299,527 research outputs found

    Context-aware Synthesis for Video Frame Interpolation

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    Video frame interpolation algorithms typically estimate optical flow or its variations and then use it to guide the synthesis of an intermediate frame between two consecutive original frames. To handle challenges like occlusion, bidirectional flow between the two input frames is often estimated and used to warp and blend the input frames. However, how to effectively blend the two warped frames still remains a challenging problem. This paper presents a context-aware synthesis approach that warps not only the input frames but also their pixel-wise contextual information and uses them to interpolate a high-quality intermediate frame. Specifically, we first use a pre-trained neural network to extract per-pixel contextual information for input frames. We then employ a state-of-the-art optical flow algorithm to estimate bidirectional flow between them and pre-warp both input frames and their context maps. Finally, unlike common approaches that blend the pre-warped frames, our method feeds them and their context maps to a video frame synthesis neural network to produce the interpolated frame in a context-aware fashion. Our neural network is fully convolutional and is trained end to end. Our experiments show that our method can handle challenging scenarios such as occlusion and large motion and outperforms representative state-of-the-art approaches.Comment: CVPR 2018, http://graphics.cs.pdx.edu/project/ctxsy

    Two-handed navigation in a haptic virtual environment

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    This paper describes the initial results from a study looking at a two-handed interaction paradigm for tactile navigation for blind and visually impaired users. Participants were set the task of navigating a virtual maze environment using their dominant hand to move the cursor, while receiving contextual information in the form of tactile cues presented to their non-dominant hand. Results suggest that most participants were comfortable with the two-handed style of interaction even with little training. Two sets of contextual cues were examined with information presented through static patterns or tactile flow of raised pins. The initial results of this study suggest that while both sets of cues were usable, participants performed significantly better and faster with the static cues

    Counterexamples to simulation in non-deterministic call-by-need lambda-calculi with letrec

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    This note shows that in non-deterministic extended lambda calculi with letrec, the tool of applicative (bi)simulation is in general not usable for contextual equivalence, by giving a counterexample adapted from data flow analysis. It also shown that there is a flaw in a lemma and a theorem concerning finite simulation in a conference paper by the first two authors

    Brain rhythms of pain

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    Pain is an integrative phenomenon that results from dynamic interactions between sensory and contextual (i.e., cognitive, emotional, and motivational) processes. In the brain the experience of pain is associated with neuronal oscillations and synchrony at different frequencies. However, an overarching framework for the significance of oscillations for pain remains lacking. Recent concepts relate oscillations at different frequencies to the routing of information flow in the brain and the signaling of predictions and prediction errors. The application of these concepts to pain promises insights into how flexible routing of information flow coordinates diverse processes that merge into the experience of pain. Such insights might have implications for the understanding and treatment of chronic pain
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