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An Efficient Multi-View Panoramic Imaging and Extra Compression of Surveillance Cameras’ Footage Using Stitching

机译:使用缝合的高效多视图全景成像和监视摄像机镜头的额外压缩

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Saving data stored and transferred is a critical topic in modern era, especially after the evolution in the numbers of surveillance cameras in the world. So an extra level of compression is needed to contribute in solving the problem of the huge data produced by those cameras. The proposed system: “An Efficient multi-view panoramic imaging and Extra Compression of surveillance cameras' footage using Stitching” (ECS) aims to contribute in the solution of this problem by merging feature extraction stitching techniques with geometric relational matrix calculations. ECS creates a new real-time efficient stitching algorithm to minimize the sending and storing of the redundant pixels between the footage of the surveillance cameras. The limitations of using stitching on video footage and not on still images is due to the high complexities of stitching algorithms; the proposed system, in this paper, uses the projective affine transformation matrix between images of camera footage to reduce this limitations. The work presented in this paper introduces, for the first time, an algorithm to reconstruct images of each camera from the panoramic view. The experimental work of this research tests multiple feature extraction algorithms for stitching; Scale Invariant Feature Transform (SIFT), Speed Up Robust Feature (SURF) and Oriented FAST and Rotated BRIEF (ORB) with different order of stitching, and the amount of compression per image after reconstruction is analyzed. Moreover, the panoramic view is mostly a better monitoring option rather than multiple monitors in complex surveillance cameras' control rooms. Experimental results show that the proposed method could be faster than other state-of-the-art image stitching methods and accurate panoramic image. The system also gives a better visual effect in a large view panorama due to the high speed real time stitching introduced in this paper.
机译:保存存储和转移的数据是现代时代的关键主题,尤其是在世界上监控摄像机数量之后的演变之后。因此,需要额外的压缩水平来解决解决这些摄像机产生的巨大数据的问题。所提出的系统:“使用缝合”(ECS)的高效多视图全景成像和监控摄像机“素材的额外压缩旨在通过利用具有几何关系矩阵计算的特征提取拼接技术来解决该问题的解决方案。 ECS创建了一种新的实时高效拼接算法,可最大限度地减少监视摄像机的镜头之间的冗余像素的发送和存储。在视频镜头上使用缝合而不是静止图像的限制是由于拼接算法的高复杂性;本文中所提出的系统使用摄像机镜头图像之间的投影仿射转换矩阵来减少此限制。本文呈现的工作首次介绍了从全景视图重建每个相机的图像的算法。该研究的实验工作测试了用于拼接的多个特征提取算法;缩放不变特征变换(SIFT),加速鲁棒特征(冲浪),并以不同的缝合顺序定向快速和旋转的简要(ORB),分析重建后的每张图像的压缩量。此外,全景视图主要是更好的监控选项,而不是复杂监视摄像机控制室中的多个监视器。实验结果表明,该方法可以比其他最先进的图像拼接方法和准确的全景图像更快。由于本文介绍的高速实时缝合,该系统在大型视野全景中还提供了更好的视觉效果。

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