CN112364777B - Face distance estimation method based on face recognition - Google Patents
Face distance estimation method based on face recognition Download PDFInfo
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/161—Detection; Localisation; Normalisation
- G06V40/165—Detection; Localisation; Normalisation using facial parts and geometric relationships
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
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- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/168—Feature extraction; Face representation
- G06V40/171—Local features and components; Facial parts ; Occluding parts, e.g. glasses; Geometrical relationships
Abstract
The invention discloses a face distance estimation method based on face recognition. The face distance calculation is carried out according to images obtained after a plurality of people are shot by the cameras, and the method comprises the following steps: 1) Acquiring a horizontal view angle value of a camera; 2) Establishing a space rectangular coordinate system; 3) Acquiring coordinates of a face organ in an image; 4) Calculating the distance between eyes of a person and the distance between the eyebrows and the center of the mouth in the image, and 5) calculating the real distance between the person and the camera in the direction of the number axis Oz; calculating the real distance from the person to the center point of the image in the direction of the number axis Ox; 6) An estimated distance between any two persons is calculated. According to the invention, the coordinate information of the target eyes, nose and mouth in the picture is obtained by the face recognition technology based on deep learning, and the face distance is obtained by using a projection geometric algorithm on the detection result, so that the face distance estimation can be realized at low cost.
Description
Technical Field
The invention relates to the field of computer vision, in particular to a face distance estimation method based on face recognition.
Background
The measurement of people-to-people spacing in video frames is an important technology in many intelligent education and community infrastructure at present. Traditional ranging modes based on radar, ultrasonic waves, binocular cameras and the like have the defects of high deployment difficulty, low coupling degree with the existing monitoring equipment, high requirement on the environment of a monitoring site and the like. In order to meet the requirement of on-site personnel spacing measurement during monitoring, research and development of a ranging algorithm applicable to most monitoring equipment are urgently needed.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention provides a face distance calculation method based on face recognition. The invention has the advantages of no need of extra hardware overhead, low deployment cost, capability of directly utilizing the existing monitoring equipment to measure distance and low requirement on environmental condition stability. The target detection frame is obtained through the face target detection operation based on deep learning, and the face distance is obtained through a projection geometric algorithm on the detection result, so that the face distance measurement can be realized with low cost.
A face distance estimation method based on face recognition carries out face distance calculation according to images obtained after a plurality of people are shot by cameras, and the method comprises the following steps:
1) Acquiring a value of a horizontal visual angle alpha of the camera;
2) Establishing a space rectangular coordinate system: taking the top left vertex of the picture as an origin O, taking the right direction of an O point as an x-axis positive direction, taking the downward direction of the O point as a y-axis positive direction, and taking the direction which is perpendicular to the plane of the picture and outwards as a z-axis positive direction;
3) Acquiring coordinate information of a left eye pupil, a right eye pupil, a nose tip, a left mouth corner and a right mouth corner of a face of a person from an image: eye_left (x) 1 ，y 1 )，eye_right(x 2 ，y 2 )，nose(x 3 ，y 3 )，mouth_left(x 4 ，y 4 )，mouth_right(x 5 ，y 5 )；
4) Calculating the distance g between two eyes of the person in the x-axis direction in the image 1 ＝|x 1 -x 2 Calculating the distance g between the eyebrow center and the mouth center of the person in the image in the y-axis direction 2 ＝(|y 1 -y 4 |+|y 2 -y 5 I)/2, calculating the interocular distance of the person on the xOy plane in the image
Calculating the center-to-center distance +.f between the eyebrow and the mouth of the person on the xOy plane in the image>
The triangle composed of three points of the eye_left, the eye_right and the phase is set as a triangle A, the distance between the coordinate eye_left and the phase on the xOy plane is set as a, the distance between the coordinate eye_right and the phase on the xOy plane is set as b, and g is set as b 1 The actual length in reality is set to g 1 _real；
a) When a is greater than or equal to b and a/b is less than 1.4 or a is less than or equal to b andb/a is less than 1.4, the face is raised, lowered, rotated clockwise or rotated anticlockwise or is completely opposite to the camera mirror face: g 1 _real＝(L 1 /f 1 )×g 1 ；
b) When a is more than or equal to b and a/b is more than or equal to 1.4 or a is less than or equal to b and b/a is more than 1.4, the face turns left, right, left upper, right upper, left lower or right lower:
when g1 < g2, g 1 _real＝(L 2 /f 2 )×g 1 ，
When g1 > g2, g 1 _real＝(L 1 /f 1 )×g 1 ；
5) Calculate g 1 Ratio R to image width W 1 ＝g 1 W, calculate g 1 Angle of horizontal view of the camera: beta=r 1 X alpha, calculating the true distance n=g of the person to the camera 1 Real/tan beta; let c be the real distance of the person to the camera in the direction of the number axis Oz, estimate the value of c: c is approximately equal to n; calculating the image distance e= |x from the nose tip of the person to the image center point in the direction of the numerical axis Ox 3 -W/2|, calculating the ratio R of e to W 2 =e/W, calculate the angle of the horizontal view of the camera occupied by e: η=r 2 Calculating the true distance w=c×tan η of the person to the image center point in the direction of the number axis Ox;
6) For personnel P i ，P j Respectively performing 3) to 5), respectively obtaining personnel P i And P j True distance c to camera in the direction of the number axis Oz i And c j Personnel P i And P j True distance w to the center of the picture in the direction of the number axis Ox i And w j ；
7) Calculator P i And P j True distance in the number axis Ox direction: when person P i And P j X= |w when both are on the left or right side of the image center point i -w j I (I); when person P i And P j When distributed on both sides of the image center point, x=w i +w j The method comprises the steps of carrying out a first treatment on the surface of the Personnel P i And P j The true distance z= |c in the direction of the number axis Oz i -c j I (I); calculating an estimated distance between any two persons
In the step 3), the coordinate information of the left eye pupil, the right eye pupil, the nose tip, the left mouth corner and the right mouth corner of the face is obtained, and the method comprises the following steps: and acquiring the facial organ coordinate information by using a Retinaface detector based on deep learning training.
In the step 4), the values of L1 and L2 are derived from the average distance between the facial organs of the adult in GB2428-81 series of Chinese adult head types: left eye to right eye interocular distance L 1 =0.07 m, spacing L between eyebrow and mouth center 2 ＝0.07m。
The invention has the following beneficial effects: the method has the advantages of no need of extra hardware overhead, low deployment cost, capability of directly utilizing the existing monitoring equipment to measure distance, and low requirement on environmental condition stability. The coordinate information of the target eyes, nose and mouth in the picture is obtained through the face recognition technology based on deep learning, and the face distance is obtained through a projection geometric algorithm on the detection result, so that the face distance estimation can be realized at low cost.
Drawings
FIG. 1 is a photograph taken by a camera at a certain time;
fig. 2 is a result diagram of a face distance calculation method based on face recognition.
Detailed description of the preferred embodiments
The present invention will be further described and illustrated with reference to the accompanying drawings and examples in order to make the objects, technical solutions and advantages of the present invention more apparent. The technical features of the embodiments of the invention can be combined correspondingly on the premise of no mutual conflict.
As shown in fig. 1, a face distance estimation method based on face recognition performs face distance calculation according to images obtained after a plurality of persons are photographed by a camera, including the following steps:
1) Acquiring a value of a horizontal visual angle alpha of the camera;
2) Establishing a space rectangular coordinate system: taking the top left vertex of the picture as an origin O, taking the right direction of an O point as an x-axis positive direction, taking the downward direction of the O point as a y-axis positive direction, and taking the direction which is perpendicular to the plane of the picture and outwards as a z-axis positive direction;
3) Acquiring coordinate information of a left eye pupil, a right eye pupil, a nasal tip, a left mouth corner and a right mouth corner of a face of a person in an image: eye_left (x) 1 ，y 1 )，eye_right(x 2 ，y 2 )，nose(x 3 ，y 3 )，mouth_left(x 4 ，y 4 )，mouth_right(x 5 ，y 5 )；
4) Calculating the distance g between two eyes of the person in the x-axis direction in the image 1 ＝|x 1 -x 2 Calculating the distance g between the eyebrow center and the mouth center of the person in the image in the y-axis direction 2 ＝(|y 1 -y 4 |+|y 2 -y 5 I)/2, calculating the interocular distance of the person on the xOy plane in the image
Calculating the center-to-center distance +.f between the eyebrow and the mouth of the person on the xOy plane in the image>
The triangle composed of three points of the eye_left, the eye_right and the phase is set as a triangle A, the distance between the coordinate eye_left and the phase on the xOy plane is set as a, the distance between the coordinate eye_right and the phase on the xOy plane is set as b, and g is set as b 1 The actual length in reality is set to g 1 _real；
a) When a is more than or equal to b and a/b is less than or equal to 1.4 or a is less than or equal to b and b/a is less than 1.4, the face is lifted, lowered, rotated clockwise, rotated anticlockwise or completely opposite to the camera mirror face: g 1 _real＝(L 1 /f 1 )×g 1 ；
b) When a is more than or equal to b and a/b is more than or equal to 1.4 or a is less than or equal to b and b/a is more than 1.4, the face turns left, right, left upper, right upper, left lower or right lower:
when g1 < g2, g 1 _real＝(L 2 /f 2 )×g 1 ，
When g1 > g2, g 1 _real＝(L 1 /f 1 )×g 1 ；
5) Calculate g 1 Ratio R to image width W 1 ＝g 1 W, calculate g 1 Angle of horizontal view of the camera: beta=r 1 X alpha, calculating the true distance n=g of the person to the camera 1 Real/tan beta; let c be the real distance of the person to the camera in the direction of the number axis Oz, estimate the value of c: c is approximately equal to n; calculating the image distance e= |x from the nose tip of the person to the image center point in the direction of the numerical axis Ox 3 -W/2|, calculating the ratio R of e to W 2 =e/W, calculate the angle of the horizontal view of the camera occupied by e: η=r 2 Calculating the true distance w=c×tan η of the person to the image center point in the direction of the number axis Ox;
6) For personnel P i ，P j Respectively performing 3) to 5), respectively obtaining personnel P i And P j True distance c to camera in the direction of the number axis Oz i And c j Personnel P i And P j True distance w to the center of the picture in the direction of the number axis Ox i And w j ；
7) Calculator P i And P j True distance in the number axis Ox direction: when person P i And P j X= |w when both are on the left or right side of the image center point i -w j I (I); when person P i And P j When distributed on both sides of the image center point, x=w i +w j The method comprises the steps of carrying out a first treatment on the surface of the Personnel P i And P j The true distance z= |c in the direction of the number axis Oz i -c j I (I); calculating an estimated distance between any two persons
In the step 3), the coordinate information of the left eye pupil, the right eye pupil, the nose tip, the left mouth corner and the right mouth corner of the face is obtained, and the method comprises the following steps: obtaining facial organ coordinate information by using a Retinaface detector based on deep learning training;
the saidIn step 4) of (2), the values of L1 and L2 are derived from the average distance between the facial organs of adults of the Chinese adult head series of GB 2428-81: left eye to right eye interocular distance L 1 =0.07 m, spacing L between eyebrow and mouth center 2 ＝0.07m。
Examples
To facilitate the understanding and practice of the invention by those of ordinary skill in the art, a specific embodiment of the method of the invention will now be presented. The core idea of estimating the distance of the person by using the face recognition technology and the projection geometric algorithm is as follows: the coordinate information of the target eyes, nose and mouth in the picture is obtained through the face recognition technology based on deep learning, and the face distance is obtained through a projection geometric algorithm on the detection result, so that the face distance estimation can be realized at low cost.
A seup>A-health DS-2DC7423IW-A camerup>A is installed in up>A certain room, and the iVMS-4200 client is used for acquiring the ip address of the camerup>A and the URL used for accessing in up>A program. In the program, an OpenCV function library of python language is used, and a camera is accessed according to the URL to acquire a picture.
And acquiring a picture of the place by a camera of the place. The picture size is: 1087×610, coordinates Pic (x pic ，y pic ) = (543.5, 305). Referring to the camera specification, the horizontal angle of view α=60° of the camera is obtained.
Establishing a space rectangular coordinate system: the top left vertex of the picture is taken as an origin O, the right direction of the O point is taken as an x-axis positive direction, the downward direction of the O point is taken as a y-axis positive direction, and the direction perpendicular to the plane of the picture is taken as a z-axis positive direction.
Person P in image is acquired by using Retinaface detector based on deep learning training 1 Coordinate information of left eye pupil, right eye pupil, nasal tip, left mouth corner, right mouth corner: left_eye 1 (636，447)、right_eye 1 (653，454)、nose 1 (634，463)、left_mouth 1 (636，472)、right_mouth 1 (647, 477); coordinate information of left eye pupil, right eye pupil, nose tip, left mouth corner, right mouth corner of person P2: left_eye 2 (140，243)、right_eye 2 (151，240)、nose 2 (146，250)、left_mouth 2 (143，255)、right_mouth 2 (152，253)。
According to the average distance between adult facial organs in GB2428-81, china adult head shape series, eye distance L1=0.07 m, and distance L2=0.07 m from eyebrow center to mouth center.
Calculator P 1 G of (2) 1 ＝|x 1 -x 2 |＝17，g 2 ＝(|y 1 -y 4 |+|y 2 -y 5 |)/2＝24，
At this time, a.ltoreq.b and b/a < 1.4, g 1 _real＝(L 1 /f 1 )×g 1 ＝0.065m。R 1 ＝g 1 /W＝0.016，β＝R 1 ×α＝0.94°，c i ≈n＝g 1 _real/tanβ＝3.95m。e＝|x 3 -W/2|＝90.5，R 2 ＝e/W＝0.083，η＝R 2 ×α＝4.995°，w i ＝c i ×tanη＝0.35m。
Calculator P 2 G of (2) 1 ＝11，g 2 ＝12.5，f 1 ＝11.40，f 2 =12.66, a=9.22, b=11.18. At this time, a.ltoreq.b and b/a < 1.4, g 1 _real＝(L 1 /f 1 )×g 1 ＝0.068m。R 1 ＝g 1 /W＝0.01，β＝R 1 ×α＝0.61°，c j ≈n＝g 1 _real/tanβ＝6.37m。e＝|x 3 -W/2|＝397.5，R 2 ＝e/W＝0.37，η＝R 2 ×α＝21.94°，w j ＝c j ×tanη＝2.57m。
Personnel P 1 Subtracting the x-axis coordinate k of the center of the picture from the x-axis coordinate of the tip of the nose 1 =90.5, person P 2 Subtracting the x-axis coordinate of the center of the picture from the x-axis coordinate of the tip of the nosek 2 = -397.5, it can be determined that person P1 is on the right side of the image, person P 2 On the left side of the image. Deriving x=w i +w j ＝2.92m，z＝|c i -c j I, get the estimated distance between any two people
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Claims (2)
1. The face distance estimation method based on face recognition is characterized by comprising the following steps of:
1-1) obtaining a value of a horizontal view angle alpha of the camera;
1-2) establishing a space rectangular coordinate system: taking the top left vertex of the picture as an origin O, taking the right direction of an O point as an x-axis positive direction, taking the downward direction of the O point as a y-axis positive direction, and taking the direction which is perpendicular to the plane of the picture and outwards as a z-axis positive direction;
1-3) acquiring coordinate information of a left eye pupil, a right eye pupil, a nose tip, a left mouth corner and a right mouth corner of a face of a person from an image: eye_left (x) 1 ,y 1 )，eye_right(x 2 ,y 2 )，nose(x 3 ,y 3 )，mouth_left(x 4 ,y 4 )，mouth_right(x 5 ,y 5 )；
1-4) calculating the distance g between the eyes of the person in the x-axis direction in the image 1 ＝|x 1 -x 2 Calculating the distance g between the eyebrow center and the mouth center of the person in the image in the y-axis direction 2 ＝(|y 1 -y 4 |+|y 2 -y 5 I)/2, calculating the interocular distance of the person on the xOy plane in the image
Calculating the center-to-center spacing of the eyebrow to the mouth of the person on the xOy plane in the image
Three points of eye_left, eye_right and nose are combinedThe triangle formed is set to be triangle a, the distance between the coordinates eye_left and the phase on the xOy plane is set to be a, the distance between the coordinates eye_right and the phase on the xOy plane is set to be b, and g is set to be g 1 The actual length in reality is set to g 1 _real；
a) When a is more than or equal to b and a/b is less than or equal to 1.4 or a is less than or equal to b and b/a is less than 1.4, the face is lifted, lowered, rotated clockwise, rotated anticlockwise or completely opposite to the camera mirror face: g 1 _real＝(L 1 /f 1 )×g 1 ；
b) When a is more than or equal to b and a/b is more than or equal to 1.4 or a is less than or equal to b and b/a is more than 1.4, the face turns left, right, left upper, right upper, left lower or right lower:
when g1 < g2, g 1 _real＝(L 2 /f 2 )×g 1 ，
When g1 > g2, g 1 _real＝(L 1 /f 1 )×g 1 ；
1-4) the L 1 And L 2 The values of (2) are derived from the average spacing of the facial organs of adults from the chinese adult cephalic series of GB 2428-81: left eye to right eye interocular distance L 1 =0.07 m, spacing L between eyebrow and mouth center 2 ＝0.07m；
1-5) calculating g 1 Ratio R to image width W 1 ＝g 1 W, calculate g 1 Angle of horizontal view of the camera: beta=r 1 X alpha, calculating the true distance n=g of the person to the camera 1 Real/tan beta; let c be the real distance of the person to the camera in the direction of the number axis Oz, estimate the value of c: c is approximately equal to n; calculating the image distance e= |x from the nose tip of the person to the image center point in the direction of the numerical axis Ox 3 -W/2|, calculating the ratio R of e to W 2 =e/W, calculate the angle of the horizontal view of the camera occupied by e: η=r 2 Calculating the true distance w=c×tan η of the person to the image center point in the direction of the number axis Ox;
1-6) person P i ，P j Respectively performing 1-3) to 1-5), respectively obtaining personnel P i And P j True distance c to camera in the direction of the number axis Oz i And c j People, peoplePersonnel P i And P j True distance w to the center of the picture in the direction of the number axis Ox i And w j ；
1-7) calculating person P i And P j True distance in the number axis Ox direction: when person P i And P j X= |w when both are on the left or right side of the image center point ii -w j I (I); when person P i And P j When distributed on both sides of the image center point, x=w i +w j The method comprises the steps of carrying out a first treatment on the surface of the Personnel P i And P j The true distance z= |c in the direction of the number axis Oz ii -c j I (I); calculating an estimated distance between any two persons
2. The method according to claim 1, wherein 1-3) the acquiring coordinate information of the left eye pupil, the right eye pupil, the nose tip, the left mouth corner, and the right mouth corner of the face comprises the following steps: and acquiring the facial organ coordinate information by using a Retinaface detector based on deep learning training.
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