Rini Akmeliawati

Real-Time Malaysian Sign Language Translation using Colour Segmentation and Neural Network

In this paper we present an automatic visual-based sign language translation system. Our proposed automatic sign-language translator provides a real-time English translation of the Malaysia SL. To date, there have been studies on sign language recognition based on visual approach (video camera). However, the emphasis on these works is limited to a small lexicon of sign language or solely focuses on fingerspelling, which takes different approaches respectively. In practical sense, fingerspelling is used if a word cannot be expressed via sign language. Our sign language translator can recognise both fingerspelling and sign gestures that involve static and motion signs. Trained neural networks are used to identify the signs to translate into English.

Hidden Markov model for human to computer interaction: a study on human hand gesture recognition

Human hand recognition plays an important role in a wide range of applications ranging from sign language translators, gesture recognition, augmented reality, surveillance and medical image processing to various Human Computer Interaction (HCI) domains. Human hand is a complex articulated object consisting of many connected parts and joints. Therefore, for applications that involve HCI one can find many challenges to establish a system with high detection and recognition accuracy for hand posture and/or gesture. Hand posture is defined as a static hand configuration without any movement involved. Meanwhile, hand gesture is a sequence of hand postures connected by continuous motions. During the past decades, many approaches have been presented for hand posture and/or gesture recognition. In this paper, we provide a survey on approaches which are based on Hidden Markov Models (HMM) for hand posture and gesture recognition for HCI applications.

Vision-based hand posture detection and recognition for Sign Language — A study

Unlike general gestures, Sign Languages (SLs) are highly structured so that it provides an appealing test bed for understanding more general principles for hand shape, location and motion trajectory. Hand posture shape in other words static gestures detection and recognition is crucial in SLs and plays an important role within the duration of the motion trajectory. Vision-based hand shape recognition can be accomplished using three approaches 3D hand modelling, appearance-based methods and hand shape analysis. In this survey paper, we show that extracting features from hand shape is so essential during recognition stage for applications such as SL translators.

Nonlinear identification of a small scale unmanned helicopter using optimized NARX network with multiobjective differential evolution

The need for a high fidelity model for design, analysis and implementation of an unmanned helicopter system (UHS) in various emerging civil applications cannot be underestimated. However, going by a first principle approach based on physical laws governing the dynamics of the system, this task is noted to be highly challenging due to the complex nonlinear characteristics of the helicopter system. On the other hand, the problem of determining network architecture for optimal/sub-optimal performances has been one of the major challenges in the use of the nonparametric approach based on Nonlinear AutoRegressive with eXogenous inputs Network (NARX-network). The performance of the NARX network in terms of complexity and accuracy is largely dependent on the network architecture. The current approach in the literature has been largely based on trial and error, while most of the reported optimization approaches have limited the domain of the problem to a single objective problem. This study proposes a hybrid of conventional back propagation training algorithm for the NARX network and multiobjective differential evolution (MODE) algorithm for identification of a nonlinear model of an unmanned small scale helicopter from experimental flight data. The proposed hybrid algorithm was able to produce models with Pareto-optimal compromise between the design objectives. The performance of the proposed optimized model is benchmarked with one of the previously reported architectures for a similar system. The optimized model outperformed the previous model architecture with up to 55% performance improvement. Apart from the effectiveness of the optimized model, the proposed design algorithm is expected to facilitate timely development of the nonparametric model of the helicopter system.

A hybrid method using haar-like and skin-color algorithm for hand posture detection, recognition and tracking

Human hand posture detection and recognition is a challenging problem in computer vision. We introduce an algorithm that is capable to recognize hand posture in a sophisticated background. The system combines two algorithms to achieve better detection rate for hand. Recently Viola et al. in [10] have introduced a rapid object detection scheme; we use this approach to detect the hand posture in the first set of consecutive frames. The chromatic color distribution of skin can be found within this cluster. As the shape of hand posture keep changing in the subsequent frames, the skin regions updated dynamically. The classification of hand posture makes use of static feature for locating and counting hand fingers. Kalman Filter is used to track the face and hand blobs based on their position. In the experiments, we have tested our system in various environments, and results showed effectiveness of the approach.

Nonlinear Energy-Based Control Method for Aircraft Automatic Landing Systems

In this paper we present an aircraft automatic landing system using the nonlinear energy-based control method (NEM). This technique is based on aircraft energy management. NEM is based on the passivity-based control technique (PBC) and similar to Total Energy Control Systems (TECS). A physical interpretation of the NEM controller for the system is presented. We demonstrate that NEM provides insight into aircraft modeling and control while it achieves a satisfactory automatic flight control system (AFCS). The aircraft dynamics are presented via the energy functions. By modifying these functions, stabilization and tracking can be achieved. The automatic landing system is designed for a twin-engine civil aircraft, developed by the Group for Aeronautical Research and Technology in Europe (GARTEUR). Singular perturbation ideas are used to deal with the separation of the short-period and the phugoid dynamics. The proposed control laws appear to behave well even under extreme flight conditions.

Dynamic approach for real-time skin detection

Human face and hand detection, recognition and tracking are important research areas for many computer interaction applications. Face and hand are considered as human skin blobs, which fall in a compact region of colour spaces. Limitations arise from the fact that human skin has common properties and can be defined in various colour spaces after applying colour normalization. The model therefore, has to accept a wide range of colours, making it more susceptible to noise. We have addressed this problem and propose that the skin colour could be defined separately for every person. This is expected to reduce the errors. To detect human skin colour pixels and to decrease the number of false alarms, a prior face or hand detection model has been developed using Haar-like and AdaBoost technique. To decrease the cost of computational time, a fast search algorithm for skin detection is proposed. The level of performance reached in terms of detection accuracy and processing time allows this approach to be an adequate choice for real-time skin blob tracking.

Parameter identification of an autonomous quadrotor

This paper describes one of possible parameter identification approach for a quadrotor. The unknown parameter of the quadrotor will be identified using state estimation method with the implementation of Unscented Kalman Filter (UKF). In the identification of state and parameter for nonlinear dynamic system, UKF has grown to be superior techniques. Two main processes highlighted in this paper are dynamic modeling of quadrotor and the implementation of UKF algorithm. The aim is to identify and estimate the needed parameters for an autonomous quadrotor. The obtained results demonstrate the performance of UKF based on the flight test applied to the quadrotor system.

Gaussian Process Dynamical Models for hand gesture interpretation in Sign Language

Classifying human hand gestures in the context of a Sign Language has been historically dominated by Artificial Neural Networks and Hidden Markov Model with varying degrees of success. The main objective of this paper is to introduce Gaussian Process Dynamical Model as an alternative machine learning method for hand gesture interpretation in Sign Language. In support of this proposition, the paper presents the experimental results for Gaussian Process Dynamical Model against a database of 66 hand gestures from the Malaysian Sign Language. Furthermore, the Gaussian Process Dynamical Model is tested against established Hidden Markov Model for a comparative evaluation. A discussion on why Gaussian Process Dynamical Model is superior over existing methods in Sign Language interpretation task is then presented.

Design and development of a hand-glove controlled wheel chair

Wheelchairs are a way of reincarnating the purpose of life in the lives of disabled people. Effective and efficient ways of delivering a cost-effective and affordable wheelchair to the common masses, which is not only at par with the present day technology, but is much easier to use are presented herewith. Replacement of the popular joystick stick controlled wheel chair with a hand-glove control system for easier maneuvering by bending the fingers, is discussed in this paper. Intended users control the system by wearing an instrumented glove fitted with flex or bend sensors for controlling the movement and direction of the wheelchair. Uni-directional wireless communication exists between the instrumented gloves and the controller which is sandwiched between the users seat and the wheels. Initial design results are also presented in this paper. The technologies presented in this paper suggest a wide domain of possibilities to a wide variety of users. In addition, it also aims at making a cost-effective chair so that more hi-tech wheelchairs are made use of, widely, by people with disabilities.