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Articles

A method for increasing 3D body scanning’s precision: Gryphon and consecutive scanning

ORCID Icon, ORCID Icon, , ORCID Icon &
Pages 39-59 | Received 06 Jul 2020, Accepted 12 May 2021, Published online: 01 Jun 2021

Figures & data

Figure 1. Accuracy and precision’s relationship in body scanning measurements.

Four woman’s outlines measuring the hip-height, showing how accuracy and precision are related, but different terms in anthropometry. Four boxes, each containing a woman showing five scans measuring her hip-height. Box one shows high accuracy and low precision, with five scans at varying height, with the average resting at the correct hip height. Box two shows high accuracy and high precision, with five scans at the same height, with the average resting at the correct hip height. Box three shows low accuracy and low precision, with five scans at varying height, with the average resting above the correct hip height. Box four shows low accuracy and high precision, with five scans at the same height, with the average resting above the correct hip height.
Figure 1. Accuracy and precision’s relationship in body scanning measurements.

Figure 2. Study tree. Assets from Muammark (Citation2017).

A flow diagram showing how the study treats humans and body forms. Humans are allocated at random to be consecutively or non-consecutively scanned. Body forms are just scanned consecutively.
Figure 2. Study tree. Assets from Muammark (Citation2017).

Figure 3. Illustration of the outlier removal process. Solid circles represent the five data points in the set. The solid blue line represents the median of the set. Dashed red box illustrates the symmetric window with the red data points included in the reduced set and the black points excluded.

Figure 3. Illustration of the outlier removal process. Solid circles represent the five data points in the set. The solid blue line represents the median of the set. Dashed red box illustrates the symmetric window with the red data points included in the reduced set and the black points excluded.

Figure 4. Percentage of all measurements suitable for garment development; Precision = 3σ.

Figure 4. Percentage of all measurements suitable for garment development; Precision = 3σ.

Figure 5. Gryphon + five Consecutive Scans against ANSUR I and II’s Allowable Errors.

Figure 5. Gryphon + five Consecutive Scans against ANSUR I and II’s Allowable Errors.

Table 1. MANOVA, consecutive and non-consecutive precision differences categorised by their importance to garment development.

Table 2. MANOVA: Human and Body Form reliability differences categorised by their importance to garment development.

Figure 6. A flow chart of Gryphon scanning process.

A flow chart with five boxes representing the Gryphon scanning process, taking five consecutive scans before running the Gryphon software. A flow chart with five boxes representing the Gryphon scanning process. First, use Gill et al.’s (2016) standard Body Scanning protocol. Second, the scan software captures five consecutive scans. Third, software applies Gryphon to remove two measurements. Four, software averages the remaining three measurements. Five, the software determines a precise anthropometric measurement.
Figure 6. A flow chart of Gryphon scanning process.

Table A1. Body scanning precision (cm) of all investigated scan methods to 3 standard deviation, representing 99.73% of all attainable measurements.

Table B1. Definition of measurement definitions used in our study (Sizestream Citation2019).