An algorithm developed by Brown University researchers may help bring high-quality 3D scanning capability to off-the-shelf digital cameras and smartphones.
“One of the things my lab has been focusing on is getting 3D image capture from relatively low-cost components,” said Gabriel Taubin, professor in Brown’s School of Engineering.
The 3D scanners on the market today are either very expensive, or are unable to do high-resolution image capture, so they can’t be used for applications where details are important.
Most high-quality 3D scanners capture images using a technique known as structured light.
A projector casts a series of light patterns on an object, while a camera captures images of the object.
The ways in which those patterns deform over and around an object can be used to render a 3D image.
But for the technique to work, the pattern projector and the camera have to precisely synchronised which requires specialized and expensive hardware.
The new algorithm enables the structured light technique to be done without synchronisation between projector and camera, which means an off-the-shelf camera can be used with an untethered structured light flash.
The camera just needs to have the ability to capture uncompressed images in burst mode (several successive frames per second), which many DSLR cameras and smartphones can do.
After the camera captures a burst of images, algorithm calibrates the timing of the image sequence using the binary information embedded in the projected pattern.
Then it goes through the images, pixel by pixel, to assemble a new sequence of images that captures each pattern in its entirety.
Once the complete pattern images are assembled, a standard structured light 3D reconstruction algorithm can be used to create a single 3D image of the object or space.
“We think this could be a significant step in making precise and accurate 3-D scanning cheaper and more accessible,” Taubin noted.