Journal ArticleDOI
Coupled HMM-based multi-sensor data fusion for sign language recognition
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TLDR
A novel multi-sensor fusion framework for Sign Language Recognition (SLR) using Coupled Hidden Markov Model (CHMM), which provides interaction in state-space instead of observation states as used in classical HMM that fails to model correlation between inter-modal dependencies.About:
This article is published in Pattern Recognition Letters.The article was published on 2017-01-15. It has received 171 citations till now. The article focuses on the topics: Sign language & Hidden Markov model.read more
Citations
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Journal ArticleDOI
Analysis of EEG signals and its application to neuromarketing
TL;DR: A predictive modeling framework to understand consumer choice towards E-commerce products in terms of “likes’ and “dislikes” by analyzing EEG signals is proposed and the framework can be used for better business model.
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A Modified LSTM Model for Continuous Sign Language Recognition Using Leap Motion
TL;DR: A modified long short-term memory (LSTM) model for continuous sequences of gestures or continuous SLR that recognizes a sequence of connected gestures based on splitting of continuous signs into sub-units and modeling them with neural networks is proposed.
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Review of Three-Dimensional Human-Computer Interaction with Focus on the Leap Motion Controller
TL;DR: The purpose of this paper is to survey the state-of-the-art Human-Computer Interaction techniques with a focus on the special field of three-dimensional interaction, including an overview of currently available interaction devices, their applications of usage and underlying methods for gesture design and recognition.
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Fusion of EEG response and sentiment analysis of products review to predict customer satisfaction
TL;DR: Experimental results suggest that the proposed ABC optimization approach can achieve lower Root Mean Square Error (RMSE) in rating prediction as compared to individual unimodal schemes.
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Sign Language Recognition Systems: A Decade Systematic Literature Review
Ankita Wadhawan,Parteek Kumar +1 more
TL;DR: This is the first identifiable academic literature review of sign language recognition systems and provides an academic database of literature between the duration of 2007–2017 and proposes a classification scheme to classify the research articles.
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.
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A Novel Connectionist System for Unconstrained Handwriting Recognition
TL;DR: This paper proposes an alternative approach based on a novel type of recurrent neural network, specifically designed for sequence labeling tasks where the data is hard to segment and contains long-range bidirectional interdependencies, significantly outperforming a state-of-the-art HMM-based system.
Journal ArticleDOI
Enhanced Computer Vision With Microsoft Kinect Sensor: A Review
TL;DR: A comprehensive review of recent Kinect-based computer vision algorithms and applications covering topics including preprocessing, object tracking and recognition, human activity analysis, hand gesture analysis, and indoor 3-D mapping.
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
Analysis of the Accuracy and Robustness of the Leap Motion Controller
TL;DR: Using the conclusion of this analysis can improve the development of applications for the Leap Motion controller in the field of Human-Computer Interaction.