Anamorphosis for 2D displays can provide viewer centric perspective viewing, enabling 3D appearance, eye contact and engagement, by adapting dynamically in real time to a single moving viewer’s viewpoint, but at the cost of distorted viewing for other viewers. We present a method for constructing non-linear projections as a combination of anamorphic rendering of selective objects whilst reverting to normal perspective rendering of the rest of the scene. Our study defines a scene consisting of five characters, with one of these characters selectively rendered in anamorphic perspective.
In this paper, we propose recurrent neural network (RNN) based incremental processing towards the SLU task of intent detection. The proposed methodology offers lower latencies than a typical SLU system, without any significant reduction in system accuracy. We introduce and analyze different recurrent neural network architectures for incremental and online processing of the ASR transcripts and compare it to the existing offline systems.
Robots with kinematic loops are known to have superior mechanical performance. However, due to these loops, their modeling and control is challenging, and prevents a more widespread use. In this paper, we describe a versatile Inverse Kinematics (IK) formulation for the retargeting of expressive motions onto mechanical systems with loops.
We present a novel real-time face detail reconstruction method capable of recovering high quality geometry on consumer mobile devices.
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