论文标题
自然图像使用深度图
Natural Image Stitching Using Depth Maps
论文作者
论文摘要
自然图像缝合（NIS）旨在从两个重叠的图像中创建一个自然的马赛克，这些图像从不同的观看位置捕获相同的3D场景。当场景是非平面且相机基线广泛时，挑战不可避免地会出现，因为在这种情况下，视差变得不可忽略。在本文中，我们提出了一种使用深度图的新型NIS方法，该方法在重叠和非重叠区域中都会产生自然的马赛克。首先，我们构建了一种强大的拟合方法，以滤除特征匹配中的离群值并估算输入图像之间的外两极几何形状。然后，我们根据其顶点的位置，整流的深度值和表现几何形状来绘制目标图像的三角剖分，并估算每个三角形的多个局部植物。最后，翘曲图像是由零件同构图的向后映射构成的。然后，全景通过平均混合和图像插入生产。实验结果表明，所提出的方法不仅提供了重叠区域中的准确比对，而且还提供了非重叠区域的虚拟自然性。
Natural image stitching (NIS) aims to create one natural-looking mosaic from two overlapping images that capture the same 3D scene from different viewing positions. Challenges inevitably arise when the scene is non-planar and the camera baseline is wide, since parallax becomes not negligible in such cases. In this paper, we propose a novel NIS method using depth maps, which generates natural-looking mosaics against parallax in both overlapping and non-overlapping regions. Firstly, we construct a robust fitting method to filter out the outliers in feature matches and estimate the epipolar geometry between input images. Then, we draw a triangulation of the target image and estimate multiple local homographies, one per triangle, based on the locations of their vertices, the rectified depth values and the epipolar geometry. Finally, the warping image is rendered by the backward mapping of piece-wise homographies. Panorama is then produced via average blending and image inpainting. Experimental results demonstrate that the proposed method not only provides accurate alignment in the overlapping regions but also virtual naturalness in the non-overlapping region.
