问题描述
可以说，对于每个检测到的人脸，我都有一组这样的界标(来自人脸检测API的结果):
Lets say for each detected face, I have a set of landmarks like this (result from face detection API):
"eye_left": {
"x": 112.3,
"y": 210.3
},
"eye_right": {
"x": 217.5,
"y": 205.5
},
"nose": {
"x": 168.6,
"y": 269.7
},
"mouth l": {
"x": 119.1,
"y": 307.6
},
"mouth_l": {
"x": 119.1,
"y": 307.6
},
"mouth r": {
"x": 215,
"y": 302.9
},
"mouth_r": {
"x": 215,
"y": 302.9
},
"pose": {
"roll": -3.71,
"yaw": 3.92,
"pitch": -6.44
},
"b_ll": {
"x": 74.3,
"y": 184.6
},
"b_lm": {
"x": 103.7,
"y": 174.7
},
"b_lr": {
"x": 135.1,
"y": 182
},
"b_rl": {
"x": 194.1,
"y": 179.1
},
"b_rm": {
"x": 224.3,
"y": 167.9
},
"b_rr": {
"x": 253.3,
"y": 175.5
},
"e_ll": {
"x": 90.1,
"y": 210.5
},
"e_lr": {
"x": 134.5,
"y": 214.8
},
"e_lu": {
"x": 112.7,
"y": 201.1
},
"e_ld": {
"x": 111.9,
"y": 217.2
},
"e_rl": {
"x": 194.6,
"y": 212.6
},
"e_rr": {
"x": 239.9,
"y": 203.8
},
"e_ru": {
"x": 216.2,
"y": 195.8
},
"e_rd": {
"x": 219.1,
"y": 212.5
},
"n_l": {
"x": 144.1,
"y": 279.6
},
"n_r": {
"x": 190.9,
"y": 277.1
},
"m_u": {
"x": 167.9,
"y": 300.4
},
"m_d": {
"x": 169.2,
"y": 336.6
},
我的问题是，我可以仅使用这些地标来比较人脸的相似性吗?也许使用一些数学算法?
My question is, can I use these landmarks alone to compare faces for similarity? Perhaps using some mathematics algorithm?
谢谢.
推荐答案
这称为基于几何的人脸识别算法.您可以将其用于面部识别.但是假设您正在处理的脸部，会有各种脸部姿势的变化.这样，对应点周围的图像斑块的外观会有所不同，从而使识别精度下降.由于这个缺点，基于外观的方法比基于几何的方法更广泛地用于人脸识别.
It's called geometric based face recognition algorithm.You can use it for face recognition.But suppose that faces you are dealing with, have a variety of facial pose variation.Then the appearance of image patches surrounding the corresponding points would be differ, so makes the recognition accuracy degrade.From this disadvantage, appearance based methods are used greatly than geometric based one for face recognition.
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