A Dual Camera System for High Spatiotemporal Resolution Video Acquisition
This paper presents a dual camera system for high spatiotemporal resolution (HSTR) video acquisition, where one camera shoots a video with high spatial resolution and low frame rate (HSR-LFR) and another one captures a low spatial resolution and high frame rate (LSR-HFR) video. Our main goal is to c...
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Main Authors | , , , , , , |
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Format | Journal Article |
Language | English |
Published |
28.09.2019
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Subjects | |
Online Access | Get full text |
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Summary: | This paper presents a dual camera system for high spatiotemporal resolution
(HSTR) video acquisition, where one camera shoots a video with high spatial
resolution and low frame rate (HSR-LFR) and another one captures a low spatial
resolution and high frame rate (LSR-HFR) video. Our main goal is to combine
videos from LSR-HFR and HSR-LFR cameras to create an HSTR video. We propose an
end-to-end learning framework, AWnet, mainly consisting of a FlowNet and a
FusionNet that learn an adaptive weighting function in pixel domain to combine
inputs in a frame recurrent fashion. To improve the reconstruction quality for
cameras used in reality, we also introduce noise regularization under the same
framework. Our method has demonstrated noticeable performance gains in terms of
both objective PSNR measurement in simulation with different publicly available
video and light-field datasets and subjective evaluation with real data
captured by dual iPhone 7 and Grasshopper3 cameras. Ablation studies are
further conducted to investigate and explore various aspects (such as reference
structure, camera parallax, exposure time, etc) of our system to fully
understand its capability for potential applications. |
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DOI: | 10.48550/arxiv.1909.13051 |