CN111242106A

CN111242106A - Facial image acquisition method, device and equipment and facial recognition equipment

Info

Publication number: CN111242106A
Application number: CN202010332373.4A
Authority: CN
Inventors: 明泉水
Original assignee: Alipay Hangzhou Information Technology Co Ltd
Current assignee: Alipay Hangzhou Information Technology Co Ltd
Priority date: 2020-04-24
Filing date: 2020-04-24
Publication date: 2020-06-05
Also published as: WO2021213249A1

Abstract

The embodiment of the specification discloses a facial image acquisition method, a facial image acquisition device, facial image acquisition equipment and facial recognition equipment, wherein the method comprises the following steps: acquiring a target image including a facial image of a target user, which is acquired by a movable camera; analyzing the face image of the target user in the target image, and determining the position information of an image corresponding to a preset reference part in the face of the target user in the target image; and when the shooting position of the movable camera is determined to be not matched with the position corresponding to the reference part of the target user based on the position information, adjusting the shooting position of the movable camera based on the position information so as to enable the shooting position of the movable camera to be matched with the position corresponding to the reference part of the target user.

Description

Facial image acquisition method, device and equipment and facial recognition equipment

Technical Field

The present disclosure relates to the field of computer technologies, and in particular, to a method, an apparatus, a device, and a face recognition device for acquiring a face image.

Background

With the rapid development of the internet of things technology, unmanned selling equipment goes deep into the lives of people, and in order to improve the convenience of user payment, the unmanned selling equipment starts to provide a face-brushing payment service for users, but how to accurately acquire facial images of the users becomes the focus of attention of equipment operators.

At present, in unmanned equipment of selling, can dispose facial recognition device for acquire brush face user's facial image, but because facial recognition device's height is fixed, so, to the brush face user that height and facial recognition device height are not in same horizontal plane, this brush face user's facial image that facial device gathered just has inaccurate problem, lead to unmanned equipment of selling can't be accurate provide the service of brushing face payment for the user, consequently, need the facial image that can be accurate acquisition user to and the accurate solution that provides the service of brushing face payment for the user in time.

Disclosure of Invention

An object of the embodiments of the present specification is to provide a method, an apparatus, a device and a face recognition device for acquiring a facial image, so as to provide a solution that can accurately acquire a facial image of a user and accurately provide a face-brushing payment service for the user in real time.

In order to implement the above technical solution, the embodiments of the present specification are implemented as follows:

in a first aspect, an embodiment of the present specification provides a method for acquiring a facial image, where the method includes: acquiring a target image including a facial image of a target user, which is acquired by a movable camera; analyzing the face image of the target user in the target image, and determining the position information of the face of the target user and the image corresponding to a preset reference part in the target image; and when the shooting position of the movable camera is determined to be not matched with the position corresponding to the reference part of the target user based on the position information, adjusting the shooting position of the movable camera based on the position information so as to enable the shooting position of the movable camera to be matched with the position corresponding to the reference part of the target user.

In a second aspect, a facial recognition apparatus provided in an embodiment of the present specification includes a movable camera and a controller, where: the movable camera is positioned on the back of the screen of the face recognition equipment and is used for acquiring a target image including a face image of a target user through the screen of the face recognition equipment; the controller is used for acquiring a target image which is acquired by the movable camera and comprises a facial image of the target user; analyzing the face image of the target user in the target image, and determining the position information of an image corresponding to a preset reference part in the face of the target user in the target image; and when the shooting position of the movable camera is determined to be not matched with the position corresponding to the reference part of the target user based on the position information, adjusting the shooting position of the movable camera based on the position information so as to enable the shooting position of the movable camera to be matched with the position corresponding to the reference part of the target user.

In a third aspect, an embodiment of the present specification provides an apparatus for acquiring a facial image, the apparatus including: the image acquisition module is used for acquiring a target image which is acquired by the movable camera and comprises a facial image of a target user; the position acquisition module is used for analyzing the face image of the target user in the target image and determining the position information of an image corresponding to a preset reference part in the face of the target user in the target image; and the position adjusting module is used for adjusting the shooting position of the movable camera based on the position information under the condition that the shooting position where the movable camera is located currently is determined to be not matched with the position corresponding to the reference part of the target user based on the position information, so that the shooting position of the movable camera is matched with the position corresponding to the reference part of the target user.

In a fourth aspect, an embodiment of the present specification provides a facial image capturing apparatus, including: a processor; and a memory arranged to store computer executable instructions that, when executed, cause the processor to: acquiring a target image including a facial image of a target user, which is acquired by a movable camera; analyzing the face image of the target user in the target image, and determining the position information of an image corresponding to a preset reference part in the face of the target user in the target image; and when the shooting position of the movable camera is determined to be not matched with the position corresponding to the reference part of the target user based on the position information, adjusting the shooting position of the movable camera based on the position information so as to enable the shooting position of the movable camera to be matched with the position corresponding to the reference part of the target user.

Drawings

In order to more clearly illustrate the embodiments of the present specification or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, it is obvious that the drawings in the following description are only some embodiments described in the present specification, and for those skilled in the art, other drawings can be obtained according to the drawings without any creative effort.

FIG. 1 is a flow chart of an embodiment of a method for capturing facial images according to the present disclosure;

FIG. 2 is a schematic diagram of a method of acquiring an image of an object according to the present disclosure;

fig. 3 is a schematic diagram of a method for acquiring location information according to the present disclosure;

FIG. 4 is a flow chart of another embodiment of a method for capturing facial images;

FIG. 5 is a schematic diagram of region partitioning for a target image according to the present disclosure;

FIG. 6 is a schematic structural diagram of another embodiment of a facial image capturing device according to the present disclosure;

fig. 7 is a schematic structural diagram of another facial image capturing device according to the present disclosure.

Detailed Description

The embodiment of the specification provides a facial image acquisition method, a facial image acquisition device, facial image acquisition equipment and facial recognition equipment.

In order to make those skilled in the art better understand the technical solutions in the present specification, the technical solutions in the embodiments of the present specification will be clearly and completely described below with reference to the drawings in the embodiments of the present specification, and it is obvious that the described embodiments are only a part of the embodiments of the present specification, and not all of the embodiments. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments in the present specification without any creative effort shall fall within the protection scope of the present specification.

Example one

As shown in fig. 1, an implementation subject of the present specification may be an electronic device capable of providing a service such as face-brushing payment for a user, where the electronic device may be configured with a movable camera, and the electronic device may be, for example, a face-brushing payment device, an unmanned vending device, or the like. The method may specifically comprise the steps of:

in S102, a target image including a face image of a target user captured by the movable camera is acquired.

In implementation, with the rapid development of the internet of things technology, the unmanned vending equipment goes deep into the lives of people, and in order to improve the convenience of user payment, the unmanned vending equipment starts to provide a face-brushing payment service for users, but how to accurately acquire facial images of the users becomes the focus of attention of equipment operators. At present, in unmanned equipment of selling, can dispose facial recognition device for acquire brush face user's facial image, but because facial recognition device's height is fixed, so, to the brush face user that height and facial recognition device height are not in same horizontal plane, this brush face user's facial image that facial device gathered just has inaccurate problem, lead to unmanned equipment of selling can't be accurate provide the service of brushing face payment for the user, consequently, need the facial image that can be accurate acquisition user to and the accurate solution that provides the service of brushing face payment for the user in time. Therefore, the embodiments of the present disclosure provide a technical solution that can solve the above problems, and refer to the following specifically.

Taking an electronic device as an unmanned vending device as an example, when a target user selects a commodity in a screen of the unmanned vending device and clicks to purchase the commodity, the electronic device may collect a target image including a facial image of the target user through a movable camera, where the movable camera may be preset at a designated position of the electronic device and may be located at a preset initial position relative to the target user. For example, as shown in fig. 2, the movable camera in the unmanned aerial vehicle vending apparatus may be located at an initial position on the upper side of the screen, and in a case where the unmanned aerial vehicle vending apparatus receives a purchase instruction of a target user for a certain commodity, a target image including a face image of the target user may be acquired by the movable camera at the initial position.

In S104, the face image of the target user in the target image is analyzed, and the position information of the image corresponding to the preset reference position in the face of the target user in the target image is determined.

The preset reference position can be any preset position such as eyes, a nose, a mouth and the like. The reference part can be used for enabling the camera to acquire a more accurate and complete facial image of the user.

In implementation, the target image may be analyzed based on a preset image analysis algorithm, and position information of an image corresponding to a preset reference portion in the target user surface in the target image may be determined.

When the position information is acquired, the target image may be divided into a plurality of regions, and the corresponding position information may be determined according to the region information where the image corresponding to the reference portion preset in the target user surface is located in the target image.

For example, taking the preset reference position as a nose as an example, assuming that the acquired target image is as shown in fig. 3, and an image corresponding to the nose in the target user face is located in an area 2 in the target image, the corresponding position information may be position information where the area 2 is located.

In addition, the determination method of the position information is an optional and realizable determination method, and there may be a plurality of determination methods in an actual application scenario, which is not specifically limited in the embodiment of the present specification.

In addition, in order to ensure the accuracy of the determined position information, a plurality of reference positions can be preset, and the corresponding position information can be determined according to the sub-position information of the image corresponding to each reference position in the target image. For example, assuming that the reference portion includes eyes, a nose, and ears, if the images corresponding to the eyes and the nose in the target user's face are all in the region 1 in the target image, and the image corresponding to the ears in the target user's face is in the region 2 in the target image, it may be determined that the position information of the image corresponding to the reference portion preset in the target user's face in the target image is the position information of the region 1.

In S106, in a case where it is determined based on the position information that the photographing position at which the movable camera is currently located does not match the position corresponding to the reference part of the target user, the photographing position of the movable camera is adjusted based on the position information so that the photographing position of the movable camera matches the position corresponding to the reference part of the target user.

In implementation, based on the position information, it may be determined whether the shooting position where the movable camera is currently located matches a position corresponding to the reference part of the target user. For example, if the shooting position at which the movable camera is currently located is on the same horizontal line as the position corresponding to the reference part of the target user, it can be considered that the shooting position of the movable camera matches the position corresponding to the reference part of the target user. Or, if an included angle on the same horizontal plane between the current shooting position of the movable camera and the position corresponding to the reference position of the target user is within a preset included angle range, it may also be considered that the shooting position of the movable camera matches the position corresponding to the reference position of the target user.

Still alternatively, as shown in fig. 3, the target image may be divided into a plurality of regions (e.g., region 1, region 2, and region 3), and if the position corresponding to the reference portion preset in the target user surface is in the region 2 in the target image, it may be considered that the shooting position of the movable camera matches the position corresponding to the reference portion of the target user.

In a case where it is determined based on the position information that the photographing position where the movable camera is currently located does not match the position corresponding to the reference part of the target user, an adjustment direction and an adjustment distance for adjusting the photographing position of the movable camera may be determined based on the position information, and then the movable camera may be moved based on the adjustment direction, or an electronic device carrying the movable camera may also be moved based on the adjustment direction.

For example, assuming that the electronic device is an unmanned vending device, and an image corresponding to a reference portion preset in the target user surface is in an area 1 in the target image, in the acquired target image, the adjustment direction may be determined to be downward, and at this time, the movable camera may be controlled to move downward. As shown in the unmanned merchandiser of fig. 2, the movable camera may be moved from an initial position to the back side of the screen, i.e., downward.

Or, assuming that the electronic device is a face brushing payment device capable of providing face brushing payment for the user, and an image corresponding to a preset reference position in the face of the target user is in the region 3 in the target image, the adjustment direction may be determined to be upward, and at this time, the face brushing device may be controlled to move upward.

The method for adjusting the shooting position of the movable camera is an optional and realizable adjustment method, and in an actual application scenario, there may be multiple adjustment methods, which may be different according to different actual application scenarios, and this is not specifically limited in the embodiment of the present specification.

In addition, in the process of adjusting the movable camera, a target image including a face image of a target user collected by the movable camera may be acquired based on a preset detection period, then in the detection period, the face image of the target user in the target image is analyzed, position information of an image corresponding to a preset reference part in the face of the target user in the target image is determined, and then in the case that it is determined that a shooting position where the movable camera is currently located does not match a position corresponding to the reference part of the target user based on the position information, a shooting position of the movable camera is adjusted based on the position information so that the shooting position of the movable camera matches the position corresponding to the reference part of the target user. Therefore, even if the position of the target user is changed in the process of adjusting the shooting position of the movable camera, the position information of the image corresponding to the preset reference position in the face of the target user in the target image can be detected in time, and the shooting position of the movable camera can be adjusted in time.

The embodiment of the specification provides a facial image acquisition method, which includes acquiring a target image including a facial image of a target user acquired by a movable camera, analyzing the facial image of the target user in the target image, determining position information of an image corresponding to a preset reference part in the face of the target user in the target image, and adjusting a shooting position of the movable camera based on the position information so that the shooting position of the movable camera matches a position corresponding to the reference part of the target user when it is determined that the current shooting position of the movable camera does not match the position corresponding to the reference part of the target user based on the position information. Therefore, the problem that the facial images of the target users collected by the target users with different heights are inaccurate due to the fact that the shooting position of the camera is fixed can be avoided, and the problem that the facial image collection accuracy is poor can be solved.

Example two

As shown in fig. 4, an implementation subject of the present specification may be an electronic device capable of providing a service such as face-brushing payment for a user, where the electronic device may be configured with a movable camera, and the electronic device may be, for example, a face-brushing payment device, an unmanned vending device, or the like. The method may specifically comprise the steps of:

in S402, a target image including a face image of a target user captured by a movable camera is acquired.

In S404, the face image of the target user in the target image is analyzed, and the position information of the image corresponding to the reference portion preset in the face of the target user in the target image is determined.

The specific processing procedures of S402 to S404 can refer to the related contents of S102 to S104 in the first embodiment, and are not described herein again.

In S406, it is determined whether an image corresponding to a reference portion preset in the target user face is within a preset center range of the target image based on the position information.

The preset central range may be a preset range region of any shape and size, for example, the preset central range may be a range region corresponding to a circle with a central point of the target image as a dot and a preset distance as a radius.

In S408, in a case where the image corresponding to the reference portion preset in the face of the target user is not within the preset central range of the target image, the relative position information between the image corresponding to the reference portion preset in the face of the target user and the preset central range in the target image is acquired.

In implementation, as shown in fig. 5 as an example, the target image may be divided into 9 regions, where the region 5 may be a preset central range, and if the image corresponding to the preset reference location in the target user face is not in the region 5, the relative position information between the image corresponding to the preset reference location in the target user face and the preset central range in the target image may be obtained. For example, if an image corresponding to a reference part preset in the target user plane is in the region 3 in the target image, the relative position information may be relative position information between a center point of the region 5 and a center point of the region 3.

In S410, based on the relative position information, the shooting position of the movable camera is adjusted so that the shooting position of the movable camera matches a position corresponding to the reference part of the target user.

For the specific processing procedure of S410, reference may be made to relevant contents of S106 in the first embodiment, which is not described herein again.

In addition, in an actual application scenario, S410 may also have various implementations, for example, the first moving direction and the first moving distance may be determined based on the relative position information.

In implementation, assuming that the target image includes 9 regions as shown in fig. 5, if the image corresponding to the reference location preset in the target user's face is in region 2 in the target image and the preset central range is the range in which region 5 is located, it may be determined that the first moving direction is downward and the first moving distance is a straight-line distance between the center points of region 3 and region 5.

Alternatively, as shown in fig. 5, the reference location of the target user is located at a point a, the point a is located in the area 4, and is not on the same horizontal line as the center point B of the area 5, the first moving direction may include a first sub moving direction and a second sub moving direction, the first sub moving direction (i.e., downward) for adjusting the photographing position of the movable camera to be on the same horizontal line as the center point B of the area 5 may be determined based on the relative position information between the point a and the center point B of the area 5, then the second sub moving direction (i.e., rightward) for adjusting the photographing position of the movable camera to be on the center point B of the area 5 may be determined, and at the same time, the first sub moving distance and the second sub moving distance may be respectively determined based on the relative position information.

And controlling the movable camera to move along the preset track based on the first moving direction and the first moving distance.

In addition, in a case where the movable camera in the electronic apparatus is a rotatable camera, or a lens in the movable camera may be rotated within the movable camera, if an image corresponding to a reference portion preset in the target user face is located in a horizontal direction of a preset center range, the first rotation direction and the first rotation angle are determined based on the relative position information.

In implementation, as shown in fig. 5, if the image corresponding to the reference portion of the target user is located in the area 4 or the area 6, the first rotation direction and the first rotation angle may be determined based on the relative position information.

The movable camera or a lens of the movable camera is rotated based on the first rotation direction and the first rotation angle.

In addition, in a case where the movable camera in the electronic apparatus is a rotatable camera, or a lens in the movable camera may be rotated within the movable camera, if an image corresponding to a reference portion preset in the target user face is located in a direction other than the horizontal direction of the preset center range, the second moving direction, the second moving distance, the second rotating direction, and the second rotating angle are determined based on the relative position information.

In an implementation, for example, as shown in fig. 5, the reference location of the target user is located at a point C, the point C is located in the area 3, the second moving direction may be downward, the second moving distance may be a straight distance between a center point of the area 3 and a center point of the area 6, the second rotating direction may be leftward, and the second rotating angle may be determined by a distance between a center point of the area 4 and a center point of the area 5.

And controlling the movable camera to move to the horizontal direction of the preset central range along the track based on the second moving direction and the second moving distance.

And rotating the movable camera or the lens of the movable camera based on the second rotation direction and the second rotation angle.

Further, in a case where the lens within the movable camera in the electronic apparatus can be moved within the movable camera, the third moving direction and the third moving distance for moving the lens of the movable camera can be determined based on the relative position information. For determining the third moving direction and the third moving distance, reference may be made to the above determining methods of the first moving distance and the second moving distance, which are not described herein again.

And controlling the lens of the movable camera to move along a preset track in the movable camera based on the third moving direction and the third moving distance.

EXAMPLE III

An embodiment of the present specification provides a facial recognition apparatus, including a movable camera and a controller, wherein:

the movable camera may be located at a back side of the screen of the face recognition apparatus, and is configured to capture a target image including a face image of a target user through the screen of the face recognition apparatus.

The controller may be configured to acquire a target image including a face image of a target user acquired by the movable camera, analyze the face image of the target user in the target image, determine position information of an image corresponding to a preset reference portion in the face of the target user in the target image, and adjust the shooting position of the movable camera based on the position information so that the shooting position of the movable camera matches the position corresponding to the reference portion of the target user when it is determined that the current shooting position of the movable camera does not match the position corresponding to the reference portion of the target user based on the position information.

The face recognition device may be a face-brushing payment device that can be used independently for providing a face-brushing payment service for the user, or the face recognition device may be a device that is configured in an unmanned vending device for providing a face-brushing payment service for the user.

The embodiment of the specification provides a face recognition device, which is characterized in that a target image including a face image of a target user and acquired by a movable camera is acquired, the face image of the target user in the target image is analyzed, position information of an image corresponding to a preset reference part in the face of the target user in the target image is determined, and under the condition that the shooting position where the movable camera is located currently is determined to be not matched with the position corresponding to the reference part of the target user based on the position information, the shooting position of the movable camera is adjusted based on the position information, so that the shooting position of the movable camera is matched with the position corresponding to the reference part of the target user. Therefore, the problem that the facial images of the target users collected by the target users with different heights are inaccurate due to the fact that the shooting position of the camera is fixed can be avoided, and the problem that the facial image collection accuracy is poor can be solved.

Example four

The embodiment of the specification provides still another face recognition device. The face recognition device comprises all the functional units of the face recognition device of the third embodiment, and is improved on the basis of the functional units, and the improvement content is as follows:

a controller further configured to: and on the basis of the position information, determining whether an image corresponding to a preset reference part in the target user face is within a preset central range of the target image, acquiring relative position information between the image corresponding to the preset reference part in the target user face and the preset central range in the target image under the condition that the image corresponding to the preset reference part in the target user face is not within the preset central range of the target image, and adjusting the shooting position of the movable camera on the basis of the relative position information.

A controller further configured to: and determining a first moving direction and a first moving distance based on the relative position information, and controlling the movable camera to move along the preset track based on the first moving direction and the first moving distance.

A controller further configured to: and if the image corresponding to the reference position preset in the target user surface is positioned in the horizontal direction of the preset central range, determining a first rotating direction and a first rotating angle based on the relative position information, and rotating the movable camera or the lens of the movable camera based on the first rotating direction and the first rotating angle.

A controller further configured to: and if the image corresponding to the preset reference position in the target user surface is positioned in a direction other than the horizontal direction of the preset central range, determining a second moving direction, a second moving distance, a second rotating direction and a second rotating angle based on the relative position information, controlling the movable camera to move along the track to the horizontal direction of the preset central range based on the second moving direction and the second moving distance, and rotating the movable camera or the lens of the movable camera based on the second rotating direction and the second rotating angle.

A controller further configured to: and determining a third moving direction and a third moving distance for moving the lens of the movable camera based on the relative position information, and controlling the lens of the movable camera to move along a preset track in the movable camera based on the third moving direction and the third moving distance.

A controller further configured to: and determining a moving direction and a moving distance for moving the face recognition device based on the position information, and controlling the face recognition device to move along a preset track based on the moving direction and the moving distance.

The controller may control the face recognition device to move along a preset track according to the determined moving direction and moving distance, so that the photographing position of the movable camera is matched with a position corresponding to the reference position of the target user.

EXAMPLE five

Based on the same idea, the facial image capturing method provided in the embodiments of the present specification further provides a facial image capturing device, as shown in fig. 6.

The facial image acquisition device includes: an image acquisition module 601, a position acquisition module 602, and a position adjustment module 603, wherein:

the image acquisition module 601 is used for acquiring a target image which is acquired by the movable camera and comprises a facial image of a target user;

a position obtaining module 602, configured to analyze a face image of the target user in the target image, and determine position information of an image corresponding to a preset reference location in the face of the target user in the target image;

a position adjusting module 603, configured to, when it is determined based on the position information that the current shooting position of the movable camera does not match the position corresponding to the reference part of the target user, adjust the shooting position of the movable camera based on the position information so that the shooting position of the movable camera matches the position corresponding to the reference part of the target user.

In this embodiment of the present specification, the position adjusting module 603 is configured to:

determining whether an image corresponding to a preset reference position in the target user face is within a preset central range of the target image or not based on the position information;

under the condition that an image corresponding to a preset reference part in the target user face is not in a preset central range of the target image, acquiring relative position information between the image corresponding to the preset reference part in the target user face and the preset central range in the target image;

and adjusting the shooting position of the movable camera based on the relative position information.

determining a first moving direction and a first moving distance based on the relative position information;

and controlling the movable camera to move along a preset track based on the first moving direction and the first moving distance.

if the image corresponding to the preset reference position in the target user surface is located in the horizontal direction of the preset central range, determining a first rotation direction and a first rotation angle based on the relative position information;

rotating the movable camera or a lens of the movable camera based on the first rotation direction and the first rotation angle.

if the image corresponding to the preset reference position in the target user surface is located in a direction other than the horizontal direction of the preset central range, determining a second moving direction, a second moving distance, a second rotating direction and a second rotating angle based on the relative position information;

controlling the movable camera to move along the track to the horizontal direction of the preset central range based on the second moving direction and the second moving distance;

rotating the movable camera or a lens of the movable camera based on the second rotation direction and a second rotation angle.

determining a third moving direction and a third moving distance for moving a lens of the movable camera based on the relative position information;

The embodiment of the specification provides a facial image acquisition device, which acquires a target image including a facial image of a target user acquired by a movable camera, analyzes the facial image of the target user in the target image, determines position information of an image corresponding to a preset reference part in the face of the target user in the target image, and adjusts a shooting position of the movable camera based on the position information so that the shooting position of the movable camera matches with a position corresponding to the reference part of the target user when it is determined that the current shooting position of the movable camera does not match with the position corresponding to the reference part of the target user based on the position information. Therefore, the problem that the facial images of the target users collected by the target users with different heights are inaccurate due to the fact that the shooting position of the camera is fixed can be avoided, and the problem that the facial image collection accuracy is poor can be solved.

EXAMPLE six

Based on the same idea, the embodiments of the present specification further provide a facial image capturing device, as shown in fig. 7.

The facial image acquisition device may be the electronic device provided in the above embodiment.

The facial image capturing device may have a large difference due to different configurations or performances, and may include one or more processors 701 and a memory 702, where one or more stored applications or data may be stored in the memory 702. Memory 702 may be, among other things, transient storage or persistent storage. The application program stored in memory 702 may include one or more modules (not shown), each of which may include a series of computer-executable instructions in an acquisition device for facial images. Still further, the processor 701 may be configured to communicate with the memory 702 to execute a series of computer-executable instructions in the memory 702 on the facial image capture device. The facial image capture device may also include one or more power supplies 703, one or more wired or wireless network interfaces 704, one or more input-output interfaces 705, and one or more keyboards 706.

In particular, in this embodiment, the facial image capturing device includes a memory, and one or more programs, wherein the one or more programs are stored in the memory, and the one or more programs may include one or more modules, and each module may include a series of computer-executable instructions for the facial image capturing device, and the one or more programs configured to be executed by the one or more processors include computer-executable instructions for:

acquiring a target image including a facial image of a target user, which is acquired by a movable camera;

analyzing the face image of the target user in the target image, and determining the position information of an image corresponding to a preset reference part in the face of the target user in the target image;

and when the shooting position of the movable camera is determined to be not matched with the position corresponding to the reference part of the target user based on the position information, adjusting the shooting position of the movable camera based on the position information so as to enable the shooting position of the movable camera to be matched with the position corresponding to the reference part of the target user.

Optionally, in a case that it is determined based on the position information that the current shooting position of the movable camera does not match the position corresponding to the reference part of the target user, adjusting the shooting position of the movable camera based on the position information includes:

Optionally, the adjusting the shooting position of the movable camera based on the relative position information includes:

EXAMPLE seven

The embodiments of the present disclosure further provide a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the computer program implements each process of the above-mentioned facial image acquisition method embodiment, and can achieve the same technical effect, and in order to avoid repetition, the details are not repeated here. The computer-readable storage medium may be a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk.

The embodiment of the specification provides a computer-readable storage medium, which is used for acquiring a target image including a face image of a target user, wherein the target image is acquired by a movable camera, analyzing the face image of the target user in the target image, determining position information of an image corresponding to a preset reference part in the face of the target user in the target image, and adjusting a shooting position of the movable camera based on the position information so that the shooting position of the movable camera is matched with a position corresponding to the reference part of the target user when it is determined that the current shooting position of the movable camera is not matched with the position corresponding to the reference part of the target user based on the position information. Therefore, the problem that the facial images of the target users collected by the target users with different heights are inaccurate due to the fact that the shooting position of the camera is fixed can be avoided, and the problem that the facial image collection accuracy is poor can be solved.

The foregoing description has been directed to specific embodiments of this disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.

In the 90 s of the 20 th century, improvements in a technology could clearly distinguish between improvements in hardware (e.g., improvements in circuit structures such as diodes, transistors, switches, etc.) and improvements in software (improvements in process flow). However, as technology advances, many of today's process flow improvements have been seen as direct improvements in hardware circuit architecture. Designers almost always obtain the corresponding hardware circuit structure by programming an improved method flow into the hardware circuit. Thus, it cannot be said that an improvement in the process flow cannot be realized by hardware physical modules. For example, a Programmable Logic Device (PLD), such as a Field Programmable Gate Array (FPGA), is an integrated circuit whose Logic functions are determined by programming the Device by a user. A digital system is "integrated" on a PLD by the designer's own programming without requiring the chip manufacturer to design and fabricate application-specific integrated circuit chips. Furthermore, nowadays, instead of manually making an integrated Circuit chip, such Programming is often implemented by "logic compiler" software, which is similar to a software compiler used in program development and writing, but the original code before compiling is also written by a specific Programming Language, which is called Hardware Description Language (HDL), and HDL is not only one but many, such as abel (advanced Boolean Expression Language), ahdl (alternate Language Description Language), traffic, pl (core unified Programming Language), HDCal, JHDL (Java Hardware Description Language), langue, Lola, HDL, laspam, hardsradware (Hardware Description Language), vhjhd (Hardware Description Language), and vhigh-Language, which are currently used in most common. It will also be apparent to those skilled in the art that hardware circuitry that implements the logical method flows can be readily obtained by merely slightly programming the method flows into an integrated circuit using the hardware description languages described above.

The controller may be implemented in any suitable manner, for example, the controller may take the form of, for example, a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro) processor, logic gates, switches, an Application Specific Integrated Circuit (ASIC), a programmable logic controller, and an embedded microcontroller, examples of which include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320, the memory controller may also be implemented as part of the control logic for the memory. Those skilled in the art will also appreciate that, in addition to implementing the controller as pure computer readable program code, the same functionality can be implemented by logically programming method steps such that the controller is in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like. Such a controller may thus be considered a hardware component, and the means included therein for performing the various functions may also be considered as a structure within the hardware component. Or even means for performing the functions may be regarded as being both a software module for performing the method and a structure within a hardware component.

The systems, devices, modules or units illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product with certain functions. One typical implementation device is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a cellular telephone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

For convenience of description, the above devices are described as being divided into various units by function, and are described separately. Of course, the functionality of the various elements may be implemented in the same one or more software and/or hardware implementations in implementing one or more embodiments of the present description.

As will be appreciated by one skilled in the art, embodiments of the present description may be provided as a method, system, or computer program product. Accordingly, one or more embodiments of the present description may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, one or more embodiments of the present description may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

Embodiments of the present description are described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the description. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.

The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.

Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.

It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.

One or more embodiments of the present description may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. One or more embodiments of the specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.

The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.

The above description is only an example of the present specification, and is not intended to limit the present specification. Various modifications and alterations to this description will become apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present specification should be included in the scope of the claims of the present specification.

Claims

1. A method of acquiring a facial image, the method comprising:

2. The method according to claim 1, wherein in a case where it is determined based on the position information that the shooting position at which the movable camera is currently located does not match the position corresponding to the reference part of the target user, adjusting the shooting position of the movable camera based on the position information comprises:

3. The method of claim 2, the adjusting the shooting position of the movable camera based on the relative position information, comprising:

4. The method of claim 2, the adjusting the shooting position of the movable camera based on the relative position information, comprising:

5. The method of claim 3, the adjusting the shooting position of the movable camera based on the relative position information, comprising:

6. The method of claim 2, the adjusting the shooting position of the movable camera based on the relative position information, comprising:

7. A facial recognition apparatus comprising a movable camera and a controller, wherein:

the movable camera is positioned on the back of the screen of the face recognition equipment and is used for acquiring a target image including a face image of a target user through the screen of the face recognition equipment;

the controller is used for acquiring a target image which is acquired by the movable camera and comprises a facial image of the target user; analyzing the face image of the target user in the target image, and determining the position information of an image corresponding to a preset reference part in the face of the target user in the target image; and when the shooting position of the movable camera is determined to be not matched with the position corresponding to the reference part of the target user based on the position information, adjusting the shooting position of the movable camera based on the position information so as to enable the shooting position of the movable camera to be matched with the position corresponding to the reference part of the target user.

8. The facial recognition device of claim 7, the controller further to:

determining a moving direction and a moving distance for moving the face recognition device based on the location information;

and controlling the face recognition equipment to move along a preset track based on the moving direction and the moving distance.

9. An apparatus for acquiring a facial image, the apparatus comprising:

the image acquisition module is used for acquiring a target image which is acquired by the movable camera and comprises a facial image of a target user;

the position acquisition module is used for analyzing the face image of the target user in the target image and determining the position information of an image corresponding to a preset reference part in the face of the target user in the target image;

and the position adjusting module is used for adjusting the shooting position of the movable camera based on the position information under the condition that the shooting position where the movable camera is located currently is determined to be not matched with the position corresponding to the reference part of the target user based on the position information, so that the shooting position of the movable camera is matched with the position corresponding to the reference part of the target user.

10. The apparatus of claim 9, the position adjustment module to:

11. The apparatus of claim 10, the position adjustment module to:

12. The apparatus of claim 10, the position adjustment module to:

13. The apparatus of claim 11, the position adjustment module to:

14. The apparatus of claim 10, the position adjustment module to:

15. An acquisition apparatus of a face image, comprising:

a processor; and

a memory arranged to store computer executable instructions that, when executed, cause the processor to: