ISO 17097:2024

International
Standard
ISO 17097
First edition
3-D human body scan data —
2024-05
Methods for the processing of
human body scan data
Données de numérisation 3D du corps humain — Méthodes relatives
au traitement des données de numérisation du corps humain
Reference number
© ISO 2024
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ii
Contents Page
Foreword .iv
Introduction .v
1 Scope . 1
2 Normative references . 1
3 Terms and definitions . 1
3.1 3-D anthropometry .1
3.2 3-D scan data .2
3.3 Processing of 3-D human scan data .4
4 Methods for point-cloud processing . 4
4.1 General .4
4.2 Registration .5
4.3 Merging .6
4.4 Denoising (noise removal) .6
4.5 Adjustment of point-cloud resolution .7
4.6 Meshing .7
4.7 Texture mapping .8
4.8 Saving of mesh .8
5 Methods for mesh processing . 8
5.1 General .8
5.2 Editing of mesh .10
5.2.1 Merging .10
5.2.2 Hole-filling .10
5.2.3 Smoothing .11
5.3 Adjustment of mesh resolution . 12
5.3.1 Mesh subdivision. 12
5.3.2 Decimation (mesh downsampling) . 13
5.3.3 Remesh (mesh optimization) . . 13
5.4 Landmarking for mesh alignment .14
5.5 Alignment of mesh coordinates .14
5.6 Template matching (mesh parameterization) . 15
Bibliography .16

iii
Foreword
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Anthropometry and biomechanics.
Any feedback or questions on this document should be directed to the user’s national standards body. A
complete listing of these bodies can be found at www.iso.org/members.html.

iv
Introduction
Three-dimensional (3-D) human body scan data are the digitized 3-D shape information of the human body
in the form of a point cloud. 3-D body scanners or 3-D image-capturing systems are used to obtain these
data. The collected 3-D point-cloud data are processed using 3-D scan data processing software and then
used for anthropometric measurement, body shape analysis and ergonomic product design.
Knowledge and experience in the processing and analysis of 3-D point-cloud and mesh are required to
improve the quality of human body scan data while maintaining their morphological characteristics for their
application to the design of a particular product, workplace or system. Custom software can be developed to
support the processing of human body scan data by incorporating terms, methods and considerations in this
document in a selective manner.
This document is intended to be used by software developers during the development of scan data processing
software. It could also be helpful for anthropometric researchers and product designers when they establish
3-D human body scan databases to analyse human body shape and size. A 3-D human body scan database
could benefit manufacturers, customers and employees by developing products, workplaces and systems
with better fit, comfort and usability.
The purpose of this document is to enhance the utilization of 3-D human body scan data through appropriate
processing. It is further intended to improve the accuracy and reliability of analysis of 3-D human body scan data.

v
International Standard ISO 17097:2024(en)
3-D human body scan data — Methods for the processing of
human body scan data
1 Scope
This document specifies methods for the processing of human body scan data acquired using a 3-D body
scanner.
2 Normative references
The following documents are referred to in the text in such a way that some or all of their content constitutes
requirements of this document. For dated references, only the edition cited applies. For undated references,
the latest edition of the referenced document (including any amendments) applies.
ISO 7250-1, Basic human body measurements for technological design — Part 1: Body measurement definitions
and landmarks
3 Terms and definitions
For the purposes of this document, the terms and definitions given in ISO 7250-1 and the following apply.
ISO and IEC maintain terminology databases for use in standardization at the following addresses:
— ISO Online browsing platform: available at https:// www .iso .org/ obp
— IEC Electropedia: available at https:// www .electropedia .org/
3.1 3-D anthropometry
3.1.1
3-D body scanner
hardware and software system that creates data representing a human form, or parts thereof, in three
dimensions
[SOURCE: ISO 20685-1:2018, 3.2, modified — “creates digital data” has been replaced by “creates data” in
the definition.]
3.1.2
3-D scanner hardware
physical components of a 3-D body scanner and any associated computer(s)
[SOURCE: ISO 20685-1:2018, 3.4]
3.1.3
3-D scanner software
operating system, user interface, programs, algorithms and instructions associated with a 3-D scanning system
[SOURCE: ISO 20685-1:2018, 3.3]
3.1.4
anatomical landmark
point clearly defined on the body that can be used for defining anthropometric measurements
[SOURCE: ISO 20685-1:2018, 3.6]

3.2 3-D scan data
3.2.1
3-D scan data
collection of the coordinate values of either 3-D points or the connection information of the 3-D points, or both
3.2.2
x, y, z coordinate system
axis system
system for measuring the body with respect to the standing or sitting human where x, y and z refer to the fore-
and-aft direction (the sagittal axis), the side-to-side direction (the transverse axis) and the top-to-bottom
direction (the longitudinal axis), respectively
[SOURCE: ISO 20685-1:2018, 3.13, modified — the content of the definition has been restructured and Note
1 to entry has been removed.]
3.2.3
point cloud
collection of 3-D points in space referenced by their coordinate values
Note 1 to entry: See Table 1.
Table 1 — Point cloud consisting of n 3-D points
Column 1 Column 2 Column 3
Point index
(x-coordinate) ( y-coordinate) (z-coordinate)
1 2,56 −21,94 91,31
2 2,69 −20,89 90,01
3 2,11 −22,83 92,84
⋮ ⋮ ⋮ ⋮
n − 2 −28,57 −17,08 −27,89
n − 1 −9,69 −19,81 −29,03
n −19,92 −9,61 −33,74
[SOURCE: ISO 20685-1:2018, 3.9, modified — Note 1 to entry has been replaced and Table 1 has been added.]
3.2.4
texture
visual information of colour in 3-D scan data
Note 1 to entry: The texture of each point is expressed as a value between 0 and 255 for the individual colours of red,
green and blue, as shown in Table 2, in the .ply file format.
Table 2 — Point cloud consisting of n points with texture information
Point Column 1 Column 2 Column 3 Column 4 Column 5 Column 6
index (x-coordinate) ( y-coordinate) (z-coordinate) (red) (green) (blue)
1 2,56 −21,94 91,31 127 127 127
2 2,69 −20,89 90,01 123 133 138
3 2,11 −22,83 92,84 92 97 215
⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮
n − 2 −28,57 −17,08 -27,89 238 200 210
n − 1 −9,69 −19,81 -29,03 255 230 243
n −19,92 −9,61 -33,74 255 255 255

3.2.5
vertex
node
intersection of two or more lines, curves or edges
3.2.6
triangle face
surface (face) created by connecting three adjacent vertices
3.2.7
mesh
surface consisting of a set of vertices, edges and faces that define the shape of an object
Note 1 to entry: A triangular mesh consisting of a set of triangle faces (each of which is defined by the indices of three
vertices, as shown in Table 3) is used to construct the 3-D digital form of the human body, as shown in Figure 1.
Table 3 — 3-D scan data presented by a triangular mesh with m triangle faces
Column 1 Column 2 Column 3
Triangle face index (point index of (point index of (point index of
the first vertex) the second vertex) the third vertex)
1 1 2 3
2 1 2 4
3 1 3 5
⋮ ⋮ ⋮ ⋮
m − 2 8 345 8 346 8 347
m − 1 8 347 8 348 8 349
m 8 347 8 348 8 350
Key
1 vertex
2 triangle face
Figure 1 — 3-D human scan data in triangle faces

3.3 Processing of 3-D human scan data
3.3.1
point-cloud processing
manipulation of point cloud and texture data acquired by 3-D scanner hardware by applying operations
such as merging, noise removal, meshing, resolution adjustment and texture mapping
3.3.2
mesh processing
manipulation of a mesh by applying operations such as hole filling, merging, smoothing, mesh subdivision,
decimation, remesh, landmarking, alignment and template matching
3.3.3
resolution
density of vertices and triangle faces that consist of 3-D scan data
4 Methods for point-cloud processing
4.1 General
A point cloud obtained by scanning the human body shall be processed by one or more of the following
[11],[17],[19],[40],[46]
operations:
— registration (4.2);
— merging (4.3);
— denoising (4.4);
— adjustment of point-cloud resolution (4.5);
— meshing (4.6);
— texture mapping (4.7);
— saving of mesh (4.8).
NOTE The point-cloud processing operations are performed automatically or semi-automatically by 3-D scanner
software or manually by using 3-D scan data processing software while following a general procedure of point-cloud
processing, as shown in Figure 2.

Figure 2 — General procedure of point-cloud processing
4.2 Registration
When a 3-D body scanner consisting of two or more cameras captures the human body from different angles
simultaneously, sets of point-cloud data obtained from the different cameras shall be registered based on
[25],[28],[40],[44]
one or more areas in common.
NOTE 1 A 3-D body scanner consisting of multiple cameras generally requires calibration for automatic registration
of point-cloud sets, which are captured from different angles.
NOTE 2 If point-cloud sets are separated from each other, a manual registration function provided by 3-D scanner
software can be used to make point-cloud sets appropriately aligned through manually determining pairs of the
corresponding areas (see Figure 3).

Figure 3 — Manual registration of point-cloud sets
NOTE 3 An inaccurate registration can occur if common areas of point-cloud sets are morphologically unequal,
which is caused by breathing or postural change. In these cases, a non-rigid registration can be applied to match point-
[19],[40]
cloud sets precisely by adjusting the location of vertices.
4.3 Merging
The sets of registered point-cloud data should be combined into a single point-cloud set for further processing
[19],[35]
steps.
4.4 Denoising (noise removal)
Points that are not part of the human body but are included during the process of human body scanning
[19],[31]
shall be removed.
NOTE 1 Noise in 3-D scan data can be caused either by a poor quality imaging system (e.g. low resolution of 3-D
scanner hardware, improper focal length, inappropriate calibration) or by environmental interference during the
image-capturing process (e.g. light intensity), or both.
NOTE 2 Denoising function with parameters (e.g. denoise method, denoising intensity, iteration of denoising
process) provided by 3-D scanner software is used to filter noise. The effect of noise can be recognized once point-
cloud data has meshed in consequence. If the resulting mesh shows an unclean surface partly or overall, denoising
with adjusted parameters can be applied until an improved mesh is obtained.
If noise in the point-cloud data of the human body is not properly removed, the surface of the corresponding
mesh can have many significant irregularities, as shown in Figure 4. If significant noise occurs repeatedly,
then the focal length of either the scanner’s lenses or the light intensity, or both, should be checked and the
scanner should be recalibrated if needed.

Figure 4 — An inappropriate scan result with significant noise
4.5 Adjustment of point-cloud resolution
The resolution of point-cloud data should be adjusted by controlling the number of points in the point-cloud
data. The 3-D scanning system adjusts the number of points that constitute the surface of the scanned object
so that the spacing between the vertices is kept within a designated range of distance (e.g. 1 mm to 2 mm).
NOTE 1 A resolution adjustment function with parameters (e.g. average distance between vertices, target number
of vertices) provided by 3-D scanner software is used to change the density of the point cloud.
NOTE 2 When the density of a point cloud is high, the resolution of the point cloud can be reduced to keep a smaller
number of points. A lower density of a point cloud enables faster data processing and analysis.
NOTE 3 The resolution of a 3-D sc
...