In this paper, a novel gesture spotting and recognition technique is proposed to handle hand gesture from continuous hand motion based on Conditional Random Fields in conjunction with Support Vector Machine. Firstly, YCbCr color space and 3D depth map are used to detect and segment the hand. The depth map is to neutralize complex background sense. Secondly, 3D spatio-temporal features for hand ...

Sign Language Recognition is one of the most growing fields of research today. Many new techniques have been developed recently in these fields. Here in this paper, we have proposed a system using Eigen value weighted Euclidean distance as a classification technique for recognition of various Sign Languages of India. The system comprises of four parts: Skin Filtering, Hand Cropping, Feature Ext...

Gesture is one of the most natural and expressive ways of communications between human and computer in a real system. We naturally use various gestures to express our own intentions in everyday life. Hand gesture is one of the important methods of non-verbal communication for human beings. Hand gesture recognition based man-machine interface is being developed vigorously in recent years. This p...

with the rapid emergence of 3d applications and virtual environments in computer systems; the need for a new type of interaction device arises. this is because the traditional devices such as mouse, keyboard, and joystick become inefficient and cumbersome within these virtual environments. in other words, evolution of user interfaces shapes the change in the human-computer interaction (hci). in...

In this paper, we introduce a hand gesture recognition system to recognize continuous gesture before stationary background. The system consists of four modules: a real time hand tracking and extraction, feature extraction, hidden Markov model (HMM) training, and gesture recognition. First, we apply a real-time hand tracking and extraction algorithm to trace the moving hand and extract the hand ...

The gesture recognition process, in general, may be divided into two stages: motion sensing, which extracts useful data from hand motion; and the classification process, which classifies the motion sensing data as gestures. We have developed the visionbased Hand Motion Understanding (HMU) system that recognises static and dynamic Australian Sign Language (Auslan) signs by extracting and classif...

When giving descriptions, speakers often signify object shape or size with hand gestures. Such so-called ‘iconic’ gestures represent their meaning through their relevance to referents in the verbal content, rather than having a conventional form. The gesture form on its own is often ambiguous, and the aspect of the referent that it highlights is constrained by what the language makes salient. W...

Recently, we have witnessed dramatic improvements in processing speeds and visualization displays. Yet input devices for the most part have lagged behind, presenting a bottleneck in applications that require a human operator in the processing loop. In this paper a review of vision-based hand gestures for human computer interaction is presented. The emphasis of the review as well as the commenta...

In this paper, we propose a micro hand gesture recognition system using ultrasonic active sensing, which uses micro dynamic hand gestures within a time interval for classification and recognition to achieve Human-Computer Interaction (HCI). The implemented system called Hand-Ultrasonic-Gesture (HUG) consists of ultrasonic active sensing, pulsed radar signal processing, and time-sequence pattern...

A gesture-based interface involves tracking a moving hand across frames, and extracting the semantic interpretation corresponding to the gesture. This is a difficult task, since there is a change in both the position as well as the appearance of the hand. Further, such a system should be robust to the speed at which the gesture is performed. This paper presents a novel attempt at developing a h...