Learning a Deep Predictive Coding Network for a Semi-Supervised 3D-Hand Pose Estimation
文献类型：期刊论文
| 作者 | Jamal Banzi; Isack Bulugu; Zhongfu Ye |
| 刊名 | IEEE/CAA Journal of Automatica Sinica
 |
| 出版日期 | 2020 |
| 卷号 | 7期号:5页码:1371-1379 |
| 关键词 | Convolutional neural networks deep learning hand pose estimation human-machine interaction predictive coding recurrent neural networks unsupervised learning |
| ISSN号 | 2329-9266 |
| DOI | 10.1109/JAS.2020.1003090 |
| 英文摘要 | In this paper we present a CNN based approach for a real time 3D-hand pose estimation from the depth sequence. Prior discriminative approaches have achieved remarkable success but are facing two main challenges: Firstly, the methods are fully supervised hence require large numbers of annotated training data to extract the dynamic information from a hand representation. Secondly, unreliable hand detectors based on strong assumptions or a weak detector which often fail in several situations like complex environment and multiple hands. In contrast to these methods, this paper presents an approach that can be considered as semi-supervised by performing predictive coding of image sequences of hand poses in order to capture latent features underlying a given image without supervision. The hand is modelled using a novel latent tree dependency model (LDTM) which transforms internal joint location to an explicit representation. Then the modeled hand topology is integrated with the pose estimator using data dependent method to jointly learn latent variables of the posterior pose appearance and the pose configuration respectively. Finally, an unsupervised error term which is a part of the recurrent architecture ensures smooth estimations of the final pose. Experiments on three challenging public datasets, ICVL, MSRA, and NYU demonstrate the significant performance of the proposed method which is comparable or better than state-of-the-art approaches. |
| 源URL | [http://ir.ia.ac.cn/handle/173211/43039]  |
| 专题 | 自动化研究所_学术期刊_IEEE/CAA Journal of Automatica Sinica |
| 推荐引用方式 GB/T 7714 | Jamal Banzi,Isack Bulugu,Zhongfu Ye. Learning a Deep Predictive Coding Network for a Semi-Supervised 3D-Hand Pose Estimation[J]. IEEE/CAA Journal of Automatica Sinica,2020,7(5):1371-1379. |
| APA | Jamal Banzi,Isack Bulugu,&Zhongfu Ye.(2020).Learning a Deep Predictive Coding Network for a Semi-Supervised 3D-Hand Pose Estimation.IEEE/CAA Journal of Automatica Sinica,7(5),1371-1379. |
| MLA | Jamal Banzi,et al."Learning a Deep Predictive Coding Network for a Semi-Supervised 3D-Hand Pose Estimation".IEEE/CAA Journal of Automatica Sinica 7.5(2020):1371-1379. |
入库方式： OAI收割
来源：自动化研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。