Image conditions for machine-based face recognition of juvenile faces

Effect of distance education courses held in different environments on emotions of the instructor

In this study, the emotional states of the instructors who teach by distance education and the effect of the environment in which they give the lesson on their emotions were examined. Computer-aided "Facial Action Coding System" method was used to measure emotion values from facial images. Through the software developed by the researchers using the Microsoft Face Recognition API, 43292 facial images taken from five trainers during their training were analysed and seven basic emotions representing facial expressions were obtained numerically. As a result of the analysis, it was found that the emotions of the instructors that can be described as negative in the lessons held in the e-studio environment generally increased at the beginning of the lesson, decreased in the following minutes and increased again at the end of the lesson; On the other hand, it was determined that positive emotions decreased at the beginning of the lesson and increased later. In the home environment, while the emotions that can be described as negative at the beginning decreased, positive emotions increased. A significant difference was determined between home and e-studio environment in all emotions except anger. One of the emotions with a difference in value between the two environments is happiness, and it has been determined that happiness has higher values in the home environment. It has been determined that other emotions are experienced more in the e-studio environment. It is thought that the results of the study will contribute to the mental states of the instructors who teach through distance education and to the efficiency of distance education.

Correlation Between Maxillary Anterior Teeth and Common Facial Measurements

Background

The symmetry between maxillary anterior teeth and the face holds significant importance. This study assessed and analyzed the relationship between facial parameters and anterior teeth in the maxillary arch of male and female subjects. Specifically, individual width and combined width (CW) measurements of the maxillary anterior teeth were investigated.

Methods

This study involved a total of 150 dentate Yemeni subjects (74 men and 76 women), whose ages ranged from 18 years old to 30 years old. A maxillary cast was created, and two digital photographs of the face of each subject were taken and analyzed. Digital calipers and AutoCAD were used to gather measurement data of the dental parameters (intercanthal distance [ICD], interpupillary distance [IPD], interalar width [IAW], intercommissural width [ICW], and bizygomatic width [BZW]) and facial parameters (profile distance).

Results

Significant correlations were found for the following: IPD and width of six maxillary anterior teeth of each of the study subjects; ICD and their central incisors; and BZW and their canine width measurements. In contrast, IAW and ICW were not correlated with all tooth measurements. Linear regression findings showed that the CW measurement of the four incisors was significantly correlated with all facial parameter measurements, excluding the ICW and IAW in females and the IAW, ICW, and profile distance in males.

Conclusion

The IPD and ICD of males and females may be used to determine their CW measurements. The BZW and IPD of males can be used to take precise anthropological measurements of the width of the central canines and incisors. Meanwhile, the IPD distance of females can be used to assess the central and lateral incisor widths.

A guided manual method for juvenile age progression using digital images

Predicting the possible age-related changes to a child's face, age progression methods modify the shape, colour and texture of a facial image while retaining the identity of the individual. However, the techniques vary between different practitioners. This study combines different age progression techniques for juvenile subjects, various researches based on longitudinal radiographic data; physical anthropometric measurements of the head and face; and digital image measurements in pixels. Utilising 12 anthropometric measurements of the face, this study documents a new workflow for digital manual age progression. An inter-observer error study (n = 5) included the comparison of two age progressions of the same individual at different ages. The proposed age progression method recorded satisfactory levels of repeatability based on the 12 anthropometric measurements. Seven measurements achieved an error below 8.60%. Facial anthropometric measurements involving the nasion (n) and trichion (tr) showed the most inconsistency (14-34% difference between the practitioners). Overall, the horizontal measurements were more accurate than the vertical measurements. The age progression images were compared using a manual morphological method and machine-based face recognition. The confidence scores generated by the three different facial recognition APIs suggested the performance of any age progression not only varies between practitioners, but also between the Facial recognition systems. The suggested new workflow was able to guide the positioning of the facial features, but the process of age progression remains dependant on artistic interpretation.