ORCID Profile
0000-0001-6306-3023
Current Organisation
Edith Cowan University
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In Research Link Australia (RLA), "Research Topics" refer to ANZSRC FOR and SEO codes. These topics are either sourced from ANZSRC FOR and SEO codes listed in researchers' related grants or generated by a large language model (LLM) based on their publications.
Artificial Intelligence and Image Processing | Computer Vision | Pattern Recognition and Data Mining | Image Processing | Signal Processing | Computer Vision | Pattern Recognition | Electrical and Electronic Engineering | Image Processing | Manufacturing Robotics and Mechatronics (excl. Automotive Mechatronics) | Intelligent Robotics | Simulation And Modelling | Optimisation | Automotive Engineering | Computer Communications Networks | Stochastic Analysis And Modelling | Interdisciplinary Engineering Not Elsewhere Classified | Applied Statistics | Neurobiology | Automotive Engineering | Decision Support And Group Support Systems | Numerical Analysis |
Combined operations | Information processing services | Expanding Knowledge in the Information and Computing Sciences | Diagnostic methods | Application Software Packages (excl. Computer Games) | Information and Communication Services not elsewhere classified | Industrial Instruments | Integrated Systems | Computer Hardware and Electronic Equipment not elsewhere classified | Emerging Defence Technologies | Intelligence | Computer equipment | Data, image and text equipment | Medical instrumentation | Road safety | Appliances and electrical machinery and equipment | Integrated systems | Automotive equipment | Physical sciences | Computer software and services not elsewhere classified | Film and Video Services (excl. Animation and Computer Generated Imagery) | Consumer Electronic Equipment (excl. Communication Equipment) | Commercial security services | Computer hardware and electronic equipment not elsewhere classified | Instrumentation not elsewhere classified
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 08-2014
Publisher: IEEE
Date: 11-2006
DOI: 10.1109/AVSS.2006.25
Publisher: Institute of Image Information and Television Engineers
Date: 2007
DOI: 10.3169/ITEJ.61.213
Publisher: Elsevier BV
Date: 10-2003
Publisher: Elsevier BV
Date: 03-2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 1991
DOI: 10.1109/12.106221
Publisher: IEEE
Date: 06-2007
Publisher: Springer Berlin Heidelberg
Date: 1990
Publisher: IEEE
Date: 29-11-2020
Publisher: Springer International Publishing
Date: 2021
Publisher: IEEE
Date: 11-2013
Publisher: IEEE
Date: 11-2017
Publisher: Elsevier BV
Date: 2013
Publisher: IEEE
Date: 06-2008
Publisher: Springer Berlin Heidelberg
Date: 2010
Publisher: Elsevier BV
Date: 03-2001
Publisher: Elsevier BV
Date: 12-2003
Publisher: IEEE
Date: 2006
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2017
Publisher: Elsevier BV
Date: 12-2013
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 08-2004
Publisher: Elsevier BV
Date: 07-1999
Publisher: Wiley
Date: 30-10-2023
DOI: 10.1002/JBMR.4921
Publisher: IEEE
Date: 09-2013
Publisher: IEEE
Date: 11-2008
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2012
Publisher: Elsevier BV
Date: 09-2009
Publisher: Springer Science and Business Media LLC
Date: 19-05-2019
Publisher: IEEE
Date: 11-2021
Publisher: World Scientific Pub Co Pte Lt
Date: 06-2005
DOI: 10.1142/S0218001405004174
Abstract: Illumination effects, including shadows and varying lighting, make the problem of face recognition challenging. Experimental and theoretical results show that the face images under different illumination conditions approximately lie in a low-dimensional subspace, hence principal component analysis (PCA) or low-dimensional subspace techniques have been used. Following this spirit, we propose new techniques for the face recognition problem, including an outlier detection strategy (mainly for those points not following the Lambertian reflectance model), and a new error criterion for the recognition algorithm. Experiments using the Yale-B face database show the effectiveness of the new strategies.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2014
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2000
DOI: 10.1109/42.848181
Abstract: In medical imaging it is common to reconstruct dense motion estimates, from sparse measurements of that motion, using some form of elastic spline (thin-plate spline, snakes and other deformable models, etc.). Usually the elastic spline uses only bending energy (second-order smoothness constraint) or stretching energy (first-order smoothness constraint), or a combination of the two. These elastic splines belong to a family of elastic vector splines called the Laplacian splines. This spline family is derived from an energy minimization functional, which is composed of multiple-order smoothness constraints. These splines can be explicitly tuned to vary the smoothness of the solution according to the deformation in the modeled material/tissue. In this context, it is natural to question which members of the family will reconstruct the motion more accurately. We compare different members of this spline family to assess how well these splines reconstruct human cardiac motion. We find that the commonly used splines (containing first-order and/or second-order smoothness terms only) are not the most accurate for modeling human cardiac motion.
Publisher: IEEE
Date: 11-2013
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2012
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2021
Publisher: IEEE
Date: 12-2019
Publisher: IEEE
Date: 11-2017
Publisher: Elsevier BV
Date: 11-2023
Publisher: IEEE
Date: 06-2014
Publisher: IEEE
Date: 06-2021
Publisher: Association for Computing Machinery (ACM)
Date: 10-2011
Abstract: In this article, we develop an integrated adult-content recognition system which can detect adult images, adult videos, and adult Web page bags, where a Web page bag consists of a Web page and a predefined number of Web pages linked to it through hyperlinks. In our adult image-recognition algorithm, we model skin patches rather than skin pixels, resulting in better results than state-of-the-art algorithms which model skin pixels. In our adult video-recognition algorithm, information from the accompanying audio section around an image in an adult video is used to obtain a prior classification of the image. The algorithm achieves a better performance than the ones which use image information alone or audio information alone. The adult Web page bag recognition is carried out using multi-instance learning based on the combination of classifying texts, images and videos in Web pages. Both the speed and the accuracy for recognizing the Web adult content are increased, in contrast to recognizing Web pages one-by-one.
Publisher: IEEE
Date: 2006
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2013
Publisher: IGI Global
Date: 2009
DOI: 10.4018/978-1-60566-900-7.CH005
Abstract: A marker-less motion capture system, based on machine learning, is proposed and tested. Pose information is inferred from images captured from multiple (as few as two) synchronized cameras. The central concept of which, we call: Kernel Subspace Mapping (KSM). The images-to-pose learning could be done with large numbers of images of a large variety of people (and with the ground truth poses accurately known). Of course, obtaining the ground-truth poses could be problematic. Here we choose to use synthetic data (both for learning and for, at least some of, testing). The system needs to generalizes well to novel inputs:unseen poses (not in the training database) and unseen actors. For the learning we use a generic and relatively low fidelity computer graphic model and for testing we sometimes use a more accurate model (made to resemble the first author). What makes machine learning viable for human motion capture is that a high percentage of human motion is coordinated. Indeed, it is now relatively well known that there is large redundancy in the set of possible images of a human (these images form som sort of relatively smooth lower dimensional manifold in the huge dimensional space of all possible images) and in the set of pose angles (again, a low dimensional and smooth sub-manifold of the moderately high dimensional space of all possible joint angles). KSM, is based on the KPCA (Kernel PCA) algorithm, which is costly. We show that the Greedy Kernel PCA (GKPCA) algorithm can be used to speed up KSM, with relatively minor modifications. At the core, then, is two KPCA’s (or two GKPCA’s) - one for the learning of pose manifold and one for the learning image manifold. Then we use a modification of Local Linear Embedding (LLE) to bridge between pose and image manifolds.
Publisher: IEEE
Date: 06-2008
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2019
Publisher: Springer Berlin Heidelberg
Date: 2012
Publisher: IEEE
Date: 2010
Publisher: IEEE
Date: 06-2016
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2012
Publisher: Springer Berlin Heidelberg
Date: 2010
Publisher: IEEE
Date: 10-2017
Publisher: Springer Berlin Heidelberg
Date: 2011
Publisher: IEEE
Date: 06-2022
Publisher: Wiley
Date: 16-09-2021
DOI: 10.1002/AUR.2612
Abstract: Greater facial asymmetry has been consistently found in children with autism spectrum disorder (ASD) relative to children without ASD. There is substantial evidence that both facial structure and the recurrence of ASD diagnosis are highly heritable within a nuclear family. Furthermore, sub‐clinical levels of autistic‐like behavioural characteristics have also been reported in first‐degree relatives of in iduals with ASD, commonly known as the ‘broad autism phenotype’. Therefore, the aim of the current study was to examine whether a broad autism phenotype expresses as facial asymmetry among 192 biological parents of autistic in iduals (134 mothers) compared to those of 163 age‐matched adults without a family history of ASD (113 females). Using dense surface‐modelling techniques on three dimensional facial images, we found evidence for greater facial asymmetry in parents of autistic in iduals compared to age‐matched adults in the comparison group ( p = 0.046, d = 0.21 [0.002, 0.42]). Considering previous findings and the current results, we conclude that facial asymmetry expressed in the facial morphology of autistic children may be related to heritability factors. In a previous study, we showed that autistic children presented with greater facial asymmetry than non‐autistic children. In the current study, we examined the amount of facial asymmetry shown on three‐dimensional facial images of 192 parents of autistic children compared to a control group consisting of 163 similarly aged adults with no known history of autism. Although parents did show greater levels of facial asymmetry than those in the control group, this effect is statistically small. We concluded that the facial asymmetry previously found in autistic children may be related to genetic factors.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2023
Publisher: IEEE
Date: 11-2011
Publisher: IEEE
Date: 12-2015
Publisher: IEEE
Date: 2010
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 02-2016
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2007
Abstract: In this paper, we learn explicit representations for dynamic shape manifolds of moving humans for the task of action recognition. We exploit locality preserving projections (LPP) for dimensionality reduction, leading to a low-dimensional embedding of human movements. Given a sequence of moving silhouettes associated to an action video, by LPP, we project them into a low-dimensional space to characterize the spatiotemporal property of the action, as well as to preserve much of the geometric structure. To match the embedded action trajectories, the median Hausdorff distance or normalized spatiotemporal correlation is used for similarity measures. Action classification is then achieved in a nearest-neighbor framework. To evaluate the proposed method, extensive experiments have been carried out on a recent dataset including ten actions performed by nine different subjects. The experimental results show that the proposed method is able to not only recognize human actions effectively, but also considerably tolerate some challenging conditions, e.g., partial occlusion, low-quality videos, changes in viewpoints, scales, and clothes within-class variations caused by different subjects with different physical build styles of motion etc.
Publisher: Springer Berlin Heidelberg
Date: 1997
Publisher: IEEE Comput. Soc
Date: 2000
Publisher: IEEE
Date: 2005
Publisher: IEEE
Date: 11-2015
Publisher: IEEE
Date: 11-2005
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2007
Abstract: The kernel principal component analysis (KPCA) has been applied in numerous image-related machine learning applications and it has exhibited superior performance over previous approaches, such as PCA. However, the standard implementation of KPCA scales badly with the problem size, making computations for large problems infeasible. Also, the "batch" nature of the standard KPCA computation method does not allow for applications that require online processing. This has somewhat restricted the domains in which KPCA can potentially be applied. This paper introduces an incremental computation algorithm for KPCA to address these two problems. The basis of the proposed solution lies in computing incremental linear PCA in the kernel induced feature space, and constructing reduced-set expansions to maintain constant update speed and memory usage. We also provide experimental results which demonstrate the effectiveness of the approach.
Publisher: IEEE
Date: 06-2007
Publisher: World Scientific Pub Co Pte Lt
Date: 04-2002
Publisher: IEEE
Date: 06-2012
Publisher: IEEE
Date: 11-2006
DOI: 10.1109/AVSS.2006.4
Publisher: Elsevier BV
Date: 10-2012
Publisher: Springer Science and Business Media LLC
Date: 27-07-2014
Publisher: IEEE
Date: 2006
Publisher: IEEE
Date: 10-2007
DOI: 10.1109/CW.2007.24
Publisher: Springer Science and Business Media LLC
Date: 05-09-2009
Publisher: Elsevier BV
Date: 08-2023
Publisher: IEEE
Date: 03-2012
Publisher: Springer Nature Switzerland
Date: 2022
Publisher: IEEE
Date: 09-2009
Publisher: Elsevier BV
Date: 11-2014
Publisher: IEEE
Date: 11-2006
DOI: 10.1109/AVSS.2006.66
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: Springer Berlin Heidelberg
Date: 2006
DOI: 10.1007/11612032_56
Publisher: Springer International Publishing
Date: 2016
Publisher: Elsevier BV
Date: 03-2007
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 11-2004
Publisher: Springer Science and Business Media LLC
Date: 16-01-2020
DOI: 10.1038/S41398-020-0695-Z
Abstract: Autism spectrum disorder is a heritable neurodevelopmental condition diagnosed based on social and communication differences. There is strong evidence that cognitive and behavioural changes associated with clinical autism aggregate with biological relatives but in milder form, commonly referred to as the ‘broad autism phenotype’. The present study builds on our previous findings of increased facial masculinity in autistic children (Sci. Rep., 7:9348, 2017) by examining whether facial masculinity represents as a broad autism phenotype in 55 non-autistic siblings (25 girls) of autistic children. Using 3D facial photogrammetry and age-matched control groups of children without a family history of ASD, we found that facial features of male siblings were more masculine than those of male controls ( n = 69 p 0.001, d = 0.81 [0.36, 1.26]). Facial features of female siblings were also more masculine than the features of female controls ( n = 60 p = 0.005, d = 0.63 [0.16, 1.10]). Overall, we demonstrated for males and females that facial masculinity in non-autistic siblings is increased compared to same-sex comparison groups. These data provide the first evidence for a broad autism phenotype expressed in a physical characteristic, which has wider implications for our understanding of the interplay between physical and cognitive development in humans.
Publisher: IEEE
Date: 06-2011
Publisher: IEEE
Date: 06-2010
Publisher: IEEE
Date: 2006
Publisher: Springer Science and Business Media LLC
Date: 04-2006
Publisher: Springer Berlin Heidelberg
Date: 2013
Publisher: IEEE
Date: 2008
Publisher: ACM Press
Date: 2006
Publisher: IEEE
Date: 2006
Publisher: IEEE
Date: 06-2022
Publisher: Springer Science and Business Media LLC
Date: 12-02-2010
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2008
Publisher: Elsevier BV
Date: 2005
Publisher: World Scientific Pub Co Pte Lt
Date: 04-2002
DOI: 10.1142/S0219467802000627
Abstract: In this paper we present techniques to compare the quality of tracking performances of B-spline based contour trackers. Three trackers reported to give good tracking performance have been considered for our empirical evaluation. They are the CONT-IMM tracker, the Condensation tracker and the Baumberg's tracker. Four different test conditions were set and for each test, the tracking performance of each tracker was measured against four performance measures. The results presented have revealed some interesting findings about the performance of the trackers under various conditions.
Publisher: IEEE
Date: 2005
Publisher: British Machine Vision Association
Date: 2007
DOI: 10.5244/C.21.92
Publisher: Elsevier BV
Date: 08-2004
Publisher: Springer Berlin Heidelberg
Date: 2010
Publisher: Elsevier BV
Date: 05-2008
Publisher: Elsevier BV
Date: 2017
Publisher: Computing in Cardiology
Date: 30-12-2020
Publisher: Elsevier BV
Date: 05-2006
Publisher: Elsevier BV
Date: 03-2011
Publisher: Springer Nature Switzerland
Date: 2023
Publisher: SPIE
Date: 09-1991
DOI: 10.1117/12.48419
Publisher: Springer International Publishing
Date: 2018
Publisher: IEEE
Date: 06-2013
Publisher: Springer Science and Business Media LLC
Date: 09-2004
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2022
Publisher: Elsevier BV
Date: 12-2016
Publisher: Cambridge University Press (CUP)
Date: 11-1999
DOI: 10.1017/S0263574799001812
Abstract: A method of data segmentation, based upon robust least K-th order statistical model fitting (LKS), is proposed and applied to image motion and range data segmentation. The estimation method differs from other approaches using versions of LKS in a number of important ways. Firstly, the value of K is not determined by a complex optimization routine. Secondly, having chosen a fit, the estimation of scale of the noise is not based upon the K-th order statistic of the residuals. Other aspects of the full segmentation scheme include the use of segment contiguity to: (a) reduce the number of random s le fits used in the LKS stage, and (b) to “fill-in” holes caused by isolated miss-classified data.
Publisher: IEEE
Date: 2005
Publisher: Springer Science and Business Media LLC
Date: 13-09-2009
Publisher: IEEE
Date: 07-2017
DOI: 10.1109/CVPR.2017.48
Publisher: IEEE
Date: 06-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2009
Publisher: Elsevier BV
Date: 10-2009
Publisher: IEEE
Date: 06-2014
Publisher: IEEE
Date: 2005
Publisher: Elsevier BV
Date: 02-2004
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 1998
DOI: 10.1109/99.714590
Publisher: IEEE
Date: 06-2022
Publisher: Springer Berlin Heidelberg
Date: 2006
DOI: 10.1007/11612704_64
Publisher: ACM
Date: 14-03-2014
Publisher: Springer Science and Business Media LLC
Date: 06-10-2007
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2010
Publisher: Springer International Publishing
Date: 2014
Publisher: IEEE
Date: 05-2011
Publisher: IEEE
Date: 10-2010
Publisher: IEEE
Date: 09-2012
Publisher: IEEE
Date: 12-2013
Publisher: Springer Science and Business Media LLC
Date: 24-04-2021
Start Date: 2008
End Date: 12-2010
Amount: $235,000.00
Funder: Australian Research Council
View Funded ActivityStart Date: 2016
End Date: 12-2018
Amount: $268,000.00
Funder: Australian Research Council
View Funded ActivityStart Date: 08-2008
End Date: 12-2011
Amount: $422,000.00
Funder: Australian Research Council
View Funded ActivityStart Date: 01-2004
End Date: 12-2003
Amount: $20,000.00
Funder: Australian Research Council
View Funded ActivityStart Date: 12-2016
End Date: 12-2020
Amount: $285,000.00
Funder: Australian Research Council
View Funded ActivityStart Date: 2011
End Date: 12-2014
Amount: $300,000.00
Funder: Australian Research Council
View Funded ActivityStart Date: 2013
End Date: 11-2016
Amount: $330,000.00
Funder: Australian Research Council
View Funded ActivityStart Date: 07-2013
End Date: 12-2016
Amount: $252,000.00
Funder: Australian Research Council
View Funded ActivityStart Date: 09-2005
End Date: 09-2008
Amount: $186,662.00
Funder: Australian Research Council
View Funded ActivityStart Date: 12-2004
End Date: 12-2010
Amount: $2,250,000.00
Funder: Australian Research Council
View Funded ActivityStart Date: 2020
End Date: 01-2024
Amount: $380,000.00
Funder: Australian Research Council
View Funded ActivityStart Date: 03-2004
End Date: 12-2006
Amount: $201,000.00
Funder: Australian Research Council
View Funded ActivityStart Date: 10-2016
End Date: 06-2020
Amount: $275,000.00
Funder: Australian Research Council
View Funded ActivityStart Date: 2013
End Date: 12-2013
Amount: $210,000.00
Funder: Australian Research Council
View Funded ActivityStart Date: 2003
End Date: 12-2007
Amount: $5,625,165.00
Funder: Australian Research Council
View Funded ActivityStart Date: 2010
End Date: 12-2011
Amount: $280,000.00
Funder: Australian Research Council
View Funded ActivityStart Date: 2004
End Date: 12-2004
Amount: $10,000.00
Funder: Australian Research Council
View Funded Activity