# Review: Facial Anthropometric, Landmark Extraction, and Nasal Reconstruction Technology
## 5 Discussions and Evaluations
The number of landmarks is determined depending on the application, and the surveyed papers were determined between 5 and 80 key points. Some studies only identify a few areas of the face, such as two eyes, nose, and mouth, or recognize a few facial landmarks that are applied in simple applications, such as determining the rotation angle of the face and recognizing the face, or a large number of landmarks in facials were used in emotional identification and reconstruction. With a non-deep learning method, [PERSON] et al. [108] showed that the accuracy of landmarks depends on the number of points identified because the points are determined based on a part of the coordinates of other neighborhood points. They showed a big change in accuracy when changing the number of landmarks from 3 to 68. Factors considered in landmark recognition are the accuracy and speed of the model, and the model's ability to handle various poses or occlusion. To solve the problem of accuracy in occlusion cases, network structures with a large number of parameters are proposed [109; 110]. In these studies, the issues of landmark detection were solved very well, but too many model parameters make it difficult to have real-time applications. Accuracy and processing speed are considered a trade-off, as shown in [111]. The mentioned studies are applied in many cases, but they have not been used in medical studies. In hospitals, the recognition of facial landmarks is now mostly a manual method; it is essential to apply automatic identification and measurement in medicine. Many studies have impressive results but have not yet connected them to studies in the medical field. In some cases, the anthropometric measurements were performed automatically from facial landmarks that were manually marked [93]. Nowadays, 3D printing technology is developed as a rapid prototyping device that is applied in many fields. Recently, it has been applied to medicine, especially for clinical diagnoses, and 3D models are created for medical education and patient education. Furthermore, the studies created guidelines to be used during surgery or fixation and post-surgery shaping. The 3D models are created depending on the following key factors: the skill of the technicians in creating the 3D image file, the accuracy of the recording equipment, and the accuracy of the printer. In our view, the creation of 3D images is very necessary for medicine to facilitate the surgical process, however, at present, this model has not been particularly popular, especially in Asia. The current 3D printed models deployed in studies were largely outsourced, the 3D reconstructing image, landmark extractions, and measurements are all performed manually by professional staff. It is necessary to put new technologies into practice that reduce the amount of work for employees, in addition, to help to normalize measurements to avoid human measurement errors, especially reducing time and cost. Nowadays, software that reconstructs 3D from 2D images is also becoming more popular, but it often comes with expensive hardware compared to the digital camera. With the development of science and technology, machine learning algorithms gradually replace the hardware of complex collection systems. This also reduces investment costs for 3D devices that address a disadvantage of 3D, which was presented by [PERSON] et al. [112]. The 3D printer was applied in medical reconstructions, which was a potential development direction to improve the quality of healthcare, especially in the field of cosmetic surgery. 3D printed models used for medicine as a supported tool in surgery, medicine education, and patient communication. The 3D printed model could be used like a model to clinical diagnosis [98], a guide for surgery (Figure 2), or external nasal splint after rhinoplasty (Figure 3). To brief, in this paper, we surveyed studies that represent approaches from the authors in landmark extraction and their application.