This paper presents a novel technique for hand gesture recognition through human–computer interaction based on shape analysis. The main objective of this effort is to explore the utility of a neural network-based approach to the recognition of the hand gestures. A unique multi-layer perception of neural network is built for classification by using backpropagation learning algorithm. The goal of...

Humans perform iconic gestures to refer to entities through embodying their shapes. For instance, people often gesture the outline of an object (e.g. a circle for a ball) when referring to it during communication. In this paper, we present a gesture-based object recognition algorithm that enables natural human-computer interaction involving iconic gestures. Based on our analysis of multiple ges...

We propose a gesture recognition system based primarily on a single 3-axis accelerometer. The system employs dynamic time warping and affinity propagation algorithms for training and utilizes the sparse nature of the gesture sequence by implementing compressive sensing for gesture recognition. A dictionary of 18 gestures or classes is defined and a database of over 3,700 repetitions is created ...

Creating gestural recognition system is a challenging task which requires skills and updated applications. It is required for designer to be skillful and innovative in order to create interesting and acceptable gestures. Gesture Recognition Design Toolkit (GRDT) is set of tools designed to simplify the gesture creation process for non experts. From designing a new gesture, to suggesting the bes...

This paper describes the primary and secondary driving task together with Human Machine Interface (HMI) trends and issues which are driving automotive user interface designers to consider hand gesture recognition as a realistic alternative for user controls. A number of hand gesture recognition technologies and applications for Human Vehicle Interaction (HVI) are also discussed including a summ...

The use of hand gesture provides an attractive alternative to cumbersome interface devices for human-computer interactio n(HCI). Many methods for hand gesture recognition using visual analysis have been proposed such as syntactical analysis, neural network(NN), Hidden Markov Model(HMM) and so on. In our research, a HMM is proposed for alphabetical hand gesture recognition. In the preprocessing ...

In this paper, we report a real-time gesture driven interactive system with multimodal feedback for performing arts, especially dance. The system consists of two major parts: a gesture recognition engine and a multimodal feedback engine. The gesture recognition engine provides real-time recognition of the performer’s gesture based on the 3D marker coordinates from a marker-based motion capture ...

The use of human hand as a natural interface for humancomputer interaction (HCI) serves as the motivation for research in hand gesture recognition. Vision-based hand gesture recognition involves visual analysis of hand shape, position and/or movement. In this paper, we use the concept of object-based video abstraction for segmenting the frames into video object planes (VOPs), as used in MPEG-4,...

With the increasing role of computing devices, facilitating natural human computer interaction (HCI) will have a positive impact on their usage and acceptance as a whole. For long time, research on HCI has been restricted to techniques based on the use of keyboard, mouse, etc. Recently, this paradigm has changed. Techniques such as vision, sound, speech recognition allow for much richer form of...

Gesture recognition is key to enabling natural human-computer interactions. Existing approaches based on wireless sensing focus accurate identification of arm gesture types. It remains a challenge recognize and profile the details gestures for precise interaction control. In addition, current have strict positioning requirements between radars users, making them difficult real-world deployment....