A Non-Photorealistic Rendering Technique for Art-directed Hatching of
3D Point Clouds
Ronja Wagner, Ole Wegen
, Daniel Limberger
, J
urgen D
ollner and Matthias Trapp
Hasso Plattner Institute, Faculty of Digital Engineering, University of Potsdam, Germany
3D Point Clouds, Non-photorealistic Rendering, Real-time Rendering, Art-directed.
Point clouds or point-based geometry of varying density can nowadays be easily acquired using
or modern smartphones with
sensors. We demonstrate how this data can be used directly to create novel
artistic digital content using Non-Photorealistic Rendering techniques. We introduce a
-based technique
for art-directable
rendering of 3D point clouds at interactive frame-rates. The technique uses either a
subset or all of the points to generate oriented, sketchy strokes by taking local curvature and normal information
into account. It uses X-Toon textures as part of its parameterization, supports hatching and cross hatching, and
is inherently temporal coherent with respect to virtual camera movements. This introduces significant artistic
freedom that is underlined by our results, which show that a variety of different sketchy styles such as colored
crayons, pencil, pointillism, wax crayons, blue print, and chalk-drawings can be achieved on a wide spectrum
of point clouds, i.e., covering 3D polygonal meshes as well as iPad-based LiDAR scans.
Point clouds are a simple, compact, and flexible geo-
metric representation that can easily be acquired for
real-world scenes using off-the-shelf photogrammet-
ric techniques. With the introduction of Light Detec-
tion And Ranging (
) sensors in high-end smart-
phones, e.g., iPhone 12, straightforward acquisition of
point clouds is easily accessible to consumers.
Despite both its potential applicability in various
domains and increasing popularity in social media—
mainly for 3D photography and animation with the
point cloud as an art style in itself— their usage
as a fundamental geometric representation in Non-
Photorealistic Rendering (
) as well as respective
rendering systems or frameworks are sparsely stud-
ied. Notable uses of 3D point clouds are (1) to enable
light transport for rendering scanned assets (Sabbadin
et al., 2019), (2) stylized, interactive self portraits, (3)
data visualization, as well as (4) art-directed particle
animation and stylization such as the reprojection of
recorded memories in the computer game Cyberpunk
2077 (Ankermann et al., 2021) as a means of distin-
guishing between reality and virtual reality. Another
noteworthy use can be found in previsualization or
(a) Blue Print (b) Pencil
(c) Colored Crayons (d) Wax Crayons
(a) Blue Print (b) Pencil
(c) Colored Crayons (d) Wax Crayons
(a) Blue Print (b) Pencil
(c) Colored Crayons (d) Wax Crayons
Figure 1: The Stanford dragon as 3D point cloud, rendered
in four different styles using art-direct hatching.
digital content creation to evaluate ideas and concepts
early before performing possibly costly data enhance-
ment or transformation, e.g., creating stylized, textured
3D meshes. We present a first approach into this do-
main by researching methods to enable art-directed
procedural-controlled rendering effects.
Wagner, R., Wegen, O., Limberger, D., Döllner, J. and Trapp, M.
A Non-Photorealistic Rendering Technique for Art-directed Hatching of 3D Point Clouds.
DOI: 10.5220/0010849500003124
In Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 1: GRAPP, pages
ISBN: 978-989-758-555-5; ISSN: 2184-4321
2022 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
In the context of
, point clouds have both ad-
vantages and disadvantages over traditional 3D polyg-
onal models. Point clouds lack inherent connectiv-
ity information that needs to be respected or main-
tained, which simplifies their representation, transfor-
mation, and rendering. The absence of surface-related
attributes such as normal vectors, texture coordinates,
or curvature data is rather inconvenient, since they are
essential for the implementation of
Additionally, while high quality renderings of point
clouds are possible (Sch
utz and Wimmer, 2015; Sch
et al., 2021), they often rely on a sufficient point den-
sity. With these observations in mind, enabling the
implementation of real-time, art-directed
niques comprises the following major challenges:
Art-directable Parametrization (C
of processing operations that are required for
different manifestations of stylization techniques,
e.g., point-splat functions (Anjos et al., 2018), to
facilitate the interchange of respective techniques
and increasing ease-of-use.
Efficient Data Handling (C
An efficient represen-
tation of complex point clouds and respective styl-
ization data to allow for art-directed stylization
based on point-attribute data. This also concerns
the reduction of data transfer and update latency to
support real-time rendering for interactive control.
Existing approaches to implement animation tech-
niques for point clouds are (1) customized integration
into existing game engines (to enable real-time render-
ing) or (2) specific tooling or scripts to extend existing
software, e.g., Blender. These, however, either re-
quire auxiliary constructs for data representation, e.g.,
texture-based representations, lack real-time rendering
capabilities, or can hardly handle millions of points.
In the context of the challenges
, we
present a Graphics Processing Unit (
hatching technique for producing art-directed non-
photorealistic renderings of potentially massive point
clouds, which are obtained either using
ning of a real-world scene or by sampling polygonal
geometry. The presented approach is not limited to
hatching, but can serve as a general approach for the
implementation of further non-photorealistic rendering
techniques for point clouds.
To this end, we. . .
. . . introduce a method for creating sketched im-
ages directly out of 3D point clouds using only
position, normal, and curvature information,
enable significant artistic freedom due to wide
range of parameters by using X-Toon textures, and
demonstrate the method’s real-time capability (pre-
computed attributes) and temporal coherence.
Prior art with respect to texture-based stylization in 3D
object space using, e.g., proxy-geometry as well as in
image space remains quite popular and is well covered.
In the following, we briefly classify an exemplary cross
section of classics as well as latest works.
rendering of 3D polygonal meshes targeting
a sketched look and feel can be easily achieved us-
ing texture-based hatching approaches (Praun et al.,
2001; Webb et al., 2002). Hatching patterns are pre-
generated in multiple levels of details, i.e., Tonal Art
Maps, and enable fine control over shading without
aliasing. In order to also create sketchy outlines
or silhouettes, image-based approaches can be ap-
plied (Nienhaus and D
ollner, 2003; Zakaria and Seidel,
2004). These types of techniques, however, cannot be
applied to point clouds, since texturing and image-
based post processing is implemented fundamentally
different; Strokes are placed directly and individually,
and require a dedicated level of detail concept. In ad-
dition, image-based curvature estimates (Kim et al.,
2008) and purely image-based stippling (Awano et al.,
2010) are not applicable and, regardless, usually lead
to temporal incoherent results.
Another common approach for simulating, e.g.,
pencil-like renderings, is to use edges of the 3D meshes
to create overlapping graphite strokes (Sousa and
Buchanan, 1999). This concept of creating textured
proxy geometry, also sometimes referred to as graph-
tals (Smith, 1984), facilitates temporal frame-to-frame
coherence and can be applied to particles and point
clouds alike (Kaplan et al., 2000; Markosian et al.,
2000). The proxy geometry, e.g., dots or strokes, can
be specialized dynamically at run-time w.r.t. size, ori-
entation, placement, and color. Thereby, artistic con-
trol can be linked to mesh properties and thus allow
for silhouettes and contouring (Grabli et al., 2004).
This approach represents the core of our technique
and, apart from various differences in the implementa-
tion details due to the evolution of graphic hardware,
can be easily extend, enhanced, and specialized for
point clouds.
A promising extension to this are ribbons, i.e., one-
dimensional strips of points, ordered “according to
their neighbourhood relations” (Runions et al., 2007).
The concept could be used to create silhouette or cur-
vature aware proxy geometry (Schmid et al., 2011)
such as strokes consisting of multiple links instead of
single, straight ones, and might allow for fine-grained
stippling styles. So far, existing approaches covering
water color, caligraphy, etc. still rely on strokes drawn
by the artist (Zheng et al., 2017). Automatic splatting
of lines or strokes, though applicable to volumetric
A Non-Photorealistic Rendering Technique for Art-directed Hatching of 3D Point Clouds
(a) Pencil. (b) Wax crayon. (c) Two-colored.
Figure 2: Shading effects and their corresponding X-Toon
textures (RGBA). Note that the y-axis is not utilized here.
data as well, does only cover a specific style and is not
easily art-directable (Zhang et al., 2014; Anjos et al.,
2018). We partially combine these ideas and aim for
an automated approach that allows for a constrained
but artist-directable, expressive stylization.
This section details concepts as well as implementation
details of our real-time hatching technique.
3.1 Art-directed Parametrization
We make the assumption that any point cloud is given
with point normal vectors (Cao et al., 2021), color, and
curvature attributes (M
erigot et al., 2009; Lu et al.,
2020). The latter two can improve the appearance but
are not required. To achieve the desired hatching effect,
each point is replaced by textured proxy geometry, e.g.,
two orthogonal lines aligned to the surface, textured
with pencil strokes.
A drawing technique that characterizes cross-
hatching is to depict lighting by not only using dif-
ferent colors but also by omitting lines and therefore
showing the underlying paper. The amount of light
that reaches a point defines how likely it is to be omit-
ted. To accomplish a wide variety of artistic styles and
effects, the color and point density for each amount
of light can be controlled through the alpha channel
of an X-Toon (Barla et al., 2006; Kang et al., 2009)
texture (Fig. 2). On white paper for example, strongly
illuminated parts are realized by removing most points,
while darker parts keep their original point density. An-
other option (better suited to darker backgrounds) is
to color well-lit points brightly and leave out points
receiving a medium amount of light.
Lighting by omission only works if there are no
visible parts behind the points that are left out. To
avoid such parts, e.g., the back of the model, from
appearing where only the paper should be visible, we
use an additional depth pass. With that pass we ensure
that nothing behind the surface of the model is visible
in the final result.
For a more realistic pencil effect there is also the
option to limit the stroke colors to a number of pre-
defined pencil colors, similar to a colored pencil set.
In addition to the classic X-Toon parametrization, the
following parameters are provided for hatching:
Line Length and Thickness:
These parameters con-
trol the extent of hatching strokes.
Parallel to cross-hatch Proportion:
Our technique
supports both cross hatching, where almost all
points are replaced with two lines, and parallel
hatching, where all points are replaced with a sin-
gle line. This parameter specifies the probability
for a point to be replaced with a single stroke or
two, crossed strokes.
Stroke Density:
In point clouds of high density, the
individual hatched strokes might not be distinguish-
able from each other. By specifying the proportion
of strokes to be left out, the density of rendered
strokes can be controlled.
Line Direction:
This parameter is used to determine
the direction of each stroke.
Light Direction:
For lighting we use a uniform light
direction that is specified by this parameter.
Coloring Mode:
Defines which method is to be used
for determining the color of the hatched strokes.
Hue Shift:
Is applied to the color calculated with the
selected coloring mode.
3.2 Stroke Generation for Hatching
X-Toon Coordinate Computation.
To determine
the desired density and therefore the proportion of
points to be omitted, we first compute the X-Toon
texture coordinates, namely depth and brightness, for
a point. Transforming the point’s z-coordinate (af-
ter projection) into a
range yields the depth co-
ordinate. The brightness coordinate depends on the
scene lighting implementation, e.g., Phong-based light-
ing (Phong, 1975). With these coordinates and the
corresponding texture value, we determine whether
the current point should be discarded or replaced by
lines, and in the latter case, obtain the color of these
Probabilistic Interpolation.
Both lighting by omis-
sion and the pencil color quantization rely on a proba-
bilistic approach. Instead of interpolating between two
values (e.g., visible and not visible or two RGB val-
ues) and applying the result, the point only attains one
of the values chosen at random with the interpolation
factor determining the probabilities. With a sufficient
number of points, the result creates an approximate
GRAPP 2022 - 17th International Conference on Computer Graphics Theory and Applications
(b) Irregular Stroke Placement(a) Regular Stroke Placement
Figure 3: For hatching, one or more strokes, i.e., two for
cross-hatching, can be placed and oriented either in a (a) reg-
ular more accurate or (b) irregular and scattered way.
impression of directly interpolated values. As random
seed, we use the point ID, which is temporally consis-
tent. For determining whether a point should be visible
or not, we use the alpha value from the X-Toon texture
as the interpolation factor between visibility and invis-
ibility. So if
a [0;1]
is the alpha value, the point has
100 · a%
chance of being visible. The general point
density can be controlled through a corresponding pa-
rameter that we multiply with the alpha value from the
X-Toon texture.
Line Geometry Generation.
For the cross hatch-
ing effect we replace each point with two orthogonal
lines perpendicular to the point’s normal. In doing so,
we need to ensure the line directions are consistent
for all points. Line directions are consistent if points
with similar normal vectors produce similar line direc-
tions (Fig. 3) so that they properly illustrate the surface
direction. To achieve that consistency we project a nor-
malized uniform vector on the plane defined by each
point normal. Let
be the uniform vector and
be the
surface normal. The projected vector
is computed
as follows:
= ~u (~u ·~n) ·~n
. The second direction
can be determined by simply computing the nor-
malized cross product of the first direction and the
point normal:
=~n ×
. With these directions, we
can now create two orthogonal lines along the surface.
be the point coordinates and
be the line length
parameter. Then the first line extends from
p +
. The second line starts at
and ends at
p +
. We can now use these coordinates to create
rectangle geometry for each line. One side of said rect-
angle is described by the corresponding line direction
and length. The direction of the other side needs to
be orthogonal to both the line direction and the vector
from the camera to the current point and can therefore
be calculated by taking their cross product. The width
of the line is defined in a separate line thickness pa-
rameter. From this information, we can derive the four
vertices of the resulting rectangle, with the texture co-
for the pencil
stroke texture.
3.3 Local Shading Models
There are three ways to determine the color of the
created pencil strokes. The simplest one is to apply
the same color to all strokes, which can, for example,
be used to create a classic gray pencil sketch or a blue
ballpoint pen drawing. Alternatively, the color can
be taken directly from the X-Toon texture. The third
approach is to blend the initial point color with the
X-Toon texture value to depict both lighting and the
original color information.
After the point color is determined, it is possible to
add pencil color quantization. That means only allow-
ing colors from a predefined set to simulate drawing
with pencils from a limited pencil box. Unlike other
media, pencil colors can only be mixed to a limited
extent. With watercolors for example, three colors and
black and white are in theory sufficient to get every
other color. For colored pencils however, you need
more base colors to illustrate the whole color spec-
trum properly. This is because generally, the quality
of the blending result of two pencil colors suffers with
decreasing similarity of the blended colors.
Our pencil color effect simulates that by calcu-
lating the two closest colors from a predetermined
pencil set to a given color and blending them with
probabilistic interpolation. We call the given color
. The pencil color set is given as rgb and hsv val-
ues sorted by hue. It contains only colors with high
saturation and value. First, we calculate the hsv rep-
resentation of
and apply the hue shift parameter.
We can then search for the colors
from the
pencil set whose hues are closest to
s hue, so that
) = hue(c
)· a + hue(c
)· (1 a)
applies for an
a [0,1]
. We can use this
as an interpolation factor
for probabilistic interpolation to create the impression
of a color with the same hue as
. Finally, we mix the
resulting color with black and white to more closely
match c
in value and saturation.
(a) (b) (c)
Figure 4: The point sprites used during the depth pass
cause discontinuities in the z-buffer which interfere with the
strokes rendered later (a). In addition, the semi-transparent
strokes interfere with one another (b). By shifting the strokes
towards the virtual camera using polygon offsets while using
order-independent rendering (blending or alpha to coverage)
both effects can be circumvented respectively (c).
A Non-Photorealistic Rendering Technique for Art-directed Hatching of 3D Point Clouds
3.4 Depth Pass
For the lighting by omission approach to work, we
need to ensure there are no visible lines behind the
points that are omitted. A first approach to that prob-
lem is back face culling, which prevents the back of the
surface from being visible. However, even with back
face culling, there still are lines behind the surface that
are not supposed to be visible (Fig. 6). We prevent
that by using an additional rendering pass before the
hatching pass.
In the depth pass, we render every point as a single
circle and write only to the depth buffer. With a suffi-
cient point density and point size, these circles cover
the whole surface, so in the following hatching pass,
only lines in front of the surface get rendered. Without
any modifications however, the circles of the points at
the front will cover the pencil strokes of nearby points.
To avoid that problem, we add an offset to the poly-
gons in the hatching pass, so the pencil strokes are
slightly in front of their corresponding points from the
depth pass (Fig. 4 a). Since the depth test needs to be
activated in the drawing pass for this approach to work,
we need to make sure nothing is written to the depth
buffer in the hatching pass, otherwise the lines will
cover each other instead of overlapping and thereby
creating darker tones (Fig. 4 b).
The size of the circles is also controllable via a pa-
rameter and needs to be adapted to achieve the desired
result in the depth pass and to not cover too much or
to little of the hatched lines.
3.5 Enhancements
The approach described so far allows for decent results,
though the following tweaks should be considered.
Alpha Modification.
So far, we use the approach
of probabilistic interpolation to create the impression
of the surface being transparent. However, for image
regions with almost full transparency, this results in
very few strong strokes on an otherwise clear part
of the surface, when in an actual pencil sketch, you
would also adjust the pressure of the pencil to modify
the transparency of the strokes themselves. That is
(a) Points (b) W/o alignment (c) With alignment
Figure 5: The length of strokes can be aligned based on the
local curvature at the stroke’s location. This can be used to
achieve (b) increased sketchiness especially in curved areas
as well as (c) a strict, more accurate hatching.
why we adjust the alpha value of the generated pencil
stroke proportional to the alpha value from the X-Toon
texture. Also, even in parts with similar lighting, not
every stroke is applied with exactly the same pressure.
To account for that, we apply some randomness on the
final alpha value.
Interpolation of Cross & Parallel Hatches.
In ad-
dition to a decreased stroke strength, another technique
to convey higher transparency is to use fewer lines by
transitioning from cross hatching to parallel hatching.
We implement this approach by using the alpha value
from the X-Toon texture as the probability for replac-
ing a point with a cross instead of a line. We multiply
that probability by a parameter
h [0,1]
, allowing us
to influence the proportion of cross-hatched to parallel-
hatched points. This parameter also makes it possible
to create results that exclusively use parallel hatching.
Curvature-controlled Line-length.
So far, we re-
place each point with equally long, straight lines. Put
together, they already create a good illustration of
curved surfaces because the lines are short enough
that they are a good approximation of the direction of
the surface below them. On areas of high curvature
on the other hand, the surface direction changes faster.
That means a line that is as long as the lines on low-
curvature areas is not a good surface approximation
anymore. With curvature information at each point,
we can align for that by decreasing the length of lines
in high-curvature areas (Fig. 5). In addition to line
length modification through curvature, we also modify
the line length with a randomness factor to account for
the differences in line length when drawing by hand.
This section present and discusses various application
examples achieved by using our art-directable render-
ing technique.
Application Examples.
Fig. 7 shows an overview
of different point cloud stylization variants obtained
by our technique. The variety covers a range from
blueprint rendering, gray-scale charcoal and ballpoint
pens to classic pencil drawing or pointillism. Our
technique allows for modification of all provided styl-
ization parameters and presents them interactively to
support the demands of artists.
Performance Considerations.
We tested the ren-
dering performance of a prototypical implementation
GRAPP 2022 - 17th International Conference on Computer Graphics Theory and Applications
(a) Naive Rendering (b) Back Face enabled (c) Depth Pass enabled (d) Difference of (b) and (c)
Figure 6: The Stanford dragon rendered as 3D point cloud (a) without back face culling, (b) with back face culling, and (c) with
an additional depth pass. Points—or strokes—that are hidden due to the depth pass are highlighted in red in (d).
using three point clouds of different complexity rang-
ing from approx. 3.5 million points (LiDAR, Statue)
over 5.7 million points to 11 million points (Angel
statue, sampled 3D mesh). The first point cloud with
3.5 million points resulted in a frametime of about
30 milliseconds, with 5.7 million points we measured
60 milliseconds and for 11 million points we obtain
a frametime of 100 milliseconds. The performance
test was conducted using an AMD Radeon 5700XT
with 8 GB VRAM on a Ryzen 5 CPU with 3.6 GHz
and 32 GB RAM rendering at a viewport resolution
2947 × 1661
pixels. The run-time performance de-
pends mainly on the geometric complexity of the 3D
scene and decreases approx. linearly with the number
of points to process. However, while a high point den-
sity is useful for the depth pass to avoid gaps between
points it is not conducive to the overall visual quality
of the hatching effect, i.e., the generated strokes are
hardly distinguishable.
Due to the nature of point clouds, espe-
cially when created using consumer LiDAR scanners,
outliers from the depth pass (remember, all points are
used for this pass) sometimes cover strokes and might
not be desired. Similarly, the point cloud density is
typically rather irregular, which sometimes leads to
strokes bleeding from the background into the fore-
ground. Both effects can be mitigated by tweaking the
polygon offset as well as the adjusting the point size
within the depth pass. Furthermore, these effects are
not inherently wrong and are often also desirable for
less dense point clouds.
The same applies for strokes which leave an ob-
ject’s expected silhouette or contour (over-shooting of
strokes). For us, this was mostly visually pleasing and
also a welcome differentiator from image-based ren-
derings. There might be cases where this is not desired
or not fitting a specific style though. Since point clouds
are never expected to be two manifold (i.e., watertight
or closed) and more often used for capturing open
environments than for solid and closed objects, we
render the mentioned drawbacks as non-problematic
exceptions of our technique. The distinctive styles
can be easily achieved with only minor configurations
within our art-directed parameterization and the tech-
nique can be implemented without exotic extension or
groundbreaking graphics APIs.
This paper presents a real-time non-photorealistic ren-
dering technique for art-directed hatches of 3D point
clouds. By extending the X-Toon approach of Barla
et al., it facilitates various configurations yielding dif-
ferent stylization results for potentially massive 3D
point clouds that are obtained by
or sampling polygonal 3D meshes. The current state
provides basis to develop and apply more advanced
stylization techniques for 3D point clouds. For exam-
ple, to synthesize more sophisticated stylized render-
ings, our technique can be extended to support out-
lines (Rosenthal and Linsen, 2008) or even suggestive
contours (Proen
a et al., 2008) using the derived curva-
ture information (M
erigot et al., 2009; Lu et al., 2020).
Further, level-of-detail approaches for geometry gen-
eration stage can be implemented enabling seamless
level-of-abstraction transitions (Semmo and D
2014). Furthermore, the depth pass could be improved
by using oriented point splats (Anjos et al., 2018).
We thank the anonymous reviewers for their valu-
able feedback. This work was partially funded by the
German Federal Ministry of Education and Research
) through grants 01IS18092 (“mdViPro”) and
01IS19006 (“KI-LAB-ITSE”).
A Non-Photorealistic Rendering Technique for Art-directed Hatching of 3D Point Clouds
(a) Cross Hatched
(b) Colorful Contour
(c) Classic Pointillism
(d) Two-Colored Dark
(e) White and Black Chalk
(f) Blueprint
(g) iPad Scan, Hatched
(h) iPad Scan, Cross Hatched
(i) iPad Scan, Crayons
(j) Statue (k) Temple
(l) Tree with Leaves
(m) Skull
(a) Cross Hatched
(b) Colorful Contour
(c) Classic Pointillism
(d) Two-Colored Dark
(e) White and Black Chalk
(f) Blueprint
(g) iPad Scan, Hatched
(h) iPad Scan, Cross Hatched
(i) iPad Scan, Crayons
(j) Statue (k) Temple
(l) Tree with Leaves
(m) Skull
(a) Cross Hatched
(b) Colorful Contour
(c) Classic Pointillism
(d) Two-Colored Dark
(e) White and Black Chalk
(f) Blueprint
(g) iPad Scan, Hatched
(h) iPad Scan, Cross Hatched
(i) iPad Scan, Crayons
(j) Statue (k) Temple
(l) Tree with Leaves
(m) Skull
(a) Cross Hatched
(b) Colorful Contour
(c) Classic Pointillism
(d) Two-Colored Dark
(e) White and Black Chalk
(f) Blueprint
(g) iPad Scan, Hatched
(h) iPad Scan, Cross Hatched
(i) iPad Scan, Crayons
(j) Statue (k) Temple
(l) Tree with Leaves
(m) Skull
(a) Cross Hatched
(b) Colorful Contour
(c) Classic Pointillism
(d) Two-Colored Dark
(e) White and Black Chalk
(f) Blueprint
(g) iPad Scan, Hatched
(h) iPad Scan, Cross Hatched
(i) iPad Scan, Crayons
(j) Statue (k) Temple
(l) Tree with Leaves
(m) Skull
(a) Cross Hatched
(b) Colorful Contour
(c) Classic Pointillism
(d) Two-Colored Dark
(e) White and Black Chalk
(f) Blueprint
(g) iPad Scan, Hatched
(h) iPad Scan, Cross Hatched
(i) iPad Scan, Crayons
(j) Statue (k) Temple
(l) Tree with Leaves
(m) Skull
(a) Cross Hatched
(b) Colorful Contour
(c) Classic Pointillism
(d) Two-Colored Dark
(e) White and Black Chalk
(f) Blueprint
(g) iPad Scan, Hatched
(h) iPad Scan, Cross Hatched
(i) iPad Scan, Crayons
(j) Statue (k) Temple
(l) Tree with Leaves
(m) Skull
(a) Cross Hatched
(b) Colorful Contour
(c) Classic Pointillism
(d) Two-Colored Dark
(e) White and Black Chalk
(f) Blueprint
(g) iPad Scan, Hatched
(h) iPad Scan, Cross Hatched
(i) iPad Scan, Crayons
(j) Statue (k) Temple
(l) Tree with Leaves
(m) Skull
(a) Cross Hatched
(b) Colorful Contour
(c) Classic Pointillism
(d) Two-Colored Dark
(e) White and Black Chalk
(f) Blueprint
(g) iPad Scan, Hatched
(h) iPad Scan, Cross Hatched
(i) iPad Scan, Crayons
(j) Statue (k) Temple
(l) Tree with Leaves
(m) Skull
(a) Cross Hatched
(b) Colorful Contour
(c) Classic Pointillism
(d) Two-Colored Dark
(e) White and Black Chalk
(f) Blueprint
(g) iPad Scan, Hatched
(h) iPad Scan, Cross Hatched
(i) iPad Scan, Crayons
(j) Statue (k) Temple
(l) Tree with Leaves
(m) Skull
(a) Cross Hatched
(b) Colorful Contour
(c) Classic Pointillism
(d) Two-Colored Dark
(e) White and Black Chalk
(f) Blueprint
(g) iPad Scan, Hatched
(h) iPad Scan, Cross Hatched
(i) iPad Scan, Crayons
(j) Statue (k) Temple
(l) Tree with Leaves
(m) Skull
Figure 7: Various results of our NPR rendering-technique. A point cloud scan of the Stanford bunny was used in (a)
to (f). The point clouds in (g) to (i) have are actual point clouds captured using an iPad. In (j) to (m) the points are
sampled from 3D polygonal meshes and rendered using our NPR technique. All results are captured from our C++ imple-
mentation, rendered interactively and in real-time (
in Full-HD and QHD) with a temporal coherence not possible
using image-based approaches. Meshes used for (j) and (k) are licensed under CC Attribution and have been created by
noe-3d.at (sketchfab.com/3d-models/grabfigur-cfec3a9d71db42978d4a377a0e8f1154) and Robin Butler (sketchfab.com/3d-
models/roman-temple-f5efe108fb19419ab985ef69d1762839) respectively.
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A Non-Photorealistic Rendering Technique for Art-directed Hatching of 3D Point Clouds