Imagine shopping online for the perfect back-to-school outfit. You can see the colour and size and perhaps the texture of the fabric, but can you tell how it will look from different perspectives under fluorescent classroom lighting?
"The material might be very beautiful but a potential customer wouldnt know that because the image gives a grossly incomplete sense of texture," says Alex Vasilescu, a doctoral candidate at U of Ts Department of Computer Science. The software she has developed, called TensorTextures, requires just a few sample images of any surface with complex three-dimensional relief, such as luxurious velvets or shimmering silks. Using that information, it can render the true appearance of the surface from every possible viewpoint and under any illumination.
TensorTextures could be adapted for the Web and filmmaking and could possibly be introduced commercially within a year, says Vasilescu. The software is described in a study presented at the SIGGRAPH 2003 conference on computer graphics and interactive techniques in San Diego July 31.CONTACT: Alex Vasilescu, Department of Computer Science (currently at the Media Research Lab, New York University) 212-998-3320, email@example.com or Nicolle Wahl, U of T public affairs, 416-978-6974, firstname.lastname@example.org
Nicolle Wahl | U of T
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Material defects in end products can quickly result in failures in many areas of industry, and have a massive impact on the safe use of their products. This is why, in the field of quality assurance, intelligent, nondestructive sensor systems play a key role. They allow testing components and parts in a rapid and cost-efficient manner without destroying the actual product or changing its surface. Experts from the Fraunhofer IZFP in Saarbrücken will be presenting two exhibits at the Blechexpo in Stuttgart from 7–10 November 2017 that allow fast, reliable, and automated characterization of materials and detection of defects (Hall 5, Booth 5306).
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