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Multi-hypothesis Projection-Based Shift Estimation for Sweeping Panorama Reconstruction

机译:基于多假设投影的平移全景重建平移估计

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摘要

Global alignment is an important step in many imaging applications for hand-held cameras. We propose a fast algorithm that can handle large global translations in either x-or y-direction from a pan-tilt camera. The algorithm estimates the translations in x- and y-direction separately using 1D correlation of the absolute gradient projections along the x- and y-axis. Synthetic experiments show that the proposed multiple shift hypotheses approach is robust to translations up to 90% of the image width, whereas other projection-based alignment methods can handle up to 25% only. The proposed approach can also handle larger rotations than other methods. The robustness of the alignment to non-purely translational image motion and moving objects in the scene is demonstrated by a sweeping panorama application on live images from a Canon camera with minimal user interaction.
机译:全局对准是手持摄像机在许多成像应用中的重要一步。我们提出了一种快速算法,该算法可以处理来自云台摄像机的x或y方向上的大型全局平移。该算法使用沿x和y轴的绝对梯度投影的一维相关性分别估计x和y方向的平移。综合实验表明,所提出的多位移假设方法对于平移多达90%的图像宽度是鲁棒的,而其他基于投影的对齐方法只能处理多达25%的图像。所提出的方法还可以处理比其他方法更大的旋转。佳能相机的实时图像上的全景扫描应用程序以最小的用户交互性展示了对场景中非纯平移图像运动和运动对象对齐的鲁棒性。

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