0533751 20250123092348.520201102235959.9 85094851129 000620679507006 10.1109/CVPR42600.2020.00681 Sub-Frame Appearance and 6D Pose Estimation of Fast Moving Objects 9 s. E cav_un_epca*0533750978-1-7281-7169-21063-69192020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)6777-6785PiscatawayIEEE2020 tracking deblurring matting deblatting cav_un_auth*0352947 Rozumnyi D. CZ cav_un_auth*0293863 Kotera Jan UTIA-B Zpracování obrazové informace Department of Image Processing ZOI ZOI Department of Image Processing CZ Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0101209 Šroubek Filip UTIA-B Zpracování obrazové informace Department of Image Processing ZOI ZOI Department of Image Processing Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0075799 Matas J. CZ pdf http://library.utia.cas.cz/separaty/2020/ZOI/sroubek-0533751.pdf 1MB GA18-05360S GA ČR cav_un_auth*0361425 We have proposed a method for sub-frame appearance and 6D pose estimation of fast moving objects. We propose a novel method that tracks fast moving objects, mainly non-uniform spherical, in full 6 degrees of freedom, estimating simultaneously their 3D motion trajectory, 3D pose and object appearance changes with a time step that is a fraction of the video frame exposure time. The sub-frame object localization and appearance estimation allows realistic temporal super-resolution and precise shape estimation. The method, called TbD-3D (Tracking by Deblatting in 3D) relies on a novel reconstruction algorithm which solves a piece-wise deblurring and matting problem. The 3D rotation is estimated by minimizing the reprojection error. As a second contribution, we present a new challenging dataset with fast moving objects that change their appearance and distance to the camera. High-speed camera recordings with zero lag between frame exposures were used to generate videos with different frame rates annotated with ground-truth trajectory and pose. cav_un_auth*0398417 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 20200616 20200618 Seattle US JD 20000 20200 20206 2021 4 4 A sml 4as 20231122145221.1 PO RVO:67985556 http://hdl.handle.net/11104/0312101 S IEEE COPYRIGHT AND CONSENT FORM 20200311 8.073 Q1* 2020 Soubory v repozitáři: sroubek-0533751-CopyrightReceipt1.pdf 85094851129 SCOPUS PUBMED 000620679507006 WOS pdf 1MB cav_un_epca*0533750 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) IEEE 2020 Piscataway 6777 6785 978-1-7281-7169-2 1063-6919 2575-7075