Order-One Rolling Shutter Cameras
This work addresses a critical gap in computer vision for consumer and smartphone cameras, providing foundational tools for relative pose estimation, though it is incremental in building on existing absolute pose methods.
The paper tackled the unsolved relative pose problem for rolling shutter cameras by developing a unified theory for order-one rolling shutter (RS$_1$) cameras, which generalize perspective projection to rational maps, and discovered new practical minimal problems for solving this problem.
Rolling shutter (RS) cameras dominate consumer and smartphone markets. Several methods for computing the absolute pose of RS cameras have appeared in the last 20 years, but the relative pose problem has not been fully solved yet. We provide a unified theory for the important class of order-one rolling shutter (RS$_1$) cameras. These cameras generalize the perspective projection to RS cameras, projecting a generic space point to exactly one image point via a rational map. We introduce a new back-projection RS camera model, characterize RS$_1$ cameras, construct explicit parameterizations of such cameras, and determine the image of a space line. We classify all minimal problems for solving the relative camera pose problem with linear RS$_1$ cameras and discover new practical cases. Finally, we show how the theory can be used to explain RS models previously used for absolute pose computation.