# Review: Facial Anthropometric, Landmark Extraction, and Nasal Reconstruction Technology
## 3 Facial Landmark Extraction
### Facial Landmark Detection in Medicine  
Different from other applications, in the field of medicine, high accuracy and location are factors considered based on the sustainability of medical theories. For example, 18 facial \begin{table}
\begin{tabular}{c c c c c} \hline  & **Amount** & **Fps \({}^{*}\)** & **Year** & **Approach** \\ \hline [PERSON] et al. [13] & 4 & N/A & 2005 & Convolutional Face Finder and Feature Detector \\ \hline [PERSON] et al. [42] & 5 & 8.33 & 2013 & Deep Convolutional Network Cascade \\ \hline [PERSON] et al. [43] & 68 & 83.33 & 2018 & Branched Convolutional Neural Networks (BCNN) \\ \hline [PERSON] et al. [44] & 68 & 40 & 2019 & Branched Convolutional Neural Networks–Jacobian deep \\  & & & & regression (BCNN-JDR) \\ \hline [PERSON] et al. [45] & 68 & 11.11 & 2020 & Cascaded Heatmaps Regression into 2D Coordinates (CHR2C) \\ \hline [PERSON] et al. [46] & 68 & N/A & 2016 & VGG19 network–LSTM model \\ \hline [PERSON] et al. [47] & 68 & 16.67 & 2020 & Stacked Hourglass Network (SHN) \\ \hline [PERSON] et al. [48] & 68 & 86.20 & 2017 & 3D Dense Face Alignment (3 DDFA) \\ \hline [PERSON] et al. [49] & 19 & N/A & 2019 & Yolo model–Active Shape model (ASM) \\ \hline [PERSON] et al. [4] & 4 & N/A & 2014 & HAAR Cascade Classifier (enHaar and exHaar) \\ \hline [PERSON] et al. [51] & 68 & N/A & 2019 & CNN model–Conditional Random Field (CRF) \\ \hline [PERSON] et al. [52] & 49–74 & N/A & 2019 & CNN-LSTM–RNN model \\ \hline [PERSON] et al. [53] & 68 & 10 & 2015 & Pose-Induced Auto-encoder Networks (PIAN) \\ \hline [PERSON] et al. [54] & 68 & N/A & 2017 & Stacked Hourglass Network (SHN) \\ \hline [PERSON] et al. [55] & 68 & N/A & 2019 & Occlusion-adaptive Deep Networks (called ODN) \\ \hline [PERSON] et al. [56] & 68 & N/A & 2019 & Attentioned Distillation module in ODN model \\ \hline [PERSON] et al. [57] & 68 &
\begin{tabular}{c} 8–400 (based on number \\ of parameters) \\ \end{tabular} & 2018 & CNN model with a new Wingloss function \\ \hline [PERSON] et al. [58] & 68 & 45 & 2021 & Anchorface \\ \hline [PERSON] et al. [59] & 68 & 253–417 & 2022 & Two different teacher networks guiding the student network with KD-Loss \\ \hline [PERSON] et al. [60] & 68 & N/A & 2019 & Teacher model Supervises Students (TS3) \\ \hline [PERSON] et al. [15] & 29 & 2.5 & 2013 & Support Vector Machine (SVM) classifier \\ \hline [PERSON] et al. [66] & 194 & 1000 & 2014 & Regression Trees \\ \hline [PERSON] et al. [67] & 68 & N/A & 2018 & Cascaded Regression Tree \\ \hline [PERSON] et al. [14] & 49–194 & 25 & 2015 & Coarse-to-Fine Shape Searching (CFSS) \\ \hline [PERSON] et al. [64] & 68 & 700 & 2017 & Fast Shape Searching Face Alignment model (F-SSFA) \\ \hline [PERSON] et al. [65] & 68 & 43.48 & 2014 & Coarse-to-Fine Auto-encoder Networks \\ \hline \end{tabular}  
* Fps is frame per second, nevertheless, it is for reference only because it depends on many factors including the hardware; N/A: Not Available.  
\end{table} 
Table 2: Summarizing the facial landmark extraction using deep CNN and non-deep CNN models, reviewed in Sections 3.1 and 3.2.  
landmarks were extracted automatically using the Anthropometric Face Model introduced by [PERSON] et al. [68]. They used the distance of the eyes as the main parameter for finding other areas of the face, and the rotation angle of the face was recognized and calibrated to the frontal angle to increase the accuracy of the model. Then, 18 facial landmarks were also located by an Anthropometric Face Mode proposed by them in a previous study [69]. However, the study only corrects the face horizontally and is not effective for large vertical rotations; in addition, the accuracy of the model depends on the accuracy of the recognition of the centers of the two introduced eyes, according to the study of [PERSON] et al. [70]. In another study, [PERSON] et al. [71] established mathematical relationships among horizontal and vertical distances from the 18 landmarks identified to perform 16 Euclidean measurements.