Image stylization with a painting machine using semantic hints

Lindemeier, Thomas; Pirk, Sören; Deußen, Oliver

doi:10.1016/j.cag.2013.01.005

Cited by 34 publications

(18 citation statements)

References 13 publications

(19 reference statements)

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“…A more sophisticated type of method can be developed by training the machine learning algorithms to become skilled at styles or design concepts found in a diverse population of work and designers. Style as creative freedom is a higher level semantic problem found in design and initial ground have been developed in drawing and painting algorithms (Lindemeier, 2013).…”

Section: Learning Algorithms In Architectural Designmentioning

confidence: 99%

Automated Architecture: Why CAD, Parametrics and Fabrication are Really Old News

Andia¹

2013

Proceedings of the XVII Conference of the Iberoamerican Society of Digital Graphics - SIGraDi: Knowledge-Based Design

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Automation is transforming a significant number of industries today. This paper discusses how the Design and Construction industry is also entering into a new era of automation. In the paper I observe that designers are automating by using parametric tools (BIM, scripting, etc.) while contractors are moving into pre--fabrication and modularization. Both conceptualizations are incomplete. The paper presents how we are in the first steps of creating learning algorithms that develop specific intelligence in design synthesis and how the design field will became even more sophisticated as a second generation of multi--material 3D printing techniques produce new materials.

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Section: Learning Algorithms In Architectural Designmentioning

confidence: 99%

Automated Architecture: Why CAD, Parametrics and Fabrication are Really Old News

Andia¹

2013

Proceedings of the XVII Conference of the Iberoamerican Society of Digital Graphics - SIGraDi: Knowledge-Based Design

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“…The possibilities to edit the colors of an object that already exists or is manufactured by other means are more limited. Paint and decals work well on flat surfaces [LPD13], but are challenging on more complicated surfaces. Video projectors can handle such complex shapes [RWLB01, BBG*13], but the projection requires a special setup and largely precludes touching and manipulating the object.…”

Section: Introductionmentioning

confidence: 99%

“…Images can be painted on a flat canvas manually using a computer‐assisted airbrush [SMPZ15] or spray can [PJJSH15], or automatically by the robot of Lindemeier et al [LPD13]. While these approaches can generate sophisticated color maps, extending them to work on small non‐planar surfaces would be challenging.…”

Section: Introductionmentioning

confidence: 99%

Texture Mapping Real‐World Objects with Hydrographics

Panozzo

Diamanti

Paris

et al. 2015

Computer Graphics Forum

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In the digital world, assigning arbitrary colors to an object is a simple operation thanks to texture mapping. However, in the real world, the same basic function of applying colors onto an object is far from trivial. One can specify colors during the fabrication process using a color 3D printer, but this does not apply to already existing objects. Paint and decals can be used during post-fabrication, but they are challenging to apply on complex shapes. In this paper, we develop a method to enable texture mapping of physical objects, that is, we allow one to map an arbitrary color image onto a three-dimensional object. Our approach builds upon hydrographics, a technique to transfer pigments printed on a sheet of polymer onto curved surfaces. We first describe a setup that makes the traditional water transfer printing process more accurate and consistent across prints. We then simulate the transfer process using a specialized parameterization to estimate the mapping between the planar color map and the object surface. We demonstrate that our approach enables the application of detailed color maps onto complex shapes such as 3D models of faces and anatomical casts

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“…Strokes are applied until the difference between canvas and given input is sufficiently small. Details for the general feedback mechanism are described in Lindemeier et al [LPD13].…”

Section: Overviewmentioning

confidence: 99%

“…Reinhard et al [RAGS01] propose color transformation from one image to another. Pitié et al [PKD05,PKD07] LPD13] we work with acrylic paint. That requires a completely modified painting pipeline and imposes a number of algorithmical challenges.…”

Section: Related Workmentioning

confidence: 99%