CN111666835A - Face living body detection method and device - Google Patents
Face living body detection method and device Download PDFInfo
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- CN111666835A CN111666835A CN202010432044.7A CN202010432044A CN111666835A CN 111666835 A CN111666835 A CN 111666835A CN 202010432044 A CN202010432044 A CN 202010432044A CN 111666835 A CN111666835 A CN 111666835A
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- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
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Abstract
The invention discloses a face in-vivo detection method and a face in-vivo detection device, which specifically comprise the following steps: presetting a plurality of human face living body detection schemes, wherein the human face living body detection schemes comprise but are not limited to an infrared human face detection scheme, a random action human face detection scheme, an ultrasonic human face detection scheme, a frame detection scheme, a camera array detection scheme and a 3D human face detection scheme; and judging whether the face living body detection needs to be executed, and if so, randomly selecting one or more face living body detection schemes to execute the face living body detection step. The invention presets a plurality of human face living body detection schemes, when human face identification is needed, one or more human face living body detection schemes can be randomly selected for human face living body detection, so that the face identification device can be effectively prevented from being deceived by illegal users by using pre-recorded videos containing specified actions, the identification accuracy is improved, and financial accounts of the users are prevented from being embezzled.
Description
Technical Field
The invention relates to the technical field of face recognition, in particular to a face living body detection method and a face living body detection device.
Background
Face recognition is a biometric technique for identifying an identity based on facial feature information of a person. The method comprises a series of related technologies of collecting images or video streams containing human faces by using a camera or a camera, automatically detecting and tracking the human faces in the images, and further identifying the detected human faces. Face recognition has been widely applied to the fields of public security, bank finance, public security criminal investigation, social media and the like, and particularly, face recognition technology is recently applied to face payment. However, there are various counterfeit means based on face recognition defects, wherein face photos and video images are mainly used as the counterfeit means.
The following method is generally adopted to judge whether the acquired face image is a living body image: the method comprises the steps of requiring a user to make a specified action, such as blinking, opening the mouth and the like or turning the face left and right and the like, collecting a face image, judging whether the user completes the specified action or not according to the collected face image, and if so, judging that the collected face image is a living body image. However, this method is not user friendly, and some illegal users can spoof the face recognition device with a pre-recorded video containing the specified action, resulting in low recognition accuracy. And the low recognition accuracy may cause the financial account of the user to be swiped illegally.
Disclosure of Invention
The invention provides a face living body detection method and a face living body detection device, which solve the problems that in the prior art, some illegal users can use a prerecorded video containing specified actions to deceive face recognition equipment, so that the recognition accuracy is low, and the financial account of the user is possibly stolen and swiped due to the low recognition accuracy.
The technical scheme of the invention is realized as follows:
a human face living body detection method specifically comprises the following steps:
s1, presetting a plurality of human face living body detection schemes, wherein the human face living body detection schemes comprise but are not limited to an infrared human face detection scheme, a random action human face detection scheme, an ultrasonic human face detection scheme, a frame detection scheme, a camera array detection scheme and a 3D human face detection scheme;
and S2, judging whether the human face living body detection needs to be executed, if so, randomly selecting one or more human face living body detection schemes to execute the human face living body detection step.
As a preferred embodiment of the present invention, the infrared face detection scheme specifically refers to
Constructing an infrared image human face detection neural network model;
the infrared image is obtained through the infrared camera and input into the infrared image face detection neural network model, whether the infrared image has a face or not is judged, if yes, the visible light image with the face is obtained through shooting of the visible light camera, and the visible light image is input into the face recognition model, so that face recognition is achieved.
As a preferred embodiment of the present invention, the random-motion face detection scheme specifically refers to
Constructing a random action database;
generating a random action instruction to be completed by the five sense organs of the target face and sending the random action instruction to a target to be detected;
the method comprises the steps of obtaining a video of a detected target human face five sense organs, extracting a plurality of image samples from the video, sequentially inputting the image samples into a human face recognition model, outputting coordinate values of human face five sense organs feature points, judging whether coordinate value change tracks of the human face five sense organs feature points conform to random action instructions or not, and determining that the human face is a living body if the coordinate value change tracks of the human face five sense organs feature points conform to the random action instructions.
As a preferred embodiment of the present invention, the ultrasonic face detection scheme specifically refers to
A plurality of ultrasonic detection devices are provided, and the distances of a plurality of parts to be detected are detected by the ultrasonic detection devices, respectively, to determine whether the parts are living bodies.
As a preferred embodiment of the present invention, the border detection scheme specifically refers to
The method comprises the steps of collecting videos through a camera to carry out face detection, extracting frames from the videos to obtain images if faces are detected, carrying out frame detection on the images, and judging that the living bodies are not living bodies if the frames are detected in the images and the frames contain the detected face frames.
As a preferred embodiment of the present invention, the camera array detection scheme specifically refers to
And setting a camera array, acquiring images at different angles through the camera array, inputting the images into a face recognition model, and determining that the images contain faces at different angles or determining that the images do not detect frames containing faces.
As a preferred embodiment of the present invention, the 3D face detection scheme specifically refers to
And collecting a 3D face image, selecting a plurality of groups of feature points from the 3D face image, acquiring three-dimensional coordinates of the feature points, and checking the three-dimensional coordinates with a preset database to judge whether the living body is the living body.
A human face living body detection device is used for realizing the human face living body detection device.
The invention has the beneficial effects that: a plurality of face living body detection schemes are preset, the face living body detection schemes comprise but are not limited to an infrared face detection scheme, a random action face detection scheme, an ultrasonic face detection scheme, a frame detection scheme, a camera array detection scheme and a 3D face detection scheme, when face identification is needed, one or more face living body detection schemes can be randomly selected for face living body detection, an illegal user can be effectively prevented from using a prerecorded video deception face identification device containing an appointed action, the identification accuracy is improved, and a financial account of the user is prevented from being stolen and brushed.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
Fig. 1 is a flowchart of an embodiment of a face live detection method according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In the description of the present invention, it should be noted that the terms "vertical", "upper", "lower", "horizontal", and the like indicate orientations or positional relationships based on those shown in the drawings, and are only for convenience of describing the present invention and simplifying the description, but do not indicate or imply that the referred device or element must have a specific orientation, be constructed in a specific orientation, and be operated, and thus, should not be construed as limiting the present invention.
In the description of the present invention, it should also be noted that, unless otherwise explicitly specified or limited, the terms "disposed," "mounted," "connected," and "connected" are to be construed broadly and may, for example, be fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
As shown in fig. 1, the present invention provides a human face living body detection method, which specifically includes the following steps:
s1, presetting a plurality of human face living body detection schemes, wherein the human face living body detection schemes comprise but are not limited to an infrared human face detection scheme, a random action human face detection scheme, an ultrasonic human face detection scheme, a frame detection scheme, a camera array detection scheme and a 3D human face detection scheme; specifically, in the implementation process, other human face living body detection schemes can be set.
And S2, judging whether the human face living body detection needs to be executed, if so, randomly selecting one or more human face living body detection schemes to execute the human face living body detection step. For example, in the face payment process of a supermarket, if a customer selects face payment, a face living body detection step needs to be executed in advance, and if the customer determines that the face living body exists, then payment operation is executed, so that the risk that a financial account of the customer is stolen and brushed is reduced.
Unique identification codes are respectively set for an infrared face detection scheme, a random action face detection scheme, an ultrasonic face detection scheme, a frame detection scheme, a camera array detection scheme and a 3D face detection scheme, the unique identification codes are stored in a database, and one unique identification code is randomly selected from the database at equal probability.
As a preferred embodiment of the present invention, the infrared face detection scheme specifically refers to
Constructing an infrared image human face detection neural network model; the infrared image face detection neural network model is obtained by FeatherNet B training, the FeatherNet B inputs the size of 224X224 pictures, and the model is formed by combining neural network sub-blocks Block A, Block B and Block C. The neural network model can learn better texture details, so that the accuracy of in-vivo detection is improved.
The infrared image is obtained through the infrared camera and input into the infrared image face detection neural network model, whether the infrared image has a face or not is judged, if yes, the visible light image with the face is obtained through shooting of the visible light camera, and the visible light image is input into the face recognition model, so that face recognition is achieved. In the actual operation process, whether the action of lifting the mobile phone exists or not can be simply judged by detecting the infrared image of the human body, so that whether the illegal user uses the prerecorded video deception face recognition equipment containing the specified action or not is judged.
As a preferred embodiment of the present invention, the random-motion face detection scheme specifically refers to
Constructing a random action database; specifically, the random action may be to pluck the eyebrow, close the eye, open the mouth, and so on.
Generating a random action instruction to be completed by the five sense organs of the target face and sending the random action instruction to a target to be detected;
the method comprises the steps of obtaining a video of a detected target human face five sense organs, extracting a plurality of image samples from the video, sequentially inputting the image samples into a human face recognition model, outputting coordinate values of human face five sense organs feature points, judging whether coordinate value change tracks of the human face five sense organs feature points conform to random action instructions or not, and determining that the human face is a living body if the coordinate value change tracks of the human face five sense organs feature points conform to the random action instructions.
As a preferred embodiment of the present invention, the ultrasonic face detection scheme specifically refers to
A plurality of ultrasonic detection devices are provided, and the distances of a plurality of parts to be detected are detected by the ultrasonic detection devices, respectively, to determine whether the parts are living bodies. For example, a cash register integrated machine in a supermarket has a height approximately corresponding to the upper half of the human body, ultrasonic detection devices are sequentially fixed at two frames of the machine body from top to bottom, and if an illegal user uses a pre-recorded video containing an appointed action, the ultrasonic detection devices at different heights can acquire a group of distance values with a large difference, so as to judge whether the human face is a living body.
As a preferred embodiment of the present invention, the border detection scheme specifically refers to
The method comprises the steps of collecting videos through a camera to carry out face detection, extracting frames from the videos to obtain images if faces are detected, carrying out frame detection on the images, and judging that the living bodies are not living bodies if the frames are detected in the images and the frames contain the detected face frames.
As a preferred embodiment of the present invention, the camera array detection scheme specifically refers to
And setting a camera array, acquiring images at different angles through the camera array, inputting the images into a face recognition model, and determining that the images contain faces at different angles or determining that the images do not detect frames containing faces. For example, a cash register integrated machine in a supermarket is approximately corresponding to the upper half of a human body in height, and cameras are sequentially fixed on the frame of the machine body from top to bottom.
Key point P on human face is at multiple points P of multiple camera imaging planes1、P2……PnRespectively is (x)1，y1)，(x2，y2)……(xn，yn). Two points are arbitrarily selected from the two points, and according to a binocular ranging formula:
wherein f is the focal length of the camera, T is the distance between the two cameras, and the two parameters can be regarded as a fixed coefficient. So X1-XmThe depth information of the key points of the human face can be reflected. n is an integer greater than 2, and m is an integer greater than 1 and less than n.
In another embodiment, whether the face is a living body can be judged by judging whether key points of the face acquired by different cameras accord with the depth information.
As a preferred embodiment of the present invention, the 3D face detection scheme specifically refers to
And collecting a 3D face image, selecting a plurality of groups of feature points from the 3D face image, acquiring three-dimensional coordinates of the feature points, and checking the three-dimensional coordinates with a preset database to judge whether the living body is the living body.
In the specific implementation process, factors such as the accuracy, the response speed, the operation memory and the like of a single scheme of an infrared face detection scheme, a random action face detection scheme, an ultrasonic face detection scheme, a frame detection scheme, a camera array detection scheme and a 3D face detection scheme and a combination scheme are comprehensively sequenced, and if face living body detection needs to be executed, a detection scheme at the tail of sequencing is excluded when a plurality of face living body detection schemes are randomly selected.
A human face living body detection device is used for realizing the human face living body detection device. The device can be integrated cash register equipment of a supermarket.
The invention has the beneficial effects that: a plurality of face living body detection schemes are preset, the face living body detection schemes comprise but are not limited to an infrared face detection scheme, a random action face detection scheme, an ultrasonic face detection scheme, a frame detection scheme, a camera array detection scheme and a 3D face detection scheme, when face identification is needed, one or more face living body detection schemes can be randomly selected for face living body detection, an illegal user can be effectively prevented from using a prerecorded video deception face identification device containing an appointed action, the identification accuracy is improved, and a financial account of the user is prevented from being stolen and brushed.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (8)
1. A human face living body detection method is characterized by comprising the following steps:
s1, presetting a plurality of human face living body detection schemes, wherein the human face living body detection schemes comprise but are not limited to an infrared human face detection scheme, a random action human face detection scheme, an ultrasonic human face detection scheme, a frame detection scheme, a camera array detection scheme and a 3D human face detection scheme;
and S2, judging whether the human face living body detection needs to be executed, if so, randomly selecting one or more human face living body detection schemes to execute the human face living body detection step.
2. The method according to claim 1, wherein the infrared human face detection scheme specifically refers to
Constructing an infrared image human face detection neural network model;
the infrared image is obtained through the infrared camera and input into the infrared image face detection neural network model, whether the infrared image has a face or not is judged, if yes, the visible light image with the face is obtained through shooting of the visible light camera, and the visible light image is input into the face recognition model, so that face recognition is achieved.
3. The method according to claim 1, wherein the random-action face detection scheme specifically refers to
Constructing a random action database;
generating a random action instruction to be completed by the five sense organs of the target face and sending the random action instruction to a target to be detected;
the method comprises the steps of obtaining a video of a detected target human face five sense organs, extracting a plurality of image samples from the video, sequentially inputting the image samples into a human face recognition model, outputting coordinate values of human face five sense organs feature points, judging whether coordinate value change tracks of the human face five sense organs feature points conform to random action instructions or not, and determining that the human face is a living body if the coordinate value change tracks of the human face five sense organs feature points conform to the random action instructions.
4. The living human face detection method as claimed in claim 1, wherein the ultrasonic human face detection scheme specifically refers to
A plurality of ultrasonic detection devices are provided, and the distances of a plurality of parts to be detected are detected by the ultrasonic detection devices, respectively, to determine whether the parts are living bodies.
5. The method according to claim 1, wherein the frame detection scheme specifically refers to
The method comprises the steps of collecting videos through a camera to carry out face detection, extracting frames from the videos to obtain images if faces are detected, carrying out frame detection on the images, and judging that the living bodies are not living bodies if the frames are detected in the images and the frames contain the detected face frames.
6. The method according to claim 1, wherein the camera array detection scheme specifically refers to
And setting a camera array, acquiring images at different angles through the camera array, inputting the images into a face recognition model, and determining that the images contain faces at different angles or determining that the images do not detect frames containing faces.
7. The method according to claim 1, wherein the 3D face detection scheme specifically refers to
And collecting a 3D face image, selecting a plurality of groups of feature points from the 3D face image, acquiring three-dimensional coordinates of the feature points, and checking the three-dimensional coordinates with a preset database to judge whether the living body is the living body.
8. A face liveness detection apparatus, characterized by means for implementing a face liveness detection method according to any one of claims 1 to 7.
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| CN112418865A (en) * | 2020-11-13 | 2021-02-26 | 上海臻面智能信息科技有限公司 | Living body detection method based on safety payment module |
| CN112990019A (en) * | 2021-03-18 | 2021-06-18 | 广州伟宏智能科技有限公司 | Face recognition living body detection method |
| CN113066237A (en) * | 2021-03-26 | 2021-07-02 | 中国工商银行股份有限公司 | Face living body detection and identification method for automatic teller machine and automatic teller machine |
| CN113486834A (en) * | 2020-12-09 | 2021-10-08 | 上海齐感电子信息科技有限公司 | Method for confirming effective face area and verifying living face |
| CN114495192A (en) * | 2021-12-09 | 2022-05-13 | 成都臻识科技发展有限公司 | Multi-model-based face anti-counterfeiting method, storage medium and detection equipment |
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