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| The problem of the light field (LF) stitching aims to align two 4D LFs seamlessly. However, the prior works use conventional $3\times3$ homography to draw the 2D relation and ignore the depth information, leading to two main disadvantages, namely, significant stitching artifacts in the general scene and failure to produce stitched depth map. This paper tackles these challenges by proposing a $4\times4$ homography that analytically and globally describes the relationship between two LFs under pure rotation. Besides, we also present a novel linear solver called 4ry, which can estimate the 4D homography by giving four 4D LF feature correspondences. Extensive synthetic and real data experiments demonstrate that the proposed method outperforms state-of-the-art approaches in LF stitching qualitatively and quantitatively. More importantly, the output of our method is still an LF that retains the nature of LF, such as refocusing, viewpoint shifting, and depth estimation. |
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| Keywords:Computer vision, Homography estimation, Image stitching |
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