Feature Fusion for 3D Hand Gesture Recognition by Learning a Shared Hidden Space | |
Cheng, Jun; Xie, Can; Bian, Wei | |
刊名 | PATTERN RECOGNITION LETTERS
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2012 | |
英文摘要 | Hand gesture recognition has been intensively applied in various human–computer interaction (HCI) sys- tems. Different hand gesture recognition methods were developed based on particular features, e.g., ges- ture trajectories and acceleration signals. However, it has been noticed that the limitation of either features can lead to flaws of a HCI system. In this paper, to overcome the limitations but combine the merits of both features, we propose a novel feature fusion approach for 3D hand gesture recognition. In our approach, gesture trajectories are represented by the intersection numbers with randomly gener- ated line segments on their 2D principal planes, acceleration signals are represented by the coefficients of discrete cosine transformation (DCT). Then, a hidden space shared by the two features is learned by using penalized maximum likelihood estimation (MLE). An iterative algorithm, composed of two steps per iter- ation, is derived to for this penalized MLE, in which the first step is to solve a standard least square prob- lem and the second step is to solve a Sylvester equation. We tested our hand gesture recognition approach on different hand gesture sets. Results confirm the effectiveness of the feature fusion method. |
收录类别 | SCI |
原文出处 | http://www.sciencedirect.com/science/article/pii/S016786551000406X |
语种 | 英语 |
内容类型 | 期刊论文 |
源URL | [http://ir.siat.ac.cn:8080/handle/172644/3731] ![]() |
专题 | 深圳先进技术研究院_集成所 |
作者单位 | PATTERN RECOGNITION LETTERS |
推荐引用方式 GB/T 7714 | Cheng, Jun,Xie, Can,Bian, Wei. Feature Fusion for 3D Hand Gesture Recognition by Learning a Shared Hidden Space[J]. PATTERN RECOGNITION LETTERS,2012. |
APA | Cheng, Jun,Xie, Can,&Bian, Wei.(2012).Feature Fusion for 3D Hand Gesture Recognition by Learning a Shared Hidden Space.PATTERN RECOGNITION LETTERS. |
MLA | Cheng, Jun,et al."Feature Fusion for 3D Hand Gesture Recognition by Learning a Shared Hidden Space".PATTERN RECOGNITION LETTERS (2012). |
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