As an emerging human-computer interaction (HCI) technology, recognition of human hand gesture is considered a very powerful means for human intention reading. To construct a system with a reliable and robust hand gesture recognition algorithm, it is necessary to resolve several major difficulties of hand gesture recognition, such as inter-person variation, intra-person variation, and false posi...

Convolutional neural networks (CNNs) have been widely utilized to identify hand gestures from surface electromyography (sEMG) signals. However, due the nonstationary characteristics of sEMG, classification accuracy usually degrades significantly in daily living environment involving complex movements. To further improve reliability a classifier, unconfident classifications are expected be ident...

Mel Frequency Ceptral Coefficient is a very common and efficient technique for signal processing. This paper presents a new purpose of working with MFCC by using it for Hand gesture recognition. The objective of using MFCC for hand gesture recognition is to explore the utility of the MFCC for image processing. Till now it has been used in speech recognition, for speaker identification. The pres...

In some real-world personal identification applications requiring high security standards, multibiometrics can provide higher accuracy than single biometrics. Due to its good performance, palmprint has received a lot of attention among other biometrics technologies. Combining left and right palmprints for is easy implement produce better results. However, previous studies did not explore this i...

A new method for hand gesture recognition is proposed which is based on an innovative Self-Growing and Self-Organized Neural Gas (SGONG) network. Initially, the region of the hand is detected by using a colour segmentation technique that depends on a skin-colour distribution map. Then, the SGONG network is applied on the segmented hand so as to approach its topology. Based on the output grid of...

We have developed a static hand-gesture recognition system for the Human Computer Interaction based on shape analysis. This appearance-based recognition uses modified Fourier descriptors for the classification of hand shapes. Usually systems use two phases: training and running phase under the recognition. A new method is shown that under the running phase of the system users can interactive mo...

In this paper a gesture 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 novelty of the proposed system, with respect to other 3D gesture recognition techniques, is the capability for robust recognition of complex hand postures such as those encountered in sign language alphabets. This is achieved by ...

This paper introduces a fuzzy rule-based method for the recognition of hand gestures acquired from a data glove, with an application to the recognition of some sample hand gestures of LIBRAS, the Brazilian Sign Language. The method uses the set of angles of finger joints for the classification of hand configurations, and classifications of segments of hand gestures for recognizing gestures. The...

Communication in today’s world is performed through the vocal sounds and body language. Vocal sounds are main tool for interaction, where body language and facial expressions also have important support. Even in few cases, interacting with physical world by using expressive movements like gestures and postures is much easier. In this paper, an approach is designed for Upper Body Pose Recognitio...