In this paper, we introduce a novel method for view-independent hand pose recognition from depth data. The proposed approach, which does not rely on color information, provides an estimation of the shape and orientation of the user’s hand without constraining him/her to maintain a fixed position in the 3D space. We use principal component analysis to estimate the hand orientation in space, Flus...

Interpretation of human activity is primarily known from surveillance and video analysis tasks and concerned with the persons alone. In this paper we present an integrated system that gives a natural language interpretation of activities where a person handles objects. The system integrates low-level image components such as hand and object tracking, detection and recognition, with high-level p...

A structural representation of the hand embedding information about the identity and relative position of fingers is necessary to counting routines. It may also support associations between numbers and allocentric spatial codes that predictably interact with other known numerical spatial representations, such as the mental number line (MNL). In this study, 48 Western participants whose typical ...

To address the problems of low feature extraction accuracy, large bias human motion pose recognition and posture error, poor effect, rate traditional fast algorithm, we propose a algorithm using multimodal bioinformation fusion. First, wavelet packet decomposition with sample entropy is used to extract hand features such as kurtosis, time domain skewness, frequency electromyogram (EMG) integral...

We present an appearance-based 3D hand posture estimation method that determines a ranked set of possible hand posture candidates from an unmarked hand image, based on an analysis by synthesis method and an image retrieval algorithm. We formulate the posture estimation problem as a nonlinear, many-to-many mapping problem in a high dimension space. A general algorithm called ISOSOM is proposed f...

This paper presents a model for Gesture controlled user interface (GCUI), and identifies trends in technology, application and usability. We present an integrated approach to real time detection, gesture based data glove technique which controls the wheelchair using hand movements. The paper proposed a low-cost and small 3-axis wireless accelerometers based system to control the wheelchair usin...

In this paper, we present work on understanding Vietnamese sign language through the use of Micro Electronic Mechanical System (MEMS) accelerometers. The system consists of six ADXL202 accelerometers for sensing the hand posture, a BASIC Stamp microcontroller and a PC for data acquisition and recognition of sign language. The data is then transformed to relative angles between fingers and the p...