Gaussian process motion graph models for smooth transitions among multiple actions-Reference-Cited by-同舟云学术

Gaussian process motion graph models for smooth transitions among multiple actions

Published:2012-04 Issue:4 Volume:116 Page:500-509
ISSN:1077-3142
Container-title:Computer Vision and Image Understanding
language:en
Short-container-title:Computer Vision and Image Understanding

Author:

Ukita Norimichi,Kanade Takeo

Publisher

Elsevier BV

Subject

Computer Vision and Pattern Recognition,Signal Processing,Software

Reference34 articles.

1. L. Sigal, M.J. Black, HumanEva: synchronized video and motion capture dataset for evaluation of articulated human motion, Technical Report CS-06-08, Brown University, 2006. .

2. CMU Graphics Lab Motion Capture Database: .

3. Articulated mesh animation from multi-view silhouettes;Vlasic;ACM Transactions on Graphics,2008

4. H. Sidenbladh, M.J. Black, L. Sigal, Implicit probabilistic models of human motion for synthesis and tracking, in: ECCV, 2002.

5. A. Agarwal, B. Triggs, Tracking articulated motion using a mixture of autoregressive models, in: ECCV, 2004.

Cited by 15 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Contrastive disentanglement for self-supervised motion style transfer;Multimedia Tools and Applications;2024-01-30

2. MotionAug: Augmentation with Physical Correction for Human Motion Prediction;2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR);2022-06

3. Data Augmentation for Human Motion Prediction;2021 17th International Conference on Machine Vision and Applications (MVA);2021-07-25

4. Human Pose Annotation Using a Motion Capture System for Loose-Fitting Clothes;IEICE Transactions on Information and Systems;2020-06-01

5. Synthesizing Character Animation with Smoothly Decomposed Motion Layers;Computer Graphics Forum;2019-11-29