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Multi-Branch High-Dimensional Guided Transformer-Based 3D Human Posture Estimation
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作者 Xianhua Li Haohao Yu +2 位作者 Shuoyu Tian Fengtao Lin Usama Masood 《Computers, Materials & Continua》 SCIE EI 2024年第3期3551-3564,共14页
The human pose paradigm is estimated using a transformer-based multi-branch multidimensional directed the three-dimensional(3D)method that takes into account self-occlusion,badly posedness,and a lack of depth data in ... The human pose paradigm is estimated using a transformer-based multi-branch multidimensional directed the three-dimensional(3D)method that takes into account self-occlusion,badly posedness,and a lack of depth data in the per-frame 3D posture estimation from two-dimensional(2D)mapping to 3D mapping.Firstly,by examining the relationship between the movements of different bones in the human body,four virtual skeletons are proposed to enhance the cyclic constraints of limb joints.Then,multiple parameters describing the skeleton are fused and projected into a high-dimensional space.Utilizing a multi-branch network,motion features between bones and overall motion features are extracted to mitigate the drift error in the estimation results.Furthermore,the estimated relative depth is projected into 3D space,and the error is calculated against real 3D data,forming a loss function along with the relative depth error.This article adopts the average joint pixel error as the primary performance metric.Compared to the benchmark approach,the estimation findings indicate an increase in average precision of 1.8 mm within the Human3.6M sample. 展开更多
关键词 key point detection 3D human posture estimation computer vision deep learning
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A new navigation approach of terrain contour matching based on 3-D terrain reconstruction from onboard image sequence 被引量:5
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作者 LI LiChun1,2,YU QiFeng2,SHANG Yang2,YUAN Yun2,LU HongWei3 & LIU XiaoLin4 1 Beijing Aerospace Control Center,Beijing 100094,China 2 College of Aerospace and Material Engineering,National University of Defense Technology,Changsha 410073,China +1 位作者 3 Equipment Research Institute of PLA’s Second Artillery,Beijing 100085,China 4 College of Mechatronic Engineering and Automation,National University of Defense Technology,Changsha 410073,China 《Science China(Technological Sciences)》 SCIE EI CAS 2010年第5期1176-1183,共8页
This article presents a passive navigation method of terrain contour matching by reconstructing the 3-D terrain from the image sequence(acquired by the onboard camera).To achieve automation and simultaneity of the ima... This article presents a passive navigation method of terrain contour matching by reconstructing the 3-D terrain from the image sequence(acquired by the onboard camera).To achieve automation and simultaneity of the image sequence processing for navigation,a correspondence registration method based on control points tracking is proposed which tracks the sparse control points through the whole image sequence and uses them as correspondence in the relation geometry solution.Besides,a key frame selection method based on the images overlapping ratio and intersecting angles is explored,thereafter the requirement for the camera system configuration is provided.The proposed method also includes an optimal local homography estimating algorithm according to the control points,which helps correctly predict points to be matched and their speed corresponding.Consequently,the real-time 3-D terrain of the trajectory thus reconstructed is matched with the referenced terrain map,and the result of which provides navigating information.The digital simulation experiment and the real image based experiment have verified the proposed method. 展开更多
关键词 TERRAIN CONTOUR matching VISION-BASED NAVIGATION 3-D reconstruction control points key frame registration optimal local HOMOGRAPHY
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