The study aimed to shed light on the use of gesture in resolving lexical ambiguity employed by TEFL students. To this end, 60 intermediate Iranian learners, studying at Kish Way Language School in Iran were recruited. The participants were randomly put into two experimental groups and one control group. Both of the experimental groups received the same teaching approach, i.e. teaching homonyms ...

The hand gesture input systems will be adopted for use in many applications anytime and anywhere. In this research, a stating notification when and where a user can start using hand gestures for input are focused. However existing devices and systems could be used only in certain situations because of safety issues and the limitations of the devices. In this paper, a Wireless Nail Gesture Syste...

In this study, we introduce a novel variant and application of the Collaborative Representation based Classification in spectral domain for recognition of the hand gestures using the raw surface Electromyography signals. The intuitive use of spectral features are explained via circulant matrices. The proposed Spectral Collaborative Representation based Classification (SCRC) is able to recognize...

As part of our work on hand gesture interpretation, we present our results on hand shape recognition. Our method is based on attribute extraction and multiple binary SVM classification. The novelty lies in the fashion the fusion of all the partial classification results are performed. This fusion is (1) more efficient in terms of information theory and leads to more accurate result, (2) general...

Virtual Environment (VE) system offers a natural and intelligent user interface. Hand gesture recognition is more efficient and easier interaction in VE than human-computer interface (HCI) devices like keyboards and mouses. We propose a hand gesture recognition interface that generates commands to control objects directly in a game. Our novel hand gesture recognition system utilizes both Bag-of...

In this paper, we introduce a hand gesture recognition system to recognize real time gesture in unconstrained environments. The system consists of three modules: real time hand tracking, training gesture and gesture recognition using pseudo two dimension hidden Markov models (P2-DHMMs). We have used a Kalman filter and hand blobs analysis for hand tracking to obtain motion descriptors and hand ...

Hand gestures are widely used in music education. The applied gesture set is well defined since the XIX. century and contains a small number of gestures only. We present a fast and robust method for recognizing solfège hand signs with smart glasses in egocentric perspective. Our method achieves above 95% classification rate and close to real time performance running on an unmodified Google Glas...

This paper presents a new method for detecting and classifying a predefined set of hand gestures using a single transmitter and a single receiver utilizing a linearly frequency modulated ultrasonic signal. Gestures are identified based on estimated range and received signal strength (RSS) of reflected signal from the hand. Support Vector Machine (SVM) was used for gesture detection and classifi...

The objective of this paper is to recognize gestures in videos – both localizing the gesture and classifying it into one of multiple classes. We show that the performance of a gesture classifier learnt from a single (strongly supervised) training example can be boosted significantly using a ‘reservoir’ of weakly supervised gesture examples (and that the performance exceeds learning from the one...

The Kinect camera is widely used for capturing human body images and human motion recognition in video game playing, and there are already some research works on gesture recognition. However, to achieve the anti-interference performance, the current recognition algorithms are often complex and tardiness, and most of the applications are based on the incomplete gesture library and not all hand g...