Journal ArticleDOI
Recognition of dynamic hand gestures
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TLDR
A recognition engine is developed which can reliably recognize these gestures despite individual variations and has the ability to detect start and end of gesture sequences in an automated fashion.About:
This article is published in Pattern Recognition.The article was published on 2003-09-01. It has received 167 citations till now. The article focuses on the topics: Gesture recognition & Pattern recognition (psychology).read more
Citations
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DissertationDOI
Real-time hand gesture detection and recognition for human computer interaction
TL;DR: This thesis focuses on bare hand gesture recognition by proposing a new architecture to solve the problem of real-time vision-based hand detection, tracking, and gesture recognition for interaction with an application via hand gestures.
Proceedings ArticleDOI
Real-Time hand Gesture Recognition Using Pseudo 3-D Hidden Markov Model
Nguyen Dang Binh,Toshiaki Ejima +1 more
TL;DR: A new approach to recognition of hand gesture based on pseudo three-dimensional hidden Markov model (P3DHMM), a technique which can integrate spatial as well as temporal derived features in an elegant and efficient way is presented.
Journal ArticleDOI
Fusing shape and spatio-temporal features for depth-based dynamic hand gesture recognition
TL;DR: Experimental results show that the proposed fusion scheme, DLEH2, for depth-based dynamic hand gesture recognition outperforms the state-of-the-art methods.
Proceedings ArticleDOI
Dynamic hand gesture recognition for human-robot and inter-robot communication
TL;DR: This paper uses a Bag-of- features and a local part model approach for bare hand dynamic hand gesture recognition from video and uses the same approach for inter-robot communication by using two sample hand models.
Proceedings ArticleDOI
Graph matching based hand posture recognition using neuro-biologically inspired features
TL;DR: An elastic graph matching algorithm using biologically inspired features is proposed for the recognition of hand postures and provided better recognition accuracy compared to the reported results in the literature.
References
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Journal ArticleDOI
A tutorial on hidden Markov models and selected applications in speech recognition
TL;DR: In this paper, the authors provide an overview of the basic theory of hidden Markov models (HMMs) as originated by L.E. Baum and T. Petrie (1966) and give practical details on methods of implementation of the theory along with a description of selected applications of HMMs to distinct problems in speech recognition.
Journal ArticleDOI
Active shape models—their training and application
TL;DR: This work describes a method for building models by learning patterns of variability from a training set of correctly annotated images that can be used for image search in an iterative refinement algorithm analogous to that employed by Active Contour Models (Snakes).
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.
Proceedings ArticleDOI
Real-time American Sign Language recognition from video using hidden Markov models
Thad Starner,Alex Pentland +1 more
TL;DR: A real-time HMM-based system for recognizing sentence level American Sign Language (ASL) which attains a word accuracy of 99.2% without explicitly modeling the fingers.
Journal ArticleDOI
An HMM-based threshold model approach for gesture recognition
Hyeon-Kyu Lee,Jin Hyung Kim +1 more
TL;DR: A new method is developed using the hidden Markov model (HMM) based technique that calculates the likelihood threshold of an input pattern and provides a confirmation mechanism for the provisionally matched gesture patterns.