Geometric Expression Invariant 3D Face Recognition using Statistical Discriminant Models

Currently there is no complete face recognition system that is invariant to all facial expressions. Although humans find it easy to identify and recognise faces regardless of changes in illumination, pose and expression, producing a computer system with a similar capability has proved to be particularly di cult. Three dimensional face models are geometric in nature and therefore have the advantage of being invariant to head pose and lighting. However they are still susceptible to facial expressions. This can be seen in the decrease in the recognition results using principal component analysis when expressions are added to a data set. In order to achieve expression-invariant face recognition systems, we have employed a tensor algebra framework to represent 3D face data with facial expressions in a parsimonious space. Face variation factors are organised in particular subject and facial expression modes. We manipulate this using single value decomposition on sub-tensors representing one variation mode. This framework possesses the ability to deal with the shortcomings of PCA in less constrained environments and still preserves the integrity of the 3D data. The results show improved recognition rates for faces and facial expressions, even recognising high intensity expressions that are not in the training datasets. We have determined, experimentally, a set of anatomical landmarks that best describe facial expression e ectively. We found that the best placement of landmarks to distinguish di erent facial expressions are in areas around the prominent features, such as the cheeks and eyebrows. Recognition results using landmark-based face recognition could be improved with better placement. We looked into the possibility of achieving expression-invariant face recognition by reconstructing and manipulating realistic facial expressions. We proposed a tensor-based statistical discriminant analysis method to reconstruct facial expressions and in particular to neutralise facial expressions. The results of the synthesised facial expressions are visually more realistic than facial expressions generated using conventional active shape modelling (ASM). We then used reconstructed neutral faces in the sub-tensor framework for recognition purposes. The recognition results showed slight improvement. Besides biometric recognition, this novel tensor-based synthesis approach could be used in computer games and real-time animation applications

A survey on IT adoption model for SMIs in Malaysia

Understanding the major roles and functions of Information Technology (IT) in an organisation is an important factor in shaping an organisation’s characteristics and determining the usage of IT as an enabler in a business.A survey on small and medium sized industries in Malaysia has been carried out in order to identify and recognise the usage of IT in businesses.The parameters such as organisational details (i.e. the numbers of employees, sales or profitability and the type of business) and managers details (in terms of educational level, computer literacy and computer experiences) were studied in order to see whether these parameters do contribute towards the usage of IT in businesses. Based on the results of the survey, an IT adoption model is proposed.This IT adoption model can be used as a framework for users who wishes to set-up a business.Due to the diverse cultural composition, the model can also be used as guidelines to émigré entrepreneurs of the important areas in setting-up new SMIs in Malaysia

Usage of Information Technologies in Malaysian Businesses

A survey on small and medium sized industries in Malaysia has been carried out in order to identify and recognize the usage of IT in business. The parameters such as organizational details (i.e. the numbers of employees, sales or profitability and the type of business) and managers details (in terms of educational level, computer literacy and computer experiences) were studied in order to see whether these parameters do contribute towards the usage of IT in business. Based on the survey, the results found are discussed and an IT adoption model is proposed

Speech Therapy Mobile Application for Speech and Language Impairment Children

Speech and language impairment (SLI) is a communication disorder when a person has difficulties to produce speech sounds correctly and understand others. Children with SLI need speech therapy to help them improve their communication skills in order to communicate effectively with others. Due to the lack of speech therapist in the state, children are mainly waste valuable learning time while waiting for therapy and these speech therapy sessions are usually done only on a one-to-one basis within a block period. Recent studies showed that mobile technologies may work as an educational tool which can help children to learn. Hence, a local prototype of mobile speech therapy application was developed to be appealing for pre-school children of age 3 to 6 with SLI and will be used as a supplementary activity which can be used during a speech therapy session or at home. In this paper, we present the results of a six months intervention experiment with SLI children. We have adapted the heuristic evaluation for evaluating the usability of the local prototype mobile speech therapy application. The results of our study shows those children and their parents gave positive responses towards the mobile application, also helps in improving the children skills in producing correct sounds

3D Facial Expression Synthesis: A Survey

Facial expression synthesis is a process of generating new face shapes from a given face and still retain the distinct facial characteristics of the initial face. The generated facial expressions can be used to improve the performance of existing face identification systems, or to enhance human recognition. Earlier work on synthesizing face shapes used 2D face images. Only recently, the work moved to using 3D face shapes given the availability and improvement in 3D scanner technologies. The advantage of 3D faces over 2D image data is that 3D face holds more geometric shape data and is invariant to poses and illumination. This paper aims to give an overview of the methods used for 3D facial expression synthesis. We present an overview of 3D face expression synthesis, its applications and benefits and then we review some of the most resent 3D face expression synthesis approaches

Towards automatic landmarking on 2.5D face range images

In this paper, we propose an algorithm to automatically landmark points on 2.5-dimensional (2.5D) face images. We applied the Scale-invariant Feature Transform (SIFT) method to a new automatic landmarking method. Automatic landmarking has a number of added advantages over manual landmarking and it is more accurate and less time consuming especially if the dataset is large. We developed an interactive Graphical User Interface (GUI) tool to ease the visualization of the extract face features, which are scale and transformation invariant. The threshold values are then analyzed and generalized to best detect and extract important keypoints or/and regions of facial features. The results of the automatic extracted keypoint features are shown in this paper

Automatic Landmarking on 2.5D Face Range Images

In this paper, we develop an automatic land marking method on face data using 2.5-dimensional (2.5D) range images. Automatic facial land marking is a vital process that could be employed to any face application for analysis, registration and recognition. The research aims to locate facial feature points (the eye corners, the nose tip, the mouth corners, chin etc.) automatically without the intervention of human. Automatic land marking has a number of added advantages over manual land marking, especially if the dataset is large, hence the landmark selection could be more accurate and less time consuming. We also developed an interface to ease the visualization of the land marking process. It has interactive tools which allow the manipulation of threshold values. The threshold values are then analyzed and generalized to best detect and extract important key points or/and regions of facial features. The results of the automatic extracted facial features and candidate landmarks are shown in this paper

Remote health monitoring system in a rural population: Challenges and opportunities

This paper discusses remote health monitoring as a potential application field in telecentres at rural areas. We present the challenges faced and opportunities with emphasis on patients with hypertension using a remote health monitoring system. We will also discuss the potential of deploying mHealth applications as a value added to the telecentres. The remote blood pressure health monitoring system will read, store and send data over wireless network to a remote server. Medical doctors can view the data on a regular basis remotely from a website. This community-based participatory research study carried out BP monitoring on residents from a rural village in Sarawak, Borneo and did follow-up assessments on the available health care for them. Structured quantitative and qualitative research tools were carried out on a wide range of clients – the patients, telecentre managers and medical doctors. Structured and semi-structured data collection techniques, such as questionnaires, group discussions and interviews were gathered. Observation of the whole process of interaction between the patients with the managers was also captured. The aim of the project is to determine the degree to which remote health monitoring interventions can be integrated to telecentres in rural areas to increase awareness in healthy living and wellness