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Currently, two-dimensional photographs are most commonly used to facilitate visualization, assessment and treatment of facial abnormalities in craniofacial care but are subject to errors because of perspective, projection, lack metric and 3-dimensional information. One can find in the literature a variety of methods to generate 3-dimensional facial...
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Context 1
... Retro-reflective markers visible on a photograph (Figure 1) but also accurately digitized by Microscribe's digitizer ( Figure 3) will be placed on the mannequin. ...
Context 2
... Microscribe 3Dx digitizer-probe (Immersion Corp.), our "gold standard", allows continuous scanning up to 90 points per second and point measurements with accuracy of 0.0228 mm (0.009") in a 50" sphere workspace (Figure 3). The reference frame (origin and two axes) and the units (mm) can be established by the user at the beginning of each session. ...
Context 3
... software produces a polygonal triangular mesh with texture coordinates and a combined texture image. The mannequin head modeled with this software using 6 different views is shown in Figure 3. To ensure that the imaging and digitizing systems shared the same origin coordinates and reference frame (XYZ), the calibration target used by Eyetronics was digitized and used as a reference frame for the digitizer. ...
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Citations
... For example, according to studies on cephalic index for head shape proportions, previous studies may generalize a Caucasian users as Dolichocephalic or Asian users as Brachycephalic, which is not the case. Critical literature assessed in determining the parameters presented in Fig 1, include comparisons in global head shape a size variation, methods for data capture in heads, cephalic head data studies, comparative studies for scalp cooling and more [9,10,11,12,13,14,15]. ...
... Photogrammetry a safe technique, not at all like laser scanning in which just class 1 and 2 type lasers are safe to use on human subjects. Analysts adjusted and institutionalized this system with the goal that specific anthropometric measurements could be estimated to a high level of precision like direct methods [60] [61]. The coordinates are evaluated as the points where the rays from camera position to landmark cross. ...
... Biological landmarks are standard reference significative points on the face, such as the nose tip, inner and outer corners of the eyes, corners of the mouth, and the chin point [9,10]. Landmark localisation is usually localised manually, but numerous research has been achieved on automatic accurate localisation. ...
Face recognition and gender classification are vital topics in the field of computer graphic and pattern recognition. We utilized ideas from two growing ideas in computer vision, which are biological landmarks and quasi-landmarks (dense mesh) to propose a novel approach to compare their performance in face recognition and gender classification. The experimental work is conducted on FRRGv2 dataset and acquired 98% and 94% face recognition accuracies using the quasi and biological landmarks respectively. The gender classification accuracies are 92% for quasi-landmarks and 90% for biological landmarks.
... Biological landmarks are standard reference significative points on the face, such as the nose tip, inner and outer corners of the eyes, corners of the mouth, and the chin point [9,10]. Landmark localisation is usually localised manually, but numerous research has been achieved on automatic accurate localisation. ...
Face recognition and gender classification are vital topics in the field of computer graphic and pattern recognition. We utilized ideas from two growing ideas in computer vision, which are biological landmarks and quasi-landmarks (dense mesh) to propose a novel approach to compare their performance in face recognition and gender classification. The experimental work is conducted on FRRGv2 dataset and acquired 98% and 94% face recognition accuracies using the quasi and biological landmarks respectively. The gender classification accuracies are 92% for quasi-landmarks and 90% for biological landmarks.
... In the retrieval and clustering from quantitative 3D human head shape data based on Caucasian CAESAR and Size China (shown in Figure 2 below), with approximately 2400 participants. Enciso et al [9] discusses 3D head anthropometric analysis where as Azouz et al [1] studies automatic locating of anthropometric landmarks on 3d human models. Asian users have often experienced poor fit in products used on the head. ...
... However, the information available to designers has traditionally been based on mainly western Caucasian data such as the research by Godil & Ressler [3], on the retrieval and clustering from a 3D human database based on body and head shape based on caucasian CAESAR data. Enciso et al [2] discusses 3D head anthropometric analysis where as Azouz et al [1] studies automatic locating of anthropometric landmarks on 3d human models. Asian users have often experienced poor fit in products used on the head. ...
... For instance, Edler et al. [7] studied facial attractiveness using 15 facial photographs of orthoganthic patients which were taken by the same medical photographer and the landmarks were marked manually on the photographs. In a research on a 3D head anthropometric analysis [8], the 3D images were acquired by using Eyetronics, a light-based imaging system which consists of a regular slide projector, a digital camera, and a calibration pattern. Landmarks were pre-labelled on a mannequin head by placing a small triangle, red-colored paper with a blue dot on the landmarks' location. ...
Abstract Background Indirect anthropometry (IA) is one of the craniofacial anthropometry methods to perform the measurements on the digital facial images. In order to get the linear measurements, a few definable points on the structures of individual facial images have to be plotted as landmark points. Currently, most anthropometric studies use landmark points that are manually plotted on a 3D facial image by the examiner. This method is time-consuming and leads to human biases, which will vary from intra-examiners to inter-examiners when involving large data sets. Biased judgment also leads to a wider gap in measurement error. Thus, this work aims to automate the process of landmarks detection to help in enhancing the accuracy of measurement. In this work, automated craniofacial landmarks (ACL) on a 3D facial image system was developed using geometry characteristics information to identify the nasion (n), pronasale (prn), subnasale (sn), alare (al), labiale superius (ls), stomion (sto), labiale inferius (li), and chelion (ch). These landmarks were detected on the 3D facial image in .obj file format. The IA was also performed by manually plotting the craniofacial landmarks using Mirror software. In both methods, once all landmarks were detected, the eight linear measurements were then extracted. Paired t-test was performed to check the validity of ACL (i) between the subjects and (ii) between the two methods, by comparing the linear measurements extracted from both ACL and AI. The tests were performed on 60 subjects (30 males and 30 females). Results The results on the validity of the ACL against IA between the subjects show accurate detection of n, sn, prn, sto, ls and li landmarks. The paired t-test showed that the seven linear measurements were statistically significant when p
... • Biological or Anthropometric landmarks, which are often used by scientists and physicians, are meaningful points that are defined as standard reference points on the face and head, such as the nasion, inner and outer canthi of the eyes, pronasale, subnasale, center of the upper lip, center of the lower lip, outer corners of the mouth (cheilions), and a chin point (pogonion) [92,123]. • Mathematical landmarks which are defined according to certain mathematical or geometric properties of human faces, such as the middle point between two biological landmarks [190]. ...
... Many of these methods are based on image recognition and image processing. There are divided for two general branches: two-dimensional and 3D data collection [3][4][5]. Two-dimensional methods are limited by lack of some information (no depth data or only predicted values). However some of the applications can successfully adopt them (i.e. ...
... The results obtained assured accuracy to within 0.93 mm, precision to within 0.79 mm and reliability to within 0.2 mm. Another similar study conducted by Enciso et al. [15] focused on the development of indirect 3D landmark location and measurement of facial soft-tissue with the structured-light technique. Indirect anthropometric measurements included 25 linear distances currently used in anthropometry and based on Farkas' work. ...
In the last years close-range photogrammetric scanning systems are acquiring a larger market share. This is due to low-cost hardware components and to new user-friendly software. The ultimate photogrammetric 3D scanning systems are very accurate and precise because of the highresolution cameras (over 10 Mpixels) they are equipped of and the more precise algorithms of their software.
The calibration phase is the primary step for the development of a precise photogrammetric scanner.
Through a good calibration it is indeed possible to eliminate optical aberration issues and to obtain
precise and accurate three-dimensional measurements. In this study a powerful calibration method,
named full-field calibration, was implemented to obtain high-precision values, using an original threedimensional calibrator , developed so as to increase the performance of this type of calibration.
Prior to using any measurement or 3D scanning system, precision and accuracy have to be assessed. In
this study a robust validation method for photogrammetric scanning systems has been proposed. The validation procedure consisted in: 1) operator error analysis, 2) reproducibility error-analysis, 3) control-system error analysis, 4) scanning system error analysis.
The measurements taken using the "control system" (certified equipment in terms of precision and accuracy) were considered as "gold standard". The photogrammetric measurements, subsequently obtained by the scanning system, were aligned to the "gold standard" using Procrustes registration.
The system error was expressed as the displacement between these two sets of measurements.
