CN108875556B - Method, apparatus, system and computer storage medium for testimony of a witness verification - Google Patents
Method, apparatus, system and computer storage medium for testimony of a witness verification Download PDFInfo
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- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
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Abstract
The invention provides a method, a device and a system for people authentication verification and a computer storage medium. The method comprises the following steps: acquiring a face image to be verified; carrying out mirror symmetry processing on the face image to obtain a mirror symmetry image of the face image; judging the quality of the face image, and marking the face image according to the quality judgment result; and superposing the marked information on the mirror symmetry image and displaying. Therefore, in the embodiment of the invention, mirror symmetry processing and quality judgment can be executed in parallel, processing time is shortened, a face image can be presented in real time, a compared person can adjust the position, the posture and the like according to the presented face image conveniently, and user experience can be improved. And can be further used for follow-up testimony of a witness verification, improve the treatment effeciency.
Description
Technical Field
The present invention relates to the field of image processing, and more particularly, to a method, apparatus, system, and computer storage medium for human authentication.
Background
With the improvement of the accuracy of the face recognition algorithm and the maturity of terminal hardware and systems, the face recognition technology is widely applied to various industries. For example, in the security industry, a human identity card verification all-in-one machine is a ground embodiment of a face recognition technology. At present, the people's card checking all-in-one machine is used for checking whether a field face and a face on an identity card are the same person, and the use scene includes but is not limited to identity checking of a public institution, hotel check-in, internet bar check-in and the like.
However, in the current people verification system, although the front-end screen can display the on-site video information, the video delay is obvious, the user is not friendly, the image acquisition time is prolonged, and the efficiency is reduced.
Disclosure of Invention
The invention provides a method, a device and a system for people's identity verification and a computer storage medium, which can present a face image on a front-end screen in real time, facilitate the posture adjustment of a compared person, improve the user experience and simultaneously improve the processing efficiency.
According to an aspect of the present invention, there is provided a method for human authentication verification, the method comprising:
acquiring a face image to be verified;
carrying out mirror symmetry processing on the face image to obtain a mirror symmetry image of the face image;
judging the quality of the face image, and marking the face image according to the quality judgment result;
and superposing the marked information on the mirror symmetry image and displaying.
In an implementation manner of the present invention, the acquiring a face image to be verified includes:
acquiring video stream data acquired by an image acquisition device;
and determining the face image in the video stream data according to a face detection model.
In an implementation manner of the present invention, the mirror-symmetric processing on the face image to obtain a mirror-symmetric image of the face image includes:
and rotating the face image by 180 degrees by taking the face-out direction of the face image as a rotating shaft to obtain the mirror symmetry image.
In an implementation manner of the present invention, the determining the quality of the face image includes:
obtaining the numerical value of at least one of the following indications of the face based on the face image, and comparing the numerical value with a corresponding preset quality threshold value:
horizontal direction angle, vertical direction angle, rotation angle, blur degree, and brightness.
In an implementation manner of the present invention, the labeling the face image according to the result of the quality determination includes:
carrying out first marking on the face image reaching a preset quality threshold;
carrying out second marking on the face image which does not reach the preset quality threshold;
wherein the first flag is: marking a face frame of the face image as a first color;
the second label is: and marking a face frame of the face image as a second color, wherein the second color is different from the first color.
In one implementation of the present invention, the superimposing the information of the mark on the mirror-symmetric image includes:
and superposing the face frame with the first color or the second color to the mirror symmetry image.
In one implementation of the present invention, the superimposing and displaying the marked information on the mirror-symmetric image includes:
superposing the marked information on the mirror-symmetric image to obtain a marked image;
converting the marked image from an android-based coordinate system into an open graphics library OpenGL ES-based coordinate system through coordinate transformation;
and displaying the image after the coordinate conversion on an image display screen.
According to another aspect of the present invention there is provided an apparatus for human authentication verification for carrying out the steps of the method of the preceding aspect or embodiments, the apparatus comprising:
the acquisition module is used for acquiring a face image to be verified;
the mirror symmetry module is used for carrying out mirror symmetry processing on the face image to obtain a mirror symmetry image of the face image;
the quality judgment module is used for judging the quality of the face image and marking the face image according to the quality judgment result;
and the display module is used for superposing the marked information on the mirror symmetry image and displaying the information.
According to a further aspect of the present invention, there is provided a system for human authentication comprising a memory, a processor and a computer program stored on the memory and running on the processor, the processor implementing the steps of the method for human authentication as described in the preceding aspect and examples when executing the computer program.
According to a further aspect of the present invention, there is provided a computer storage medium having stored thereon a computer program which, when executed by a processor, carries out the steps of the method for testimony verification as set forth in the preceding aspects and examples.
Therefore, in the embodiment of the invention, mirror symmetry processing and quality judgment can be executed in parallel, processing time is shortened, a face image can be presented in real time, a compared person can adjust the position, the posture and the like according to the presented face image conveniently, and user experience can be improved. And can be further used for follow-up testimony of a witness verification, improve the treatment effeciency.
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The above and other objects, features and advantages of the present invention will become more apparent by describing in more detail embodiments of the present invention with reference to the attached drawings. The accompanying drawings are included to provide a further understanding of the embodiments of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings, like reference numbers generally represent like parts or steps.
FIG. 1 is a schematic block diagram of an electronic device of an embodiment of the present invention;
FIG. 2 is a schematic flow chart of a method for human verification of an embodiment of the present invention;
FIG. 3 is another schematic flow chart diagram of a method for human verification of an embodiment of the present invention;
FIG. 4 is a schematic block diagram of an apparatus for human authentication verification in accordance with an embodiment of the present invention;
FIG. 5 is a schematic block diagram of a system for human verification of an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, exemplary embodiments according to the present invention will be described in detail below with reference to the accompanying drawings. It is to be understood that the described embodiments are merely a subset of embodiments of the invention and not all embodiments of the invention, with the understanding that the invention is not limited to the example embodiments described herein. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the invention described herein without inventive step, shall fall within the scope of protection of the invention.
The embodiment of the present invention can be applied to an electronic device, and fig. 1 is a schematic block diagram of the electronic device according to the embodiment of the present invention. The electronic device 10 shown in FIG. 1 includes one or more processors 102, one or more memory devices 104, an input device 106, an output device 108, an image sensor 110, and one or more non-image sensors 114, which are interconnected via a bus system 112 and/or otherwise. It should be noted that the components and configuration of the electronic device 10 shown in FIG. 1 are exemplary only, and not limiting, and that the electronic device may have other components and configurations as desired.
The processor 102 may include a Central Processing Unit (CPU) 1021 and a Graphics Processing Unit (GPU) 1022 or other forms of Processing units having data Processing capability and/or Instruction execution capability, such as a Field-Programmable Gate Array (FPGA) or an Advanced Reduced Instruction Set Machine (Reduced Instruction Set Computer) Machine (ARM), and the like, and the processor 102 may control other components in the electronic device 10 to perform desired functions.
The storage 104 may include one or more computer program products that may include various forms of computer-readable storage media, such as volatile memory 1041 and/or non-volatile memory 1042. The volatile Memory 1041 may include, for example, a Random Access Memory (RAM), a cache Memory (cache), and/or the like. The non-volatile Memory 1042 may include, for example, a Read-Only Memory (ROM), a hard disk, a flash Memory, and the like. One or more computer program instructions may be stored on the computer-readable storage medium and executed by processor 102 to implement various desired functions. Various applications and various data, such as various data used and/or generated by the applications, may also be stored in the computer-readable storage medium.
The input device 106 may be a device used by a user to input instructions and may include one or more of a keyboard, a mouse, a microphone, a touch screen, and the like.
The output device 108 may output various information (e.g., images or sounds) to an external (e.g., user), and may include one or more of a display, a speaker, and the like.
The image sensor 110 may take images (e.g., photographs, videos, etc.) desired by the user and store the taken images in the storage device 104 for use by other components.
It should be noted that the components and structure of the electronic device 10 shown in fig. 1 are merely exemplary, and although the electronic device 10 shown in fig. 1 includes a plurality of different devices, some of the devices may not be necessary, some of the devices may be more numerous, and the like, as desired, and the invention is not limited thereto.
FIG. 2 is a schematic flow chart of a method for human verification of an embodiment of the present invention. The method illustrated in FIG. 2 may be performed by the electronic device 10 illustrated in FIG. 1, and in particular by the processor 102. The method shown in fig. 2 may include:
s110, obtaining a face image to be verified;
s120, mirror symmetry processing is carried out on the face image to obtain a mirror symmetry image of the face image;
s130, judging the quality of the face image, and marking the face image according to the quality judgment result;
and S140, superposing the marked information on the mirror symmetry image and displaying.
The execution device of the method can be a human authentication verification device. Illustratively, the human authentication apparatus may include an image capture device and a display screen, which may be a front-end screen. In S110, a face image to be verified acquired by the image acquisition device may be acquired; in S140, the display may be performed on the front screen.
It is understood that the image capture device may be a camera device, such as a camera, which may be one of the image sensors 110 shown in fig. 1. It will be appreciated that a mirror-symmetric image of the superimposed marker information may be displayed on the front-end screen, which may be one of the output devices 108 shown in fig. 1. Wherein, the front screen is a display facing the compared person.
Exemplarily, in S110, the method may include: acquiring video stream data acquired by the image acquisition device; and determining the face image in the video stream data according to a face detection model.
Referring to fig. 3, video stream data acquired by an image acquisition apparatus may be acquired. And then judging whether a human face exists in each frame of the video stream data through a human face detection model. Illustratively, the presence or absence of a face may be detected on a frame-by-frame basis. As an implementation manner, if it is determined through the face detection that no face exists in any frame, the video stream data acquired by the image acquisition device may be returned to be re-acquired, and the face detection may be performed on the re-acquired video stream data. As another implementation, if it is determined through face detection that a face exists in a certain frame, it may be determined that the frame of video stream data is a face image in S110. It is understood that 1 or more faces may exist in the face image in S110, which is not limited in the present invention.
Exemplarily, S120 may include: and rotating the face image by 180 degrees by taking the face-out direction of the face image as a rotating shaft to obtain the mirror symmetry image.
When the image acquisition device acquires a face image, the principle of image imaging is similar to that of convex lens imaging, and the obtained image is inverted compared with the actual image. Taking a face image as an example, the imaged eyes would be located below, while the mouth and nose would be located above. If the inverted images after imaging are displayed among each other, the visual experience is very bad due to the fact that the inverted images are not consistent with the observation visual angles of ordinary people. In the embodiment of the present invention, an erected image can be obtained by mirror symmetry processing.
Specifically, the mirror symmetry processing may be to rotate the face image by 180 degrees around its out-of-plane direction. Specifically, assuming that the face-out direction of the face image is the z-axis (or-z-axis) direction, the mirror-symmetric image can be obtained by rotating the face image around the rotation axis by 180 degrees with the z-axis (or-z-axis) as the rotation axis.
Illustratively, as shown in fig. 3, S120 may include: the mirror symmetric image is obtained by the following matrix transformation:
as a simplified form, the matrix transformation can also be expressed as:
wherein (x ', y ', z ') represents coordinate values in the mirror-symmetric image, and (x, y, z) represents coordinate values in the face image. θ denotes a rotation angle of the matrix transformation, and in this example, θ is 180.
Illustratively, S130 may include: and judging whether the face in the face image of the S110 meets the required face quality requirement or not. It can be understood that if more than one face exists in the face image of S110, the face closest to the image acquisition device may be used as the face image of the compared person, or the face with the largest area may be used as the face image of the compared person according to the size of the detected face.
Specifically, the method may include: and if the judgment result determines that the face image reaches the preset quality threshold, performing first marking on the face image. And if the judgment result determines that the face image does not reach the preset quality threshold value, performing second marking on the face image.
For example, when performing the quality determination, the image quality of the face, such as horizontal direction angle, vertical direction angle, rotation angle, blur degree, brightness, etc., may be determined based on the face image, and the obtained various image qualities may be compared with corresponding preset quality thresholds. If the quality of each image meets the corresponding preset quality threshold, the face image can be determined to reach the preset quality threshold. Otherwise, if the quality of a certain image does not meet the corresponding preset quality threshold, the face image can be determined not to meet the preset quality threshold. For example, if the rotation angle of the face image is greater than the preset rotation angle threshold, it is determined that the face image is not a front face and does not meet the quality requirement. For another example, if the face image is too blurred and cannot meet the definition quality threshold, it indicates that the face image is not clear enough and cannot meet the quality requirement.
That is, when the quality of the face image reaches the quality threshold, it is first labeled. And when the quality of the face image does not reach the quality threshold value, carrying out second marking on the face image. Alternatively, the first mark may be: and marking a face frame of the face image as a first color. The second mark may be: and marking a face frame of the face image as a second color, wherein the second color is different from the first color. For example, the first color is blue and the second color is red. The invention is not limited in this regard.
After the face is detected by the face detection model, a face frame can be adopted to mark out the detected face area; then, quality judgment is carried out, and if the preset quality threshold is reached, the face frame is in a first color; and if the preset quality threshold value is not reached, the face frame is in a second color.
In the embodiment of the present invention, S120 and S130 may be executed in parallel, which may shorten the processing time, so that S140 may be executed faster, i.e., may be displayed in real time in S140 for being viewed by the comparator in time.
For example, the face frame marked in S130 may be superimposed on the mirror-symmetric image in S120 in S140. For example, in S140, a face frame having a first color or a second color may be superimposed on the mirror-symmetric image.
When the face image collected by the image collecting device is subjected to face detection, the used coordinate system is an Android (Android) -based coordinate system. That is, the coordinate values of the face frame are labeled using the coordinate system of the Android system. When displaying an image on a display screen, the coordinate system used is an Open Graphics Library (OpenGL) ES-based coordinate system.
Therefore, in order to correctly display an image on a display screen, a coordinate transformation operation needs to be performed. I.e. from the android-based coordinate system into the OpenGL ES-based coordinate system by coordinate transformation.
Open Graphics Library (Open Graphics Library) refers to a specialized Graphics program interface that defines a cross-programming language, cross-platform programming interface specification. The method is used for three-dimensional images (two-dimensional images can also be used), and is a bottom layer graphic library which is powerful and convenient to call. OpenGL ES (OpenGL for Embedded Systems) is a subset of OpenGL three-dimensional graphics APIs.
Exemplarily, S140 may include: superposing the marked information on the mirror-symmetric image to obtain a marked image; converting the marked image from an android-based coordinate system into an open graphics library OpenGL ES-based coordinate system through coordinate transformation; and displaying the image after the coordinate conversion on an image display screen.
The marked information can be a face frame, and the marked image is an image with the face frame. The coordinate transformation process is illustrated: generally, the coordinate system of the Android system uses a point at the upper left corner as an origin, the x-axis direction is horizontal to the right, the y-axis direction is vertical to the bottom, and the values of x and y are the actual pixel size. The origin of the OpenGL ES coordinate system is at the center position, and the value range of the x axis and the y axis is [ -1,1 ]. The coordinate conversion may be performed using a process shown in the following code, where rectF denotes a rectangular position, representing the position of the face frame before conversion, width denotes the width of the image before conversion, height denotes the height of the image before conversion, and squarecords [ ] is the position of the face frame in the OpenGL ES coordinate system.
Thus, a mirror-symmetric face image with a marked face frame is displayed in S140. Since the front screen is oriented toward the compared person, the compared person can view the display in real time. As an example, if the face frame in the displayed mirror-symmetric face image is in the first color, which indicates that it meets the quality requirement, the subsequent verification process of the witness can be further performed based on the mirror-symmetric face image. As another example, if the face frame in the displayed mirror-symmetric face image is in the second color, which indicates that it does not satisfy the quality requirement, the compared person may adjust the position, the posture, and the like of the compared person relative to the image capturing device. And the image acquisition device can acquire the video stream data again and can execute the process again based on the acquired video stream data.
Therefore, in the embodiment of the invention, mirror symmetry processing and quality judgment can be executed in parallel, and processing time is shortened, so that the face image can be presented on a front-end screen in real time, a compared person can conveniently adjust the position, the posture and the like according to the presented face image, and user experience can be improved. And can be further used for follow-up testimony of a witness verification, improve the treatment effeciency.
For example, if the mirror-symmetric face image with the first mark is displayed in S140, the further human verification process may include: and acquiring an identity image in the certificate to be verified, and judging whether the face image acquired by the image acquisition device and the identity image belong to the same person.
The acquiring of the identity image in the document to be verified may include: the identity image is obtained by an electronic reading mode.
The document to be verified may include an integrated circuit therein such that the personal verification system can read electronic information recorded therein from the integrated circuit, where the electronic information includes the identification image. For example, the integrated circuit may also be referred to as a chip or a microcircuit, which may be composed of a wafer, but the invention is not limited thereto. For example, the document to be verified may be an identity card, a social security card, or the like.
If the electronic reading is successful, the identity image may be acquired. In addition, it can be understood that other identity information of the certificate, such as name, address, etc., can be acquired through electronic reading. For example, assuming the document is an identification card, the acquired identification information may include name, nationality, address, identification number, expiration date, issuing authority, etc. Assuming that the document is a passport, the identity information acquired may include a name, address, passport number, expiration date, issuing location, etc.
If the electronic reading fails, the identity image can be further acquired by an Optical Character Recognition (OCR) method. The identity image may be resolved, for example, by scanning or taking a picture of the document, and then performing OCR on the image of the document. In addition, it can be understood that other identity information of the certificate, such as a name, an address and the like, can be acquired by the OCR mode while the identity image is acquired by the OCR mode. For example, assuming that the document is an identity card without magnetism, such as a business card, the acquired identity information may include a name, a name of a work unit, an address, a phone number, and the like.
Wherein, OCR can determine its shape by detecting dark, bright mode, then translate the shape into the computer word with the character recognition method; that is, the characters in the paper document can be optically converted into an image file with a black-and-white dot matrix, and the characters in the image are converted into a text format by recognition software for further editing and processing by the character processing software.
Therefore, the identity image can be obtained through the electronic reading mode at first, and the identity image is obtained through the OCR mode when the electronic reading mode fails, so that the validity of obtaining the identity image can be ensured, the comparison failure caused by single mode is avoided, and the processing efficiency is ensured.
Further, whether the acquired face image and the identity image belong to the same person or not can be judged through face recognition. Alternatively, it may be determined whether the mirror-symmetric face image with the first mark and the identity image in S140 belong to the same person through face recognition.
The face recognition algorithm used may be a pre-trained convolutional neural network, and the network structure of the neural network used in the embodiment of the present invention is not limited, and may be any one of ResNet, densnet, MobileNet, ShuffleNet, inclusion, and the like.
Specifically, a first feature vector of the face image can be extracted through a feature extraction network, and a second feature vector of the identity image can be extracted. And calculating the similarity between the first feature vector and the second feature vector, and determining whether the first feature vector and the second feature vector belong to the same person or not according to the similarity.
For example, the feature extraction network may be a convolutional neural network that is currently available for feature extraction, and is not described here in detail.
Illustratively, the distance between the first feature vector and the second feature vector may be calculated to calculate the similarity. For example, the distance may be any one of an euclidean distance, a cosine distance, a mahalanobis distance, and the like, or may be another distance, which is not limited in the present invention. After calculating the distance, the similarity may be calculated from the distance. As an example, the calculated distance may be directly used as the similarity. As another example, the similarity may be obtained by recalculation after obtaining the distance. The calculated similarity may be a value between 0 and 1.
If the obtained similarity is larger than or equal to the similarity threshold, the face image of the compared person and the identity image in the certificate can be determined to belong to the same person, otherwise, the face image and the identity image do not belong to the same person. The similarity threshold may be set according to actual conditions in practical applications, which is not limited in the present invention.
In addition, in the verification method of the embodiment of the invention, off-line comparison can be carried out, so that the time consumption of a network does not need to be considered, and the processing efficiency is further improved.
Thus, the human verification process of the embodiment of the invention can be completed. Optionally, if it is determined that the face image of the compared person and the identity image in the certificate belong to the same person, the method may further include: the identity information (information such as name) acquired from the certificate is associated with the face image of the compared person. For example, if the compared person is a visitor (such as a hotel guest), the face image and the corresponding identity information of the compared person can be registered when the visitor registers, so that manual input can be reduced, time consumption can be reduced, and efficiency can be improved.
It should be understood that the alignment process shown here is only one embodiment of the present invention, and other embodiments may be used to perform the alignment process, such as obtaining identity images only by electronic scanning without using OCR method. The invention is not limited in this regard.
FIG. 4 is a schematic block diagram of an apparatus for human authentication verification in accordance with an embodiment of the present invention. The apparatus 40 shown in fig. 4 may include an acquisition module 410, a mirror symmetry module 420, a quality determination module 430, and a display module 440.
An obtaining module 410, configured to obtain a face image to be verified;
a mirror symmetry module 420, configured to perform mirror symmetry processing on the face image to obtain a mirror-symmetric image of the face image;
the quality judgment module 430 is used for judging the quality of the face image and marking the face image according to the quality judgment result;
and a display module 440, configured to superimpose and display the marked information on the mirror-symmetric image.
Illustratively, the obtaining module 410 may be specifically configured to: acquiring video stream data acquired by an image acquisition device; and determining the face image in the video stream data according to a face detection model.
Illustratively, the mirror symmetry module 420 may be specifically configured to: and rotating the face image by 180 degrees by taking the face-out direction of the face image as a rotating shaft to obtain the mirror symmetry image.
Illustratively, the quality determination module 430 may be specifically configured to: obtaining the numerical value of at least one of the following indications of the face based on the face image, and comparing the numerical value with a corresponding preset quality threshold value: horizontal direction angle, vertical direction angle, rotation angle, blur degree, and brightness.
Illustratively, the quality determination module 430 may be specifically configured to: judging the quality of the face image, and performing first marking on the face image reaching a preset quality threshold; and carrying out second marking on the face image which does not reach the preset quality threshold. Wherein the first flag is: and marking a face frame of the face image as a first color. The second label is: and marking a face frame of the face image as a second color, wherein the second color is different from the first color.
Illustratively, the display module 440 may be specifically configured to superimpose a face frame having a first color or a second color onto the mirror-symmetric image.
Illustratively, the display module 440 may be specifically configured to:
superposing the marked information on the mirror-symmetric image to obtain a marked image;
converting the marked image from an android-based coordinate system into an open graphics library OpenGL ES-based coordinate system through coordinate transformation;
and displaying the image after the coordinate conversion on an image display screen.
The apparatus 40 shown in fig. 4 can implement the method for human verification shown in fig. 2 or fig. 3, and is not described herein again to avoid repetition.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In addition, another system for human authentication verification according to an embodiment of the present invention includes a memory, a processor, and a computer program stored in the memory and running on the processor, where the processor implements the steps of the method for human authentication verification shown in fig. 2 or fig. 3 when executing the computer program.
As shown in fig. 5, the system 50 may include a memory 510 and a processor 520, and may further include an image capture device 530 and a front-end screen 540.
The memory 510 stores computer program code for implementing the respective steps in the method for human authentication according to an embodiment of the present invention.
The processor 520 is configured to run the computer program code stored in the memory 510 to perform the respective steps of the method for human authentication according to an embodiment of the present invention, and to implement the acquisition module 410, the mirror symmetry module 420, the quality judgment module 430 and the display module 440 in the apparatus 40 for human authentication according to an embodiment of the present invention.
Illustratively, the computer program code when executed by the processor 520 performs the steps of: acquiring a face image to be verified; carrying out mirror symmetry processing on the face image to obtain a mirror symmetry image; judging the quality of the face image, and marking the face image according to the quality judgment result; and superposing the marked information on the mirror symmetry image and displaying.
In addition, an embodiment of the present invention further provides an electronic device, which may include the apparatus 40 shown in fig. 4. The electronic device may implement the method for human authentication as described above with reference to fig. 2 or 3.
In addition, the embodiment of the invention also provides a computer storage medium, and the computer storage medium is stored with the computer program. The computer program, when executed by a processor, may implement the steps of the method for human authentication as described in the foregoing fig. 2 or fig. 3. For example, the computer storage medium is a computer-readable storage medium.
The computer storage medium may include, for example, a memory card of a smart phone, a storage component of a tablet computer, a hard disk of a personal computer, a Read Only Memory (ROM), an Erasable Programmable Read Only Memory (EPROM), a portable compact disc read only memory (CD-ROM), a USB memory, or any combination of the above storage media. The computer readable storage medium can be any combination of one or more computer readable storage media, e.g., one containing computer readable program code for randomly generating sequences of action instructions and another containing computer readable program code for performing facial activity recognition.
Therefore, in the embodiment of the invention, mirror symmetry processing and quality judgment can be executed in parallel, processing time is shortened, a face image can be presented in real time, a compared person can adjust the position, the posture and the like according to the presented face image conveniently, and user experience can be improved. And can be further used for follow-up testimony of a witness verification, improve the treatment effeciency.
Although the illustrative embodiments have been described herein with reference to the accompanying drawings, it is to be understood that the foregoing illustrative embodiments are merely exemplary and are not intended to limit the scope of the invention thereto. Various changes and modifications may be effected therein by one of ordinary skill in the pertinent art without departing from the scope or spirit of the present invention. All such changes and modifications are intended to be included within the scope of the present invention as set forth in the appended claims.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described device embodiments are merely illustrative, and for example, the division of the units is only one logical functional division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another device, or some features may be omitted, or not executed.
In the description provided herein, numerous specific details are set forth. It is understood, however, that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.
Similarly, it should be appreciated that in the description of exemplary embodiments of the invention, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the invention and aiding in the understanding of one or more of the various inventive aspects. However, the method of the present invention should not be construed to reflect the intent: that the invention as claimed requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this invention.
It will be understood by those skilled in the art that all of the features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or elements of any method or apparatus so disclosed, may be combined in any combination, except combinations where such features are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.
Furthermore, those skilled in the art will appreciate that while some embodiments described herein include some features included in other embodiments, rather than other features, combinations of features of different embodiments are meant to be within the scope of the invention and form different embodiments. For example, in the claims, any of the claimed embodiments may be used in any combination.
The various component embodiments of the invention may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. Those skilled in the art will appreciate that a microprocessor or Digital Signal Processor (DSP) may be used in practice to implement some or all of the functionality of some of the modules in an item analysis apparatus according to embodiments of the present invention. The present invention may also be embodied as apparatus programs (e.g., computer programs and computer program products) for performing a portion or all of the methods described herein. Such programs implementing the present invention may be stored on computer-readable media or may be in the form of one or more signals. Such a signal may be downloaded from an internet website or provided on a carrier signal or in any other form.
It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The usage of the words first, second and third, etcetera do not indicate any ordering. These words may be interpreted as names.
The above description is only for the specific embodiment of the present invention or the description thereof, and the protection scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and the changes or substitutions should be covered within the protection scope of the present invention. The protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (9)
1. A method for human verification, the method comprising:
acquiring a face image to be verified;
carrying out mirror symmetry processing on the face image to obtain a mirror symmetry image of the face image;
judging the quality of the face image, and marking the face image according to the quality judgment result;
superposing the marked information on the mirror-symmetric image and displaying the information so that a compared person can check the mirror-symmetric image superposed with the marked information in time to adjust the position or the posture;
the marking the face image according to the quality judgment result comprises the following steps: carrying out first marking on the face image reaching a preset quality threshold; carrying out second marking on the face image which does not reach the preset quality threshold; wherein the first flag is: marking a face frame of the face image as a first color; the second label is: marking a face frame of the face image as a second color, wherein the second color is different from the first color;
the superimposing of the marked information on the mirror-symmetric image comprises: and superposing the face frame with the first color or the second color to the mirror symmetry image.
2. The method according to claim 1, wherein the mirror symmetry processing and the quality determination are performed in parallel.
3. The method according to claim 1, wherein the obtaining of the face image to be verified comprises:
acquiring video stream data acquired by an image acquisition device;
and determining the face image in the video stream data according to a face detection model.
4. The method according to claim 1, wherein the mirror-symmetric processing on the face image to obtain a mirror-symmetric image of the face image comprises:
and rotating the face image by 180 degrees by taking the face-out direction of the face image as a rotating shaft to obtain the mirror symmetry image.
5. The method of claim 1, wherein the determining the quality of the face image comprises:
obtaining the numerical value of at least one of the following indications of the face based on the face image, and comparing the numerical value with a corresponding preset quality threshold value:
horizontal direction angle, vertical direction angle, rotation angle, blur degree, and brightness.
6. The method according to any one of claims 1 to 5, wherein the superimposing and displaying the marked information on the mirror-symmetric image comprises:
superposing the marked information on the mirror-symmetric image to obtain a marked image;
converting the marked image from an android-based coordinate system into an open graphics library OpenGL ES-based coordinate system through coordinate transformation;
and displaying the image after the coordinate conversion on an image display screen.
7. An apparatus for human authentication, the apparatus comprising:
the acquisition module is used for acquiring a face image to be verified;
the mirror symmetry module is used for carrying out mirror symmetry processing on the face image to obtain a mirror symmetry image of the face image;
the quality judgment module is used for judging the quality of the face image and marking the face image according to the quality judgment result;
the display module is used for superposing the marked information on the mirror-symmetrical image and displaying the information so that a compared person can check the mirror-symmetrical image superposed with the marked information in time to adjust the position or the posture;
the marking the face image according to the quality judgment result comprises the following steps: carrying out first marking on the face image reaching a preset quality threshold; carrying out second marking on the face image which does not reach the preset quality threshold; wherein the first flag is: marking a face frame of the face image as a first color; the second label is: marking a face frame of the face image as a second color, wherein the second color is different from the first color;
the superimposing of the marked information on the mirror-symmetric image comprises: and superposing the face frame with the first color or the second color to the mirror symmetry image.
8. A system for human authentication comprising a memory, a processor and a computer program stored on the memory and running on the processor, characterized in that the processor implements the steps of the method of any one of claims 1 to 6 when executing the computer program.
9. A computer storage medium on which a computer program is stored, which computer program, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 6.
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| CN110472517A (en) * | 2019-07-24 | 2019-11-19 | 广东校园卫士网络科技有限责任公司 | A kind of autonomous type campus visitor captures and analysis management method |
| CN113436735A (en) * | 2020-03-23 | 2021-09-24 | 北京好啦科技有限公司 | Body weight index prediction method, device and storage medium based on face structure measurement |
| CN112257581A (en) * | 2020-10-21 | 2021-01-22 | 广州云从凯风科技有限公司 | Face detection method, device, medium and equipment |
| CN113487670B (en) * | 2020-10-26 | 2024-09-13 | 海信集团控股股份有限公司 | Cosmetic mirror and state adjustment method |
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