cs.CVJun 30, 2026

Estimating Velocity and Spin of Spherical Objects from Rolling-Shutter Image(s)

Authors: Wenjie XueJun YangJingmin WangLimin Shang

Organizations: Epson Canada Ltd, Toronto, ON L3R 6G3, Canada · University of Toronto, Toronto, ON M5S 1A1, Canada

Abstract

Rolling-shutter cameras introduce characteristic distortions when imaging fast moving objects, and these effects are typically treated as artifacts to be corrected. In this work, we instead leverage rolling-shutter distortions as a valuable source of temporal information to estimate the 3D translational and angular velocities of rapidly moving spherical objects from a single rolling-shutter frame. We design a robust and easily detectable spherical pattern and propose a correspondence-free formulation that recovers motion by enforcing geometric consistency in a back-projection framework. By exploiting the geometry of the sphere, translational and rotational motions are decoupled and estimated through a two-stage optimization process, enabling reliable velocity recovery even for textureless objects. Extensive experiments on both synthetic and real datasets demonstrate accurate and robust estimation of motion parameters under challenging high-speed conditions.

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