الملخص
Rotational symmetry is an important prior in 6D pose estimation, improving pose accuracy and supporting symmetry-aware evaluation. However, current symmetry annotations for 3D objects remain largely manual or semi-automatic, often requiring predefined types or orders, which limits scalability. This work introduces a fully automatic, reference-free framework for symmetry-type classification, rotational-order identification, and full-axis localization across all eight canonical 3D rotational symmetry types. The method localizes a dominant high-order axis, infers its rotational order through self-consistency analysis, and reconstructs the complete symmetry structure under a hierarchy-guided formulation. A texture-aware extension further models appearance-induced reductions in rotational order while preserving axis orientations. Experiments on idealized and real-world datasets demonstrate strong accuracy and generalization, achieving 94.75% accuracy on 438 symmetric objects in GSO. Training FoundationPose with these priors improves accuracy by up to 0.9% across five BOP datasets, showing that automatically estimated rotational priors improve downstream 6D pose estimation. Code is available at https://github.com/WangYuLin-SEU/KASAL.
الكلمات المفتاحية
بيانات النشر
- المجلة
- غير متاح
- وصول مفتوح
- وصول مفتوح أخضر
اقتبس هذه المقالة
APA 7
Zhang, M., Wang, Y., Luo, C., Li, Y., & Zhou, Y. (2026). KASALv2: Fully Automatic 3D Rotational Symmetry Classification and Axis Localization. https://omanscience.com/ar/articles/kasalv2-fully-automatic-3d-rotational-symmetry-classification-and-axis-localization
MLA 9
Zhang, Mengxin, et al. "KASALv2: Fully Automatic 3D Rotational Symmetry Classification and Axis Localization." https://omanscience.com/ar/articles/kasalv2-fully-automatic-3d-rotational-symmetry-classification-and-axis-localization.
شيكاغو (المؤلف–التاريخ)
Zhang, Mengxin, Yulin Wang, Chen Luo, Yongzhe Li, and Yijun Zhou. 2026. "KASALv2: Fully Automatic 3D Rotational Symmetry Classification and Axis Localization." https://omanscience.com/ar/articles/kasalv2-fully-automatic-3d-rotational-symmetry-classification-and-axis-localization.
هارفارد
Zhang, M., Wang, Y., Luo, C., Li, Y. and Zhou, Y. (2026) 'KASALv2: Fully Automatic 3D Rotational Symmetry Classification and Axis Localization', Available at: https://omanscience.com/ar/articles/kasalv2-fully-automatic-3d-rotational-symmetry-classification-and-axis-localization.
فانكوفر
Zhang M, Wang Y, Luo C, Li Y, Zhou Y. KASALv2: Fully Automatic 3D Rotational Symmetry Classification and Axis Localization. https://omanscience.com/ar/articles/kasalv2-fully-automatic-3d-rotational-symmetry-classification-and-axis-localization
IEEE
M. Zhang, Y. Wang, C. Luo, Y. Li, and Y. Zhou, "KASALv2: Fully Automatic 3D Rotational Symmetry Classification and Axis Localization," https://omanscience.com/ar/articles/kasalv2-fully-automatic-3d-rotational-symmetry-classification-and-axis-localization.