Proceedings ArticleDOI
Human Computer Interaction for Vision Based Hand Gesture Recognition: A Survey
Haitham Hasan,S. Abdul Kareem +1 more
- pp 55-60
TLDR
This paper provides a summary of previous surveys done in this area and focuses on the different application domain which employs hand gestures for efficient interaction, and provides an analysis of existing literature related to gesture recognition systems for human computer interaction by categorizing it based on different parameters.Abstract:
The ultimate aim is to bring Human Computer Interaction to a regime where interactions with computers will be as natural as an interaction between humans, and to this end, incorporating gestures in HCI is an important research area Gestures have long been considered as an interaction technique that can potentially deliver more natural, creative and intuitive methods for communicating with our computers This paper provides a summary of previous surveys done in this area and focuses on the different application domain which employs hand gestures for efficient interaction The use of hand gestures as a natural interface serves as a motivating force for research in gesture taxonomies, its representations and recognition techniques Also provides an analysis of existing literature related to gesture recognition systems for human computer interaction by categorizing it based on different parameters The main goal of this survey is to provide researchers in the field with a summary of progress achieved to date and to help identify areas where further research is neededread more
Citations
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Journal ArticleDOI
Hand gesture recognition based on convolution neural network
Gongfa Li,Tang Heng,Ying Sun,Jianyi Kong,Guozhang Jiang,Du Jiang,Bo Tao,Xu Shuang,Honghai Liu +8 more
TL;DR: The characteristics of convolution neural network are used to avoid the feature extraction process, reduce the number of parameters needs to be trained, and finally achieve the purpose of unsupervised learning.
Journal ArticleDOI
CNN based feature extraction and classification for sign language
TL;DR: This paper applies deep learning-based convolutional neural networks (CNNs) for robust modeling of static signs in the context of sign language recognition and highlights the recognition accuracy of each character, and their similarities with identical gestures.
Book ChapterDOI
A Survey of Datasets for Human Gesture Recognition
TL;DR: This survey should be a key-access point for researchers looking to create or use datasets in the field of human gesture recognition.
Journal ArticleDOI
A dynamic gesture recognition and prediction system using the convexity approach
Pablo Barros,Nestor T. Maciel-Junior,Bruno J. T. Fernandes,Byron L. D. Bezerra,Sergio Murilo Maciel Fernandes +4 more
TL;DR: This study proposes a system for dynamic gesture recognition and prediction using an innovative feature extraction technique, called the Convexity Approach, which generates a smaller feature vector to describe the hand shape with a minimal amount of data.
Proceedings ArticleDOI
Gesture recognition using DTW & piecewise DTW
TL;DR: Experiments and evaluation on a subset of American Sign Language (ASL) hand gesture show that, by using Dynamic Time Warping hand gesture can be classified, and it is estimated that Piecewise DTW can be efficiently used to speed up the computations of DTW.
References
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Journal ArticleDOI
Visual interpretation of hand gestures for human-computer interaction: a review
TL;DR: A fraction of the recycle slurry is treated with sulphuric acid to convert at least some of the gypsum to calcium sulphate hemihydrate and the slurry comprising hemihYDrate is returned to contact the mixture of phosphate rock, phosphoric acid and recycle Gypsum slurry.
Journal ArticleDOI
A Survey of Computer Vision-Based Human Motion Capture
Thomas B. Moeslund,Erik Granum +1 more
TL;DR: A comprehensive survey of computer vision-based human motion capture literature from the past two decades is presented, with a general overview based on a taxonomy of system functionalities, broken down into four processes: initialization, tracking, pose estimation, and recognition.
Journal ArticleDOI
Gesture Recognition: A Survey
Sushmita Mitra,T. Acharya +1 more
TL;DR: A survey on gesture recognition with particular emphasis on hand gestures and facial expressions is provided, and applications involving hidden Markov models, particle filtering and condensation, finite-state machines, optical flow, skin color, and connectionist models are discussed in detail.
Journal ArticleDOI
Evaluation of a threshold-based tri-axial accelerometer fall detection algorithm.
TL;DR: Using simulated falls performed under supervised conditions and activities of daily living performed by elderly subjects, the ability to discriminate between falls and ADL was investigated using tri-axial accelerometer sensors, mounted on the trunk and thigh.
Journal ArticleDOI
Vision-based hand-gesture applications
TL;DR: Body posture and finger pointing are a natural modality for human-machine interaction, but first the system must know what it's seeing.