using the relative position calculation formula. With reference to Figure 5, the relative position calculation formula can be as follows:

A(X, Y)=O ₁ (x ₁ , y ₁ )-O ₂ (x ₂ , y ₂ ) (1)

Among them, A(X, Y) represents a vector, O ₁ (x ₁ , y ₁ ) represents the face center point coordinates of the second largest face, and O ₂ (x ₂ , y ₂ ) represents the face center point of the largest face coordinate. Among them, X>0 means that the largest face is on the horizontal axis, on the left side of the second largest face, otherwise it is on the right; Y>0 means the largest face is on the vertical axis, below the second largest face , and vice versa above.

S315. Determine whether the first position satisfies the preset position condition.

Wherein, the preset position condition includes: the first position matches the preset position, or the first position is located in a preset area. In a certain fixed scene, the absolute position and relative position of the recognition object on the display screen often appear to have a certain aggregation. It can be understood that the location of the gathering is different depending on the scene or the angle of the shooting equipment. In the scene application, a certain number (such as 100,000) of face recognition scene images with multiple faces can be selected, data processing is performed on them, the recognition object and the second largest face are marked, and the relative position and Absolute position, that is, classify each image, count the absolute position LC value, and the relative position A (X, Y). Position, confirm the absolute position and relative position of the recognition object that often appear in the scene, and use it as the preset position, or determine the preset area according to multiple frequently occurring absolute positions and relative positions. By setting a preset position or a preset area in a scene of practical application, the accuracy of identifying the object can be improved. On this basis, it is judged whether the first position satisfies the preset position condition, and if so, S316 is executed, otherwise, S317 is executed.

S316: Determine the face corresponding to the maximum face size value as the recognition object.

S317, prompting that the identification object cannot be determined.

Specifically, a voice prompt similar to "The recognition object cannot be determined, please watch the user back" can be issued.

In another example, S308 may be to calculate the first product of the maximum face size value and the first preset ratio threshold, and use the first product as the first size threshold.

S309 may be to determine whether the face size value of each face except the face with the largest face size value is less than or equal to the first size threshold. If yes, execute S310, otherwise, execute S313.

S313 may be to calculate the second product of the maximum face size value and the second preset ratio threshold, use the second product as the second size threshold, and determine the face with the largest face size value except for In addition, whether the face size value of each face is less than or equal to the second size threshold, if so, execute S314, otherwise, execute S317.

Based on the identification object determination method provided by the embodiment of the present invention, the embodiment of the present invention further provides an identification object determination apparatus. As shown in FIG. 6 , the identification object determination apparatus 600 may include: an acquisition module 610, an extraction module 620, a determination Module 630.

The acquisition module 610 is used for acquiring a shooting preview image, wherein the shooting preview image includes at least two human faces.

The extraction module 620 is configured to extract feature information of each of the at least two faces in the shot preview image, wherein the feature information includes a face size value.

The determining module 630 is configured to determine, according to the face size value of each face, the face whose face size value satisfies the preset recognition condition as the recognition object.

In one embodiment, the determining module includes: a first determining unit, configured to determine the face with the largest face size value as the recognition object.

In one embodiment, the determining module includes: a calculating unit, configured to separately calculate the face size value and the maximum face size value of each face except the face with the largest face size value among the at least two faces. ratio.

The second determining unit is configured to determine the face corresponding to the maximum face size value as the recognition object when at least one ratio is less than or equal to the first preset ratio threshold.

In one embodiment, the second determining unit includes: an obtaining subunit, configured to obtain a face corresponding to the maximum face size value displayed on the display screen when at least one ratio is less than or equal to the first preset ratio threshold duration.

The determining subunit is configured to determine the face corresponding to the maximum face size value as the recognition object when the display duration of the face corresponding to the maximum face size value is greater than or equal to the preset duration threshold.

In one embodiment, the obtaining module is further configured to obtain the maximum face size when any one of the at least one ratio is greater than the first preset ratio threshold, and the at least one ratio is less than or equal to the second preset ratio threshold value corresponds to the first position of the face, where the first The second preset ratio threshold is greater than the first preset ratio threshold.

The determining module is further configured to determine the face corresponding to the maximum face size value as the recognition object when the first position satisfies the preset position condition.

In one embodiment, the determining module includes: an obtaining unit, configured to obtain the first position of the face corresponding to the maximum face size value.

The third determining unit is configured to determine the face corresponding to the maximum face size value as the recognition object when the first position satisfies the preset position condition.

In one embodiment, the preset position condition includes: the first position matches the preset position, or the first position is located in a preset area.

In one embodiment, the feature information further includes face angle, face occlusion information, and face eye information.

The determination module includes: a screening unit for screening at least two faces according to face angle, face occlusion information, and face eye information.

The fourth determining unit is configured to determine, according to the face size value of the screened face, a face whose face size value satisfies a preset recognition condition as a recognition object.

In one embodiment, the face size value includes a face-eye distance value or the number of face pixels.

It can be understood that each module/unit in the identification object determination device 600 shown in FIG. 6 has the function of implementing each step in the identification object determination method provided by the embodiment of the present invention, and can achieve its corresponding technical effect. It is concise and will not be repeated here.

FIG. 7 is a schematic structural diagram of a device for determining an identification object according to an embodiment of the present invention.

As shown in FIG. 7 , the identification object determination device 700 in this embodiment includes an input device 701 , an input interface 702 , a central processing unit 703 , a memory 704 , an output interface 705 , and an output device 706 . Among them, the input interface 702, the central processing unit 703, the memory 704, and the output interface 705 are connected to each other through the bus bar 710, and the input device 701 and the output device 706 are respectively connected to the bus bar 710 through the input interface 702 and the output interface 705, and then to the bus bar 710. Identify pairs Other elements of the device 700 are connected as determined.

Specifically, the input device 701 receives input information from the outside, and transmits the input information to the central processing unit 703 through the input interface 702 ; the central processing unit 703 processes the input information based on the computer-executable instructions stored in the memory 704 to generate Output information, temporarily or permanently store the output information in the memory 704, and then transmit the output information to the output device 706 through the output interface 705; the output device 706 outputs the output information to the outside of the identification object determination device 700 for the user to use .

In one embodiment, the identification object determination device 700 shown in FIG. 7 includes: a memory 704 for storing a program; a processor 703 for running the program stored in the memory to realize the identification provided by the embodiment of the present invention Object determination method.

Embodiments of the present invention further provide a computer-readable storage medium, where computer program instructions are stored thereon; when the computer program instructions are executed by a processor, the identification object determination method provided by the embodiments of the present invention is implemented.

It should be clear that each embodiment in this specification is described in a progressive manner, and the same or similar parts between the various embodiments may be referred to each other, and for the sake of brevity, details are not repeated. The invention is not limited to the specific arrangements and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above-described embodiments, several specific steps are described and shown as examples. However, the method process of the present invention is not limited to the specific steps described and shown, and those skilled in the art can make various changes, modifications and additions, or change the order of steps after comprehending the spirit of the present invention.

The functional blocks shown in the structural block diagrams described above can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, it can be, for example, an electronic circuit, an application specific integrated circuit (ASIC), suitable firmware, a plug-in program, a function card, and the like. When implemented in software, elements of the invention are programs or code segments that are used to perform the required tasks. The program, or segments of program code, can be stored on a machine-readable medium or transmitted over a transmission medium or communication link by a data signal carried in a carrier wave. "Machine-readable medium" may include any medium capable of storing or transmitting information any medium. Examples of machine-readable media include electronic circuits, semiconductor memory devices, Read-Only Memory (ROM), flash memory, Erasable Read Only Memory (EROM), floppy disks, optical disks Read-only memory (Compact Disc Read-Only Memory, CD-ROM), optical disc, hard disk, optical media, radio frequency (Radio Frequency, RF) link, and so on. The code snippets may be downloaded via a computer network such as the Internet, an intranet, or the like.

It should also be noted that the exemplary embodiments mentioned in the present invention describe some methods or systems based on a series of steps or devices. However, the present invention is not limited to the order of the above steps, that is to say, the steps may be performed in the order mentioned in the embodiments, or may be different from the order in the embodiments, or several steps may be performed simultaneously.

Aspects of the present disclosure are described above with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the disclosure. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to the processor of a general purpose computer, special purpose computer, or other programmable data processing device to produce a machine in which the instructions executed by the processor of the computer or other programmable data processing device cause the Implementations of the functions/acts specified in one or more blocks of the flowchart and/or block diagrams can be performed. Such processors may be, but are not limited to, general purpose processors, special purpose processors, application specific processors, or field programmable logic circuits. It will also be understood that each block of the block diagrams and/or flowchart illustrations, and combinations of blocks in the block diagrams and/or flowchart illustrations, can also be implemented by dedicated hardware for performing the specified functions or actions, or A combination of dedicated hardware and computer instructions is implemented.

The above are only specific embodiments of the present invention, and those skilled in the art can clearly understand that, for the convenience and simplicity of description, the specific working process of the above-described systems, modules and units can be implemented with reference to the aforementioned methods. The corresponding process in the example will not be repeated here. It should be understood that the protection scope of the present invention is not limited to this. Any person skilled in the art can easily think of various equivalent modifications or replacements within the technical scope disclosed in this application, and these modifications or replacements should be covered in within the protection scope of the present invention.

S210, S220, S230: Steps

Claims (20)

A method for determining an identification object, characterized in that the method comprises: acquiring a shooting preview image, wherein the shooting preview image includes at least two faces; extracting feature information of each of the at least two faces in the shooting preview image, wherein the feature information includes a face size value; According to the face size value of each face, it is determined that the face whose face size value satisfies the preset recognition condition is the recognition object. The method according to claim 1, characterized in that, according to the face size value of each face, determining that the face whose face size value satisfies the preset recognition condition is the recognition object, comprising: Determine the face with the largest face size value as the recognition object. The method according to claim 1, characterized in that, according to the face size value of each face, determining that the face whose face size value satisfies the preset recognition condition is the recognition object, comprising: Respectively calculate the ratio of the face size value of each face to the maximum face size value except the face with the largest face size value in the at least two faces; When at least one of the ratios is less than or equal to the first preset ratio threshold, the face corresponding to the maximum face size value is determined as the recognition object. The method according to claim 3, wherein when at least one of the ratios is less than or equal to a first preset ratio threshold, determining the face corresponding to the maximum face size value as the recognition object ,include: When at least one of the ratios is less than or equal to the first preset ratio threshold, acquiring the time duration for which the face corresponding to the maximum face size value is displayed on the display screen; When the display duration of the face corresponding to the maximum face size value is greater than or equal to a preset duration threshold, it is determined that the face corresponding to the maximum face size value is the recognition object. The method according to claim 3, wherein when any one of the at least one ratio is greater than a first preset ratio threshold, the method further comprises: When at least one of the ratios is less than or equal to a second preset ratio threshold, obtain the first position of the face corresponding to the maximum face size value, wherein the second preset ratio threshold is greater than the first preset ratio threshold; When the first position satisfies the preset position condition, the face corresponding to the maximum face size value is determined as the recognition object. The method according to claim 1, characterized in that, according to the face size value of each face, determining that the face whose face size value satisfies the preset recognition condition is the recognition object, comprising: Obtain the first position of the face corresponding to the maximum face size value; When the first position satisfies the preset position condition, the face corresponding to the maximum face size value is determined as the recognition object. The method according to claim 5 or 6, wherein the preset location conditions include: The first position matches a preset position, or the first position is located in a preset area. The method according to claim 1, wherein the feature information further includes face angle, face occlusion information, and face eye information; According to the face size value of each face, it is determined that the face whose face size value satisfies the preset recognition conditions is the recognition object, including: Screen the at least two faces according to the face angle, the face occlusion information, and the face eye information; According to the face size value of the filtered face, it is determined that the face whose face size value satisfies the preset recognition condition is the recognition object. The method according to claim 1, wherein the face size value includes a face-eye distance value or the number of face pixels. A device for identifying an object, characterized in that the device comprises: an acquisition module for acquiring a shooting preview image, wherein the shooting preview image includes at least two faces; an extraction module for extracting feature information of each of the at least two faces in the shooting preview image, wherein the feature information includes a face size value; Determine the module, which is used to determine that the face size value is full according to the face size value of each face The face that meets the preset recognition conditions is the recognition object. The device according to claim 10, wherein the determining module comprises: The first determining unit is configured to determine the face with the largest face size value as the recognition object. 1. The device of claim 10, wherein the determining module comprises: A computing unit, used to calculate the ratio of the face size value of each face to the maximum face size value in the at least two faces except the face with the largest face size value; A second determining unit, configured to determine a face corresponding to the maximum face size value as the recognition object when at least one of the ratios is less than or equal to a first preset ratio threshold. The device according to claim 12, wherein the second determining unit comprises: an acquisition subunit, configured to acquire the duration of the display of the face corresponding to the maximum face size value on the display screen when at least one of the ratios is less than or equal to the first preset ratio threshold; A determination subunit, configured to determine the face corresponding to the maximum face size value as the recognition object when the display duration of the face corresponding to the maximum face size value is greater than or equal to a preset duration threshold. The apparatus of claim 12, wherein: The obtaining module is further configured to obtain the maximum number of people when any one of the at least one ratio is greater than a first preset ratio threshold and at least one of the ratios is less than or equal to a second preset ratio threshold. the first position of the face corresponding to the face size value, wherein the second preset ratio threshold is greater than the first preset ratio threshold; The determining module is further configured to determine the face corresponding to the maximum face size value as the recognition object when the first position satisfies a preset position condition. The device according to claim 10, wherein the determining module comprises: an obtaining unit for obtaining the first position of the face corresponding to the maximum face size value; A third determining unit, configured to determine a face corresponding to the maximum face size value as the recognition object when the first position satisfies a preset position condition. The device according to claim 14 or 15, wherein the preset location conditions include: The first position matches a preset position, or the first position is located in a preset area. The device according to claim 10, wherein the feature information further includes face angle, face occlusion information, and face eye information; The determining module includes: a screening unit for screening the at least two faces according to the face angle, the face occlusion information, and the face and eye information; The fourth determining unit is configured to determine, according to the face size value of the screened face, a face whose face size value satisfies a preset recognition condition as a recognition object. The device according to claim 10, wherein the face size value includes a face-eye distance value or the number of face pixels. A device for determining an identification object, characterized in that the device comprises: a processor and a memory storing computer program instructions; when the processor executes the computer program instructions, any one of claim 1 to 9 is implemented. method for identifying objects. A computer-readable storage medium, characterized in that the computer-readable storage medium stores computer program instructions, and when the computer program instructions are executed by a processor, the identification object described in any one of claim items 1-9 is realized Determine the method.

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