Wei Quan

• PhD in Computer Vision and Machine Learning
• Senior Lecturer at University of Central Lancashire

Estimating rigid objects' poses is one of the fundamental problems in computer vision, with a range of applications across automation and augmented reality. Most existing approaches adopt one network per object class strategy, depend heavily on objects' 3D models, depth data, and employ a time-consuming iterative refinement, which could be impracti...

Objective: Acoustic emission (AE) sensed from knee joints during weight-bearing movements greatly increases with joint deterioration, but the relationship between AE patterns and specific anatomical damage, as seen for example in magnetic resonance imaging (MRI), is unknown. This knowledge is essential to validate AE biomarkers for the evaluation...

Our objective was to determine the efficacy and feasibility of a new approach for identifying candidate biomarkers for knee osteoarthritis (OA), based on selecting promising candidates from a range of high-frequency acoustic emission (AE) measurements generated during weight-bearing knee movement. Candidate AE biomarkers identified by this approach...

Our objective was to determine the efficacy and feasibility of a new approach for identifying candidate biomarkers for knee osteoarthritis (OA), based on selecting promising candidates from a range of high-frequency acoustic emission (AE) measurements generated during weight-bearing knee movement. Candidate AE biomarkers identified by this approach...

From sit-stand-sit movements performed by healthy and osteoarthritic knees in three different age bands, this paper presents the investigation of the relationship between joint angular movement measured using electro-goniometers and acoustic emission measured using piezoelectric sensors. By partitioning joint movement in each sit-stand-sit cycle in...

3-D face recognition research has received significant attention in the past two decades because of the rapid development in imaging technology and ever increasing security demand of modern society. One of its challenges is to cope with non-rigid deformation among faces, which is often caused by the changes of appearance and facial expression. Popu...

Paper introduces a 3-D shape representation scheme for automatic face analysis and identification, and demonstrates its invariance to facial expression. The core of this scheme lies on the combination of statistical shape modelling and non-rigid deformation matching. While the former matches 3-D faces with facial expression, the latter provides a l...

The aims of this paper are to introduce a 3-D shape matching scheme for automatic face recognition and to demonstrate its invariance to pose and facial expressions. The core of this scheme lies on the combination of non-rigid deformation registration and statistical shape modelling. While the former matches 3-D faces regardless of facial expression...

This paper presents an effective method of statistical shape representation for automatic face analysis and identification in 3-D. The method combines statistical shape modelling techniques and the non-rigid deformation matching scheme. This work is distinguished by three key contributions. The first is the introduction of a new 3-D shape registrat...

This paper presents a new method for facial expression modelling and recognition based on diffeomorphic image registration parameterised via stationary velocity fields in the log-Euclidean framework. The validation and comparison are done using different statistical shape models (SSM) built using the Point Distribution Model (PDM), velocity fields...

Most existing approaches in structure from motion for deformable objects focus on non-incremental solutions utilizing batch type algorithms. All data is collected before shape and motion reconstruction take place. This methodology is inherently unsuitable for applications that require real-time learning. Ideally the online system is capable of incr...

This paper presents an effective method of statistical shape representation for automatic face analysis and identification in 3-D. The method combines statistical shape modelling techniques and the non-rigid deformation matching scheme. This work is distinguished by three key contributions. The first is the introduction of a new 3-D shape registrat...

Facial asymmetry is an important characteristic used in a number of applications. It plays a vital role in human perception of attractiveness and as such has been used in psychology including research on facial expressions evaluation as well as in plastic surgery and orthodontics. It has been also recognized as a biometric feature used for ide...

The face is an important medium used by humans to communicate, and facial articulation also reflects a person's emotional and awareness states, cognitive activity, personality or wellbeing. With the advances in 3-D imaging technology and ever increasing computing power, automatic analysis of facial articulation using 3-D sequences is becoming viabl...

This paper presents a new method for facial expression modelling and recognition based on diffeomorphic image registration parameterised via stationary velocity fields in Log-Euclidean framework. The validation and comparison are done using different statistical shape models (SSM) built using the Point Distribution Model (PDM), velocity fields, and...

Face is an essential medium for complex non-verbal communication between humans. Its articulation plays an important role in everyday life, including: manifestation of emotional and awareness states, cognitive activity, personality or wellbeing. With the advances in 3-D imaging technology and ever increasing computing power, automatic analysis of f...

This paper presents the methodology and performance of a statistical shape representation for automatic facial expression analysis in 3-D. The core of the method uses the statistical shape modelling technique with the deformable model-based surface matching process, which is capable of simulation and interpretation of 3-D human facial expression...

The paper aims at recognizing the various human facial expressions. Every countenance is marked by changes in the feature points of the face. These feature points are located in various regions of the face. There are two phases in the facial expression recognition technique described here. The first phase is image processing and the second phase is...

This paper describes an improved 3-D facial representation method capable of modeling different types of faces without any constraint from expression, age, gender, or ethnic origin. Using the proposed technique, a 3-D face can be represented by a low dimensional shape space vector (SSV) of the statistical shape model (SSM), which is calculated thro...

This paper describes a novel method for representing different facial expressions based on the shape space vector (SSV) of the statistical shape model (SSM) built from 3D facial data. The method relies only on the 3D shape, with texture information not being used in any part of the algorithm, that makes it inherently invariant to changes in the bac...

Human faces play an important role in everyday life, including the expression of person identity, emotion and intentionality, along with a range of biological functions. The human face has also become the subject of considerable research effort, and there has been a shift towards understanding it using stimuli of increasingly more realistic formats...

This paper describes initial results from a novel low dimensional surface parameterisation approach based on a modified iterative closest point (ICP) registration process which uses vertex based principal component analysis (PCA) to incorporate a deformable element into registration process. Using this method a 3D surface is represented by a shape...

Effective representation and recognition of human faces are essential in a number of applications including human-computer interaction (HCI), bio-metrics or video conferencing. This paper presents initial results obtained for a novel method of 3-D facial expressions representation based on the shape space vector of the statistical shape model. The...