{"ID":5443791,"CreatedAt":"2026-07-01T02:07:11.383974684Z","UpdatedAt":"2026-07-03T14:41:59.01997188Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2606.31760","arxiv_id":"2606.31760","title":"Estimating Velocity and Spin of Spherical Objects from Rolling-Shutter Image(s)","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.","short_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 vel...","url_abs":"https://arxiv.org/abs/2606.31760","url_pdf":"https://arxiv.org/pdf/2606.31760v1","authors":"[\"Wenjie Xue\",\"Jun Yang\",\"Jingmin Wang\",\"Limin Shang\"]","published":"2026-06-30T14:49:26Z","proceeding":"cs.CV","tasks":"[\"cs.CV\"]","methods":"[]","has_code":false}