August 28, 2017 by Ben-Gurion University
Aug. 28, 2017 – An international group of researchers say they have developed a technique that combines robotics and water and results in more accurate 3D scanning for reconstructing complex objects than what currently exists.
“Using a robotic arm to immerse an object on an axis at various angles, and measuring the volume displacement of each dip, we combine each sequence and create a volumetric shape representation of an object,” says Prof. Andrei Scharf of Ben-Gurion University of the Negev, Department of Computer Science.
In addition to Prof. Scharf, who is also affiliated with the Advanced Innovation Center for Future Visual Entertainment (AICFVE) in Beijing China, the other researchers involved include Kfir Aberman, Oren Katzir and Daniel Cohen-Or of Tel Aviv University and AICFVE; Baoquan Chen, Qiang Zhou and Zegang Luo of Shandong University; and Chen Greif of The University of British Columbia.
“The key feature of our method is that it employs fluid displacements as the shape sensor,” Prof. Scharf explains. “Unlike optical sensors, the liquid has no line-of-sight requirements. It penetrates cavities and hidden parts of the object, as well as transparent and glossy materials, thus bypassing all visibility and optical limitations of conventional scanning devices.”
The researchers used Archimedes’ theory of fluid displacement — the volume of displaced fluid is equal to the volume of a submerged object — to turn the modelling of surface reconstruction into a volume measurement problem. This serves as the foundation for the team’s solution to challenges in current 3D shape reconstruction.
The group demonstrated the new technique on 3D shapes with a range of complexity, including an elephant sculpture, a mother and child hugging and a DNA double helix, and note that the results show the dip reconstructions are nearly as accurate as the original 3D model.
The new technique is related to computed tomography — an imaging method that uses optical systems for scanning and pictures. However, tomography-based devices are bulky and expensive and can only be used in a safe, customized environment, says the group.
Prof. Scharf says, “Our approach is both safe and inexpensive, and a much more appealing alternative for generating a complete shape at a low-computational cost, using an innovative data collection method.”