计算机应用与软件2025，Vol.42Issue(6)：193-201,9.DOI:10.3969/j.issn.1000-386x.2025.06.025
基于多特征融合的6D姿态估计
6D POSE ESTIMATION BASED ON MULTI FEATURE FUSION
摘要
Abstract
Aimed at the problem that it is difficult to directly regress the 6D pose of an object from a single RGBD image in a cluttered environment,a pose estimation method of bidirectional fusion of key points is proposed.The method selected key points from RGB images and extracts color dense features,selected key points from point cloud data and extracted geometric dense features,and fused the selected key point features bidirectionally in the encoding stage of two feature extractions,using two data sources complementary information to obtain better feature representation.The experimental results show that the proposed method has significantly improved accuracy compared with the current method,and has strong robustness.关键词
姿态估计/深度学习/特征融合/像素级融合/注意力机制Key words
Pose estimation/Deep learning/Feature fusion/Pixel-level fusion/Attention mechanism分类
信息技术与安全科学引用本文复制引用
徐铭泽,史旭华..基于多特征融合的6D姿态估计[J].计算机应用与软件,2025,42(6):193-201,9.基金项目
国家自然科学基金项目(61773225,61803214). （61773225,61803214）
