In this study we introduce and demystify a novel signal pattern recognition method, Spectral Collaborative Representation based Classification (SCRC) and demonstrate its application for recognition of hand gestures and postures using Electromyography sensors. A recently released Thalmic Labs MYO armband is used to gather muscle electromyography signals. Along with the new signal pattern classif...

Hand gesture is an active area of research in the vision community, mainly for the purpose of sign language recognition and Human Computer Interaction. In this paper, we propose a system to recognize alphabet characters (A-Z) and numbers (0-9) in real-time from stereo color image sequences using Hidden Markov Models (HMMs). Our system is based on three main stages; automatic segmentation and pr...

A hand posture recognition system using 3D data is described. The system relies on a novel 3D sensor that generates a dense range image of the scene. The main advantage of the proposed system, compared to other gesture recognition techniques, is the capability for robust unconstrained recognition of complex hand postures such as those encountered in sign language alphabets. This is achieved by ...

This paper gives an improved gesture recognition algorithm. First, obtain the complete hand-type region of the image, using the image preprocess algorithm such as YUV color segmentation, image differencing, connected domain detection. Then process images through contour detection, have the feature extraction and compression by LBP transform and principal component analysis. Finally, use support...

Every day number of images are generated which implies the necessity to classify, organise and access them using an easy, faster and efficient way. The classification of images into semantic categories is a challenging and important problem now days. Thus hand gesture image detection and recognition is also difficult task. In this paper a novel system which can be used for sign language recogni...

The following paper develops the theories and methods used in a gesture recognition system implemented as a human-computer interface (HCI). The gesture recognition system recognizes four fundamental static hand gestures and variations for a total of nine gestures. The system uses a variation of the CAMSHIFT algorithm for hand tracking and a minimum distance classifier for classification. The Wi...

As the integration of digital cameras within personal computing devices becomes a major trend, a real opportunity exists to develop more natural Human-Computer Interfaces that rely on user gestures. In this work, we present a system that acquires and classifies users’ hand gestures from images and videos. Using inputs from low resolution off-the-shelf web cameras, our algorithm identifies the l...

This paper presents a new approach to the problem of gesture recognition in real time using inexpensive accelerometers. This approach is based on the idea of creating specialized signal predictors for each gesture class. These signal predictors forecast future acceleration values from current ones. The errors between the measured acceleration of a given gesture and the predictors are used for c...

View based representations have become very popular for recognition tasks. In this contribution, we argue that the potential of the approach is not yet fully tapped: Tasks need not to be “homogeneous”, i.e. there is no need to restrict a system e.g. to either “object classification” or “gesture recognition”. Instead, qualitatively different problems like gesture recognition and scene evaluation...