Results 261 to 270 of about 8,059 (296)

An Environment for the Specification and Recognition of Dynamic Gestures

Journal of Visual Languages & Computing, 1994
Abstract Novel 3-D input devices are taking the place of traditional 2-D input devices in current 3-D graphical user interfaces. Among them, hand-input devices seem intuitive and powerful for performing tasks in 3-D environments. They offer the possibility to interact by means of hand gestures, i.e.
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Directional Dynamic Time Warping for Gesture Recognition

Proceedings of the 2017 2nd International Conference on Multimedia Systems and Signal Processing, 2017
In this study, we propose a modified dynamic time warping (DTW) algorithm that compares the sequences based on the direction of the gesture's movement. When comparing the gesture sequences, the proposed algorithm compares the movement direction and calculates the difference by the Euclidean Distance, and therefore reflects the characteristics of the ...
Hyo-Rim Choi, TaeYong Kim 0003
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Learning dynamics for exemplar-based gesture recognition

2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings., 2003
This paper addresses the problem of capturing the dynamics for exemplar-based recognition systems. Traditional HMM provides a probabilistic tool to capture system dynamics and in exemplar paradigm, HMM states are typically coupled with the exemplars. Alternatively, we propose a non-parametric HMM approach that uses a discrete HMM with arbitrary states (
Ahmed M. Elgammal, Vinay D. Shet, Yaser Yacoob, Larry S. Davis   +3 more
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Dynamic Gesture Recognition for Social Robots

2017
Interpreting users messages, both verbal and non-verbal is essential to achieve a natural Human-Robot Interaction. Traditionally, Social Robots, and particularly Care Robots, rely on interfaces such as voice, touch or images to acquire information from users although the latter is usually used to locate them.
José Carlos Castillo 0001, David Cáceres-Domínguez, Fernando Alonso-Martín, Álvaro Castro González, Miguel Angel Salichs   +4 more
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Dynamic gesture recognition based on CNN-LSTM-Attention

2021 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC), 2021
Compared with traditional human-computer interaction techniques, gesture recognition is closer to human expression habits and have some advantages of being efficient and easy to master. Vision-based gesture recognition does not require additional equipment, and is very convenient and relatively low cost.
Jinwei Liu, Baoguo Wei, Mingzhi Cai, Yong Xu   +3 more
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Democratizing 3D dynamic gestures recognition

2013 1st IEEE Workshop on User-Centered Computer Vision (UCCV), 2013
Developing vision-based 3D gestures recognition systems requires strong expertise and knowledge in computer vision and machine learning techniques. As human-computer interaction researchers do not generally have a thorough knowledge of these techniques, we developed Gesta.
M. Caon, null Yong Yue, J. Tscherrig, O. A. Khaled, E. Mugellini   +4 more
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Dynamic Hand Gesture Recognition Based On Depth Information

2018 International Conference on Control, Automation and Information Sciences (ICCAIS), 2018
Dynamic hand gesture is consisted by hand movement trajectory and the changes of hand shape. However, some existing methods only focus on the trajectory, and those methods can not accurately recognize the gesture that has the similar trajectory but different hand shape changes.
Xinran Bai, Chen Li 0033, Lihua Tian, Hui Song   +3 more
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The Effect of Static and Dynamic Gesture Presentation on the Recognition of Two Manipulation Gestures

2018
Gesture is an important means of nonverbal communication and used in conveying messages before the advent of language. With the development of computer technology, gesture interaction has become a trend of natural and harmonious human-computer interaction.
Wenyuan Yu, Ye Liu 0010, Xiaolan Fu
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Featureweighting in dynamic timewarping for gesture recognition in depth data

2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops), 2011
We present a gesture recognition approach for depth video data based on a novel Feature Weighting approach within the Dynamic Time Warping framework. Depth features from human joints are compared through video sequences using Dynamic Time Warping, and weights are assigned to features based on inter-intra class gesture variability.
Miguel Reyes, Gabriel Dominguez, Sergio Escalera   +2 more
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Deep Dynamic Neural Networks for Gesture Segmentation and Recognition

2015
The purpose of this paper is to describe a novel method called Deep Dynamic Neural Networks(DDNN) for the Track 3 of the Chalearn Looking at People 2014 challenge [1]. A generalised semi-supervised hierarchical dynamic framework is proposed for simultaneous gesture segmentation and recognition taking both skeleton and depth images as input modules ...
Di Wu 0009, Ling Shao 0001
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