FYI.

This story is over 5 years old.

Tech

A Smart Spray Paint Can Allows Anyone To Paint Massive Murals

Artists can paint a massive, life-like mural without even knowing what they are supposed to be painting beforehand.

Love it or hate it, there's no question that street art has become a firmly entrenched aspect of urban cultures around the world. Styles range from hastily scrawled obscenities and tags to stencils and wildstyle, but as any veteran street artist is wont to tell you, the larger the piece, the more technical expertise is required.

The reasons that requisite skill scales up with the size of a street mural are manifold: some are intensely practical (larger pieces are harder to hide from the law) while others are simply a matter of artistic vision (proportion, color and other aspects of painting become more difficult when you can only look at small parts of the piece at a time). Yet thanks to the work of a team of researchers from Dartmouth University, massive photorealistic spray paint murals can now be done by anyone outfitted with their new high-tech, motion sensing spray paint can.

Advertisement

"Typically, computationally-assisted painting methods are restricted to the computer," said Wojciech Jarosz, an assistant professor of computer science at Dartmouth. "In this research, we show that by combining computer graphics and computer vision techniques, we can bring such assistance technology to the physical world even for this very traditional painting medium, creating a somewhat unconventional form of digital fabrication."

As the team details in a study published this week inComputers & Graphics, their spray paint can allows a painter to reproduce a photo as a spray mural with staggering accuracy—with little to no skill required on the part of the painter.

To begin, the researchers selected a photo they wanted writ large on a canvas or wall and uploaded it to a computer. Next, they took a normal spray paint can and outfitted its nozzle with a QR-cube to track the can's motion and an actuation device which controls the amount of paint released from the can. Using two webcams to track the can's motion relative to the wall, an algorithm designed by the researchers 'told' the can how much paint to release and as the painter waved the can around in front of the canvas.

Although computer-aided painting dates back to Desmond Paul Henry's Drawing Machine in 1962, prior to the Dartmouth team's invention, none of the research in this field has allowed non-artists to reproduce images at this scale. Moreover, the researchers hope that as their design becomes more sophisticated, it can be used to recreate images on more complicated, curved surfaces.

Paramount to the researchers, however, was maintaining the integrity of the art form despite relinquishing much of the artistic control to a computer algorithm.

"Our assistive approach is like a modern take on 'paint by numbers' for spray painting," said Jarosz. "Most importantly, we wanted to maintain the aesthetic aspects of physical spray painting and the tactile experience of holding and waving a physical spray can while enabling unskilled users to create a physical piece of art."