Image Source: facebook.com/Digital3D.it
NVIDIA Co-founder and CEO Jen-Hsun Huang showcases a demo of Face Works technology running on the GeForce GTX TITAN GPU. It includes a must be seen to be believed, amazingly realistic simulation of a face in this second segment of the opening day keynote at GTC 2013.
Activision R&D Real-time Character Demo
Last Thursday at the Optical Fiber Communication Conference in Los Angeles, a team from IBM presented research on their wonderfully-named “Holey Optochip.” The prototype chipset is the first parallel optical transceiver that is able to transfer one trillion bits (or one terabit) of information per second. To put that in perspective, IBM states that 500 high-def movies could be downloaded in one second at that speed, while the entire U.S. Library of Congress web archive could be downloaded in an hour. Stated another way, the Optochip is eight times faster than any other parallel optical components currently available, with a speed that’s equivalent to the bandwidth consumed by 100,000 users, if they were using regular 10 Mb/s high-speed internet.
For decades, scientists have dreamed of building computer systems that could replicate the human brain’s talent for learning new tasks. Plasticity is the new phenomenon developed at Massachusetts Institute of Technology- MIT, is believed to underlie many brain functions, including learning and memory. The MIT researchers have designed a computer chip that mimics how the brain’s neurons adapt in response to new information.
At last month’s SuperComputing 2011 (SC11) conference in Seattle, researchers reached transfer rates of 98 gigabits per second. The team consisted of high-energy physicists, computer scientists, and network engineers, and was led by the California Institute of Technology (Caltech), the University of Victoria, the University of Michigan, the European Center for Nuclear Research (CERN), Florida International University, and other partners. [Via: supercomputing.caltech.edu/]
Robert J. Moore will astonish you with how much data is being created. He stresses the importance of organizing and analyzing the insane amount of data we now have.
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Abstract
“We present a method for replacing facial performances in video. Our approach accounts for differences in identity, visual appearance, speech, and timing between source and target videos. Unlike prior work, it does not require substantial manual operation or complex acquisition hardware, only single-camera video. We use a 3D multilinear model to track the facial performance in both videos. Using the corresponding 3D geometry, we warp the source to the target face and retime the source to match the target performance. We then compute an optimal seam through the video volume that maintains temporal consistency in the final composite. We showcase the use of our method on a variety of examples and present the result of a user study that suggests our results are difficult to distinguish from real video footage.”
[Via Paper Source: faceReplace_sa2011.pdf]
“Figure 1: Our method for face replacement requires only single-camera video of the source (a) and target (b) subject, which allows for simple acquisition and reuse of existing footage. We track both performances with a multilinear morphable model then spatially and temporally align the source face to the target footage (c). We then compute an optimal seam for gradient domain compositing that minimizes bleeding and flickering in the final result (d).”
[Via Paper Source: faceReplace_sa2011.pdf]
Kevin Dale
Graphics, Vision, and Interaction Group
School of Engineering and Applied Sciences
Harvard University
Authors: Kevin Dale; Kalyan Sunkavalli; Micah K. Johnson; Daniel Vlasic; Wojciech Matusik; Hanspeter Pfister
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