Proceedings ArticleDOI
Parallel hidden Markov models for American sign language recognition
Christian Vogler,Dimitris N. Metaxas +1 more
- Vol. 1, pp 116-122
TLDR
A novel approach to ASL recognition that aspires to being a solution to the scalability problems, based on parallel HMMs (PaHMMs), which model the parallel processes independently and can be trained independently, and do not require consideration of the different combinations at training time.Citations
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Journal ArticleDOI
Hand and Mind: What Gestures Reveal about Thought
TL;DR: McNeill as discussed by the authors discusses what Gestures reveal about Thought in Hand and Mind: What Gestures Reveal about Thought. Chicago and London: University of Chicago Press, 1992. 416 pp.
Journal ArticleDOI
A Unified Framework for Gesture Recognition and Spatiotemporal Gesture Segmentation
TL;DR: A unified framework for simultaneously performing spatial segmentation, temporal segmentsation, and recognition is introduced and can be applied to continuous image streams where gestures are performed in front of moving, cluttered backgrounds.
Journal ArticleDOI
A survey on activity recognition and behavior understanding in video surveillance
TL;DR: This paper provides an overview of benchmark databases for activity recognition, the market analysis of video surveillance, and future directions to work on for this application.
Journal ArticleDOI
A review of hand gesture and sign language recognition techniques
TL;DR: A thorough review of state-of-the-art techniques used in recent hand gesture and sign language recognition research, suitably categorized into different stages: data acquisition, pre-processing, segmentation, feature extraction and classification.
Journal ArticleDOI
A Framework for Recognizing the Simultaneous Aspects of American Sign Language
TL;DR: This paper presents a novel framework to ASL recognition that aspires to being a solution to the scalability problems, based on breaking down the signs into their phonemes and modeling them with parallel hidden Markov models.
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.
Book
Hand and Mind: What Gestures Reveal about Thought
TL;DR: McNeill et al. as mentioned in this paper argue that gestures do not simply form a part of what is said and meant but have an impact on thought itself, and that gestures are global, synthetic, idiosyncratic, and imagistic.
Journal ArticleDOI
Factorial Hidden Markov Models
TL;DR: A generalization of HMMs in which this state is factored into multiple state variables and is therefore represented in a distributed manner, and a structured approximation in which the the state variables are decoupled, yielding a tractable algorithm for learning the parameters of the model.
Proceedings ArticleDOI
Coupled hidden Markov models for complex action recognition
TL;DR: Algorithms for coupling and training hidden Markov models (HMMs) to model interacting processes, and demonstrate their superiority to conventional HMMs in a vision task classifying two-handed actions are presented.
Journal ArticleDOI
Hand and Mind: What Gestures Reveal about Thought
TL;DR: McNeill as discussed by the authors discusses what Gestures reveal about Thought in Hand and Mind: What Gestures Reveal about Thought. Chicago and London: University of Chicago Press, 1992. 416 pp.
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Real-time American Sign Language recognition from video using hidden Markov models
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