Gesture Recognition has become a way for computers to recognise and understand human body language. They bridge the gap between machines and human beings and make the primitive interfaces like keyboards and mice redundant. This paper suggests a hybrid gesture recognition system for computer interface and wireless robot control. The real-time eye-hand gesture recognition system can be used for c...

The recent popularization of real time depth sensors has diversified the potential applications of online gesture recognition to end-user natural user interface (NUI). This requires significant robustness of the gesture recognition to cope with the noisy data from the popular depth sensor, while the quality of the final NUI heavily depends on the recognition execution speed. This work introduce...

This paper introduced a method of building and fixing a digitalized model of human hand gesture through contour analysis of the hand’s orthographic projection. Via contour analysis the fingers and palm on the projection are located and their quantized characters are calculated. The model is used in a gesture recognition method, where the articulation is of core concern. Thus the method is adapt...

Sensors on mobile devices—accelerometers, gyroscopes, pressure meters, and GPS—invite new applications in gesture recognition, gaming, and fitness tracking. However, programming them remains challenging because human gestures captured by sensors are noisy. This paper illustrates that noisy gestures degrade training and classification accuracy for gesture recognition in state-of-the-art determin...

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 ...

This paper presents a video based system for hand-gesture recognition. It is able to process the video data and to classify the gestures in real time. Even more, there exists a method for gesture tracking and fault tolerant recognition of gesture sequences. By choosing the colour video channel the system is almost independent of light innuence. For demonstration two practical applications of th...

Abstract A two stage real-time hand gesture recognition system is presented. It combines a machine learning trained detection step with colour processing contour shape validation step. The done either Adaboost Cascades or Support Vector Machines using HOG features. achieves low false positive rate and sufficient true necessary for robust performance. performs well compared to MobileNets state o...

Hand gesture recognition has long been a study topic in the field of Human Computer Interaction. Traditional camera-based hand gesture recognition systems can not work properly under dark circumstances. In this paper, a DopplerRadar based hand gesture recognition system using convolutional neural networks is proposed. A cost-effective Doppler radar sensor with dual receiving channels at 5.8GHz ...

Hand Gesture recognition and Human Computer Interaction is an open research problem as the main purpose behind gesture recognition research is to identify a particular human gesture by computer. Hand gesture recognition based man-machine interface is being currently developed and researched upon both by industry and academia. In this paper, we develop a technique for recognizing the gestures ma...

Existing gesture-recognition systems consume significant power and computational resources that limit how they may be used in low-end devices. We introduce AllSee, the first gesture-recognition system that can operate on a range of computing devices including those with no batteries. AllSee consumes three to four orders of magnitude lower power than state-of-the-art systems and can enable alway...