Image Stitching and Rectification for Hand-Held Cameras

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 12352)


In this paper, we derive a new differential homography that can account for the scanline-varying camera poses in Rolling Shutter (RS) cameras, and demonstrate its application to carry out RS-aware image stitching and rectification at one stroke. Despite the high complexity of RS geometry, we focus in this paper on a special yet common input—two consecutive frames from a video stream, wherein the inter-frame motion is restricted from being arbitrarily large. This allows us to adopt simpler differential motion model, leading to a straightforward and practical minimal solver. To deal with non-planar scene and camera parallax in stitching, we further propose an RS-aware spatially-varying homogarphy field in the principle of As-Projective-As-Possible (APAP). We show superior performance over state-of-the-art methods both in RS image stitching and rectification, especially for images captured by hand-held shaking cameras.


Rolling Shutter Image rectification Image stitching Differential homography Homography field Hand-held cameras 



We would like to thank Buyu Liu, Gaurav Sharma, Samuel Schulter, and Manmohan Chandraker for proofreading and support of this work. We are also grateful to all the reviewers for their constructive suggestions.

Supplementary material

Supplementary material 1 (mp4 25969 KB)

Supplementary material 2 (mp4 33927 KB)

504444_1_En_15_MOESM3_ESM.pdf (16.2 mb)
Supplementary material 3 (pdf 16598 KB)


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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.NEC Labs AmericaPrincetonUSA

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