Demo: BeCasso - Artistic Image Processing and Editing on Mobile Devices
Sebastian Pasewaldt Amir Semmo J¨
Hasso Plattner Institute, University of Potsdam, Germany∗
Digital Masterpieces GmbH∗
Figure 1: Three results produced with BeCasso for an input image with a resolution of 2,400 ×1,600 pixels (displayed cropped): cartoon
(left), oil paint (middle) and watercolor style (right). The outputs are based on multi-stage, ﬂow-based nonlinear ﬁltering and color grading.
BeCasso is a mobile app that enables users to transform photos into
high-quality, high-resolution non-photorealistic renditions, such as
oil and watercolor paintings, cartoons, and colored pencil drawings,
which are inspired by real-world paintings or drawing techniques.
In contrast to neuronal network and physically-based approaches,
the app employs state-of-the-art nonlinear image ﬁltering. For ex-
ample, oil paint and cartoon effects are based on smoothed structure
information to interactively synthesize renderings with soft color
transitions. BeCasso empowers users to easily create aesthetic ren-
derings by implementing a two-fold strategy: First, it provides pa-
rameter presets that may serve as a starting point for a custom styl-
ization based on global parameter adjustments. Thereby, users can
obtain initial renditions that may be ﬁne-tuned afterwards. Sec-
ond, it enables local style adjustments: using on-screen painting
metaphors, users are able to locally adjust different stylization fea-
tures, e.g., to vary the level of abstraction, pen, brush and stroke di-
rection or the contour lines. In this way, the app provides tools for
both higher-level interaction and low-level control [Isenberg 2016]
to serve the different needs of non-experts and digital artists.
Keywords: mobile, non-photorealistic rendering, image ﬁltering,
stylization, interaction, GPU
Concepts: •Computing methodologies →Image manipulation;
•Human-centered computing →Mobile devices;
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SA ’16, December 05-08, 2016, Macao
Image stylization enjoys a growing popularity on mobile devices to
foster casual creativity [Winnem¨
oller 2013]. With the limiting hard-
ware capabilities of mobile devices, an interactive processing of
high-resolution images becomes an increasingly challenging task,
in particular for artistic rendering that is based on multi-stage non-
linear ﬁltering. One approach is to shift complex processing tasks
to dedicated servers and only use mobile devices for image display,
which however sacriﬁces interactive manipulations by users.
This work presents BeCasso, a mobile app that implements a GPU-
based, efﬁcient image analysis and processing pipeline to realize
the objective of an interactive image processing on mobile devices:
(1) real-time color grading using lookup tables is employed to sim-
ulate rendering with reduced color palettes, (2) a multi-scale ap-
proach processes images on downsampled versions and performs
upsampling to achieve deliberate levels of abstraction [Semmo et al.
2016], (3) graph-based processing chains of multi-stage effects
are analyzed to dynamically trigger only invalidated stages, and
(4) algorithms for an efﬁcient (re-)use of textures reduce the mem-
ory footprint while maintaining rendering performance. These en-
hancements signiﬁcantly facilitate the implementation of interac-
tive tools to adjust ﬁltering effects at run-time, such as toon, wa-
tercolor and oil paint (Figure 1). This is demonstrated by an on-
screen painting interface for per-pixel parameterization, e.g., to lo-
cally vary the color diffusion and level of abstraction.
This work was partly funded by the Federal Ministry of Education and Re-
search (BMBF), Germany, for the AVA project 01IS15041B and within the
InnoProﬁle Transfer research group “4DnD-Vis” (www.4dndvis.de).
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