eprintid: 10206662 rev_number: 7 eprint_status: archive userid: 699 dir: disk0/10/20/66/62 datestamp: 2025-03-28 14:50:03 lastmod: 2025-03-28 14:50:03 status_changed: 2025-03-28 14:50:03 type: article metadata_visibility: show sword_depositor: 699 creators_name: Xue, Bohuan creators_name: Zhu, Yilong creators_name: Liu, Tianyu creators_name: Wu, Jin creators_name: Jiao, Jianhao creators_name: Jiang, Yi creators_name: Zhang, Chengxi creators_name: Jiang, Xinyu creators_name: He, Zhijian title: sQPEP: Global Optimal Solutions to Scaled Quadratic Pose Estimation Problems ispublished: inpress divisions: UCL divisions: B04 divisions: F48 keywords: Calibration, pose estimation, Grobner basis, ¨ polynomial note: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. abstract: State estimation encounters significant hurdles in scale ambiguity, both when assimilating data from scale-uninformed sources such as Structure from Motion (SfM) and when handling normalized point clouds, each scenario demanding robust solutions to achieve consistent scale and accurate estimation. Addressing this critical issue, we propose the Scaled Quadratic Pose Estimation Problem (sQPEP), a novel unified framework designed to enhance scale estimation in various state estimation algorithms. Our framework not only establishes a globally optimal solution strategy for the precise estimation of pose and scale factors but also systematically categorizes a broad spectrum of pose estimation challenges. This is crucial for advancing our theoretical understanding and the practical application of these solutions. The sQPEP framework consolidates a range of scale and pose estimation challenges into a unified theoretical paradigm, thereby refining the methodology for these estimations. By applying algebraic techniques, we have effectively bifurcated the problem into two distinct categories. Subsequently, we have deduced globally optimal solutions and unveiled two robust solvers. These solvers are proficient in generating 80 and 81 solutions for their respective problem classes, featuring elimination template dimensions of 664×744 and 521×602. Our method’s efficacy has been rigorously confirmed through experimental validation, which demonstrates its consistent performance in degenerate conditions and its superior noise immunity. These results bolster the framework’s applicability to intricate scenarios encountered in real-world settings. date: 2025-02-24 date_type: published publisher: Institute of Electrical and Electronics Engineers (IEEE) official_url: https://doi.org/10.1109/tim.2025.3540135 oa_status: green full_text_type: other language: eng primo: open primo_central: open_green verified: verified_manual elements_id: 2368649 doi: 10.1109/TIM.2025.3540135 lyricists_name: Jiao, Jianhao lyricists_id: JJIAO94 actors_name: Flynn, Bernadette actors_id: BFFLY94 actors_role: owner full_text_status: public publication: IEEE Transactions on Instrumentation and Measurement issn: 0018-9456 citation: Xue, Bohuan; Zhu, Yilong; Liu, Tianyu; Wu, Jin; Jiao, Jianhao; Jiang, Yi; Zhang, Chengxi; ... He, Zhijian; + view all <#> Xue, Bohuan; Zhu, Yilong; Liu, Tianyu; Wu, Jin; Jiao, Jianhao; Jiang, Yi; Zhang, Chengxi; Jiang, Xinyu; He, Zhijian; - view fewer <#> (2025) sQPEP: Global Optimal Solutions to Scaled Quadratic Pose Estimation Problems. IEEE Transactions on Instrumentation and Measurement 10.1109/TIM.2025.3540135 <https://doi.org/10.1109/TIM.2025.3540135>. (In press). Green open access document_url: https://discovery.ucl.ac.uk/id/eprint/10206662/1/sQPEP_Global_Optimal_Solutions_to_Scaled_Quadratic_Pose_Estimation_Problems.pdf