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Multi-camera Video Resolution Enhancement by Fusion of Spatial Disparity and Temporal Motion fields

机译:空间差距和时间运动字段融合的多摄像机视频分辨率增强

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In this work, we consider the problem of spatio-temporal resolution enhancement of a dynamic video scene by synergistically combining information from multiple video sequences corresponding to the different views of the scene. While prior work has focused on spatio-temporal super-resolution by primarily exploiting the blurring correlation induced by the scene imaging process, in this work we exploit another and perhaps a stronger form of correlation - the intrinsic correlation present in the dynamic scene. We use the knowledge base from the areas of multi-view computer vision, video coding and signal/image processing to efficiently model the dynamic video scene by exploiting inter-camera (space) as well as intra-camera correlations (time). We present simulation results corresponding to a low-frame rate two-camera stereo video configuration where the sequences are combined to generate higher frame-rate sequences. Our proposed framework has direct application to problems such as multi-view video surveillance and relates closely to problems such as multi-view video compression.
机译:在这项工作中,我们考虑通过协同组合来自对应于场景的不同视图的多个视频序列的信息来协同组合信息来考虑动态视频场景的时空分辨率提高的问题。虽然事先工作专注于时空超分辨率,主要通过主要利用场景成像过程引起的模糊相关性,但在这项工作中,我们利用另一个,并且可能是更强烈的相关形式 - 动态场景中存在的内在相关性。我们使用来自多视图计算机视觉,视频编码和信号/图像处理区域的知识库,以通过利用相机(空间)以及相机内相关的相关性(时间)来有效地模拟动态视频场景。我们存在对应于低帧速率的仿真结果,其中序列被组合以产生更高的帧速率序列。我们所提出的框架直接应用于多视图视频监控等问题,并与多视图视频压缩等问题密切相关。

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