A practical framework of multi-person 3D human pose estimation with a single RGB camera

被引：1
|
作者：
Ma, Le [1 ,4 ]
Lian, Sen [1 ,4 ]
Wang, Shandong [3 ]
Meng, Weiliang [1 ,2 ,4 ,5 ]
Xiao, Jun [1 ]
Zhang, Xiaopeng [1 ,2 ,4 ]
机构：
[1] Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing, Peoples R China
[2] Zhejiang Lab, Hangzhou, Peoples R China
[3] Intel Labs China, Beijing, Peoples R China
[4] Chinese Acad Sci, Inst Automat, NLPR, Beijing, Peoples R China
[5] Chinese Acad Sci, Inst Software, State Key Lab Comp Sci, Beijing, Peoples R China
来源：
2021 IEEE CONFERENCE ON VIRTUAL REALITY AND 3D USER INTERFACES ABSTRACTS AND WORKSHOPS (VRW 2021) | 2021年
基金：
国家重点研发计划; 中国国家自然科学基金;
关键词：
Skeleton; Neural network; Detection; Real-time;
D O I：
10.1109/VRW52623.2021.00092
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
We propose a practical framework named 'DN-2DPN-3DPN' for multi-person 3D pose estimation with a single RGB camera. Our framework performs three-stages tasks on the input video: our DetectNet(DN) firstly detects the people's bounding box individually for each frame of the video, while our 2DPoseNet(2DPN) estimates the 2D poses for each person in the second stage, and our 3DPoseNet(3DPN) is finally applied to obtain the 3D poses of the people. Experiments validate that our method can achieve state-of-the-art performance for multi-person 3D human pose estimation on the Human3.6M dataset.
引用
收藏
页码：420 / 421
页数：2
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