Centroid tracking based dynamic hand gesture recognition using discrete Hidden Markov Models

Premaratne Prashan; Yang Shuai; Vial Peter; Ifthikar Zubair

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Centroid tracking based dynamic hand gesture recognition using discrete Hidden Markov Models

机译：使用离散隐马尔可夫模型的基于质心跟踪的动态手势识别

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摘要

In many dynamic hand gesture recognition contexts, time information is not adequately used. The extracted features of dynamic gestures usually do not carry explicit information about time in gesture classification. This results in under-utilized data for more important accurate classification. Another disadvantage is that the gesture classification is then confined to only simple gestures. We have overcome these limitations by introducing centroid tracking of hand gestures that captures and retains the time sequence information for feature extraction. This simplifies the classification of dynamic gestures as movement in time helps efficient classification without burdensome processing.

机译：在许多动态手势识别上下文中，没有充分使用时间信息。动态手势的提取特征通常不携带有关手势分类中时间的明确信息。这导致数据利用不足，无法进行更重要的准确分类。另一个缺点是手势分类仅限于简单手势。我们通过引入手势的质心跟踪来克服这些限制，该手势捕获并保留了用于特征提取的时间序列信息。这可以简化动态手势的分类，因为及时移动有助于有效的分类而无需繁琐的处理。

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来源
《Neurocomputing》 |2017年第8期|79-83|共5页
作者
Premaratne Prashan; Yang Shuai; Vial Peter; Ifthikar Zubair;
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作者单位

Univ Wollongong, Sch Elect Comp & Telecommun Engn, North Wollongong, NSW 2522, Australia;

Univ Wollongong, Sch Elect Comp & Telecommun Engn, North Wollongong, NSW 2522, Australia;

Univ Wollongong, Sch Elect Comp & Telecommun Engn, North Wollongong, NSW 2522, Australia;

Univ Wollongong, Sch Elect Comp & Telecommun Engn, North Wollongong, NSW 2522, Australia;

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收录信息美国《科学引文索引》(SCI);美国《工程索引》(EI);
原文格式 PDF
正文语种 eng
中图分类
关键词
Dynamic hand gestures; Classification; Skin segmentation; Centroid tracking; Hidden Markov Model;

机译：动态手势;分类;皮肤分割;质心跟踪;隐马尔可夫模型;

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专利

1. Hand gesture recognition using a real-time tracking method and hidden Markov models [J] . Feng-Sheng Chen, Chih-Ming Fu, Chung-Lin Huang Image and Vision Computing . 2003,第8期

机译：使用实时跟踪方法和隐马尔可夫模型进行手势识别
2. Dynamic Hand Gesture Recognition Based on Micro-Doppler Radar Signatures Using Hidden Gauss–Markov Models [J] . Zetao Wang, Gang Li, Le Yang IEEE Geoscience and Remote Sensing Letters . 2021,第2期

机译：基于Micro-Doppler雷达签名的动态手势识别使用隐藏高斯 - 马尔可夫模型
3. Hidden-Markov-Models-Based Dynamic Hand Gesture Recognition [J] . Xiaoyan Wang, Ming Xia, Huiwen Cai, Mathematical Problems in Engineering . 2012,第PTa5期

机译：基于隐马尔可夫模型的动态手势识别
4. Recognition of Hand Gestures Tracked by a Dataglove: Exploiting Hidden Markov Models Discriminative Training and Environment Description to Improve Recognition Performance [C] . Vittorio Lippi, Emanuele Ruffaldi, Carlo Alberto Avizzano, International Workshop on Artificial Neural Networks and Intelligent Information Processing . 2009

机译：识别Dataglove跟踪的手势：利用隐藏的马尔可夫模型鉴别培训和环境描述，以提高识别性能
5. Gesture Recognition using Hidden Markov Models, Dynamic Time Warping, and Geometric Template Matching. [D] . Hunter, Garett. 2013

机译：使用隐马尔可夫模型，动态时间扭曲和几何模板匹配进行手势识别。
6. A Fusion Recognition Method Based on Multifeature Hidden Markov Model for Dynamic Hand Gesture [O] . Guoliang Chen, Kaikai Ge 2020

机译：一种基于Multififure Hidden Markov模型动态手势的融合识别方法
7. Hidden-Markov-Models-Based Dynamic Hand Gesture Recognition [O] . Xiaoyan Wang, Ming Xia, Huiwen Cai, 2012

机译：基于MADID-MARKOV模型的动态手势识别
8. Discrete Hidden Markov Modes with Application to Isolated User-Dependent Hand Gesture Recognition. [R] . Maetylae, V. M. 2001

机译：离散隐马尔可夫模型及其在孤立的用户自主手势识别中的应用。

Centroid tracking based dynamic hand gesture recognition using discrete Hidden Markov Models

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