Continuous-Time Intensity Estimation Using Event Cameras

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Scheerlinck, Cedric
Barnes, Nick
Mahony, Robert

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Springer

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Event cameras provide asynchronous, data-driven measurements of local temporal contrast over a large dynamic range with extremely high temporal resolution. Conventional cameras capture low frequency reference intensity information. These two sensor modalities provide complementary information. We propose a computationally efficient, asynchronous filter that continuously fuses image frames and events into a single high-temporal-resolution, high-dynamic-range image state. In absence of conventional image frames, the filter can be run on events only. We present experimental results on high-speed, highdynamic-range sequences, as well as on new ground truth datasets we generate to demonstrate the proposed algorithm outperforms existing state-of-the-art methods.

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Proceedings of the 14th Asian Conference on Computer Vision LNCS

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Open Access

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