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Image capture pattern optimization for panoramic photography

机译:全景摄影的图像捕获模式优化

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摘要

Panoramic photography requires intensive operations of image stitching. A large quantity of images may lead to a rather expensive image stitching; while a sparse imaging may cause a poor-quality panorama due to the insufficient correlation between adjacent images. So, a good study for the balance between image quantity and image correlation may improve the efficiency and quality of panoramic photography. Therefore, in this work, we are motivated to present a novel approach to estimate the optimal image capture patterns for panoramic photography. We aim at the minimization of the image quantity which still preserves sufficient image correlation. We represent the image correlation as overlap area between the view range that can be separately observed from adjacent images. Moreover, a time-consuming imaging process of panoramic photography will result in a considerable illumination variation of the scene in images. Subsequently, the image stitching will be more challenged. To solve this problem, we design a series of imaging routines for our image capture patterns to preserve the content consistency, ensuring the generalization of our method to various cameras. Experimental results show that the proposed method can obtain the optimal image capture pattern in a very efficient manner. In these patterns, we can obtain a balanced image quantity but still achieve good results of panoramic photography.
机译:全景摄影需要密集的图像拼接操作。大量图像可能导致相当昂贵的图像拼接。而稀疏的成像可能会由于相邻图像之间的相关性不足而导致全景质量较差。因此,对图像数量和图像相关性之间的平衡进行良好的研究可以提高全景摄影的效率和质量。因此,在这项工作中,我们有动机提出一种新颖的方法来估计全景摄影的最佳图像捕获模式。我们旨在使图像数量最小化,同时仍保留足够的图像相关性。我们将图像相关性表示为可以从相邻图像分别观察到的视图范围之间的重叠区域。此外,全景摄影的费时的成像过程将导致图像中场景的照明度发生很大变化。随后,图像拼接将面临更多挑战。为了解决这个问题,我们为图像捕获模式设计了一系列成像例程,以保持内容的一致性,从而确保将方法推广到各种相机。实验结果表明,该方法可以非常有效地获得最优的图像捕获图案​​。在这些模式下,我们可以获得平衡的图像量,但仍然可以实现全景摄影的良好效果。

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