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Seam Reconstruct: Dynamic scene stitching with Large exposure difference

机译:Seam Reconstruct:动态场景缝合大曝光差异

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Panoramic stitching of static and dynamic scenes is a very important and challenging research area. For static scenes, number of approaches has been proposed so far. The result produced by these approaches provides great similarity between resultant panorama and input images with almost zero seam visibility. However for dynamic scenes, we have found that existing approaches are unable to overcome the challenges introduced due to simultaneous presence of (A) Large exposure difference and (B) Moving Objects. In this paper we propose a Seam-Reconstruction technique which overcomes these limitations. Seam-Reconstruction technique is a two step approach. The first step resolves the position of moving objects and prevents ghosting due to parallax by building a reference panorama with the help of optimal seam evaluation technique while the second step removes the remaining differences along the seam with the help of Poisson's equation. Experimental result depicts that we were able to stitch dynamic scene containing large exposure difference maintaining the quality as well as photometric and geometric similarity.
机译:静态和动态场景的全景拼接是一个非常重要和充满挑战性的研究区。对于静态场景,到目前为止提出了方法数。通过这些方法产生的结果在合成的全景和输入图像之间提供了很大的相似性,具有几乎零缝可视性。然而,对于动态场景,我们发现现有方法无法克服由于(a)大曝光差和(b)移动物体的同时存在而引入的挑战。在本文中,我们提出了一种克服了这些限制的接缝重构技术。接缝重建技术是一种两步的方法。第一步通过在最佳接缝评估技术的帮助下通过建立参考全景,通过在最佳接缝评估技术的帮助下,解决了移动物体的位置并防止由于视差而导致重影。第二步在泊松等式的帮助下除去沿着接缝的剩余差异。实验结果描绘了我们能够缝合具有大曝光差的动态场景,保持质量和光度和几何相似性。

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