ORCID Profile
0000-0001-6306-3023
Current Organisation
Edith Cowan University
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Research Topics
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.
Top 5 Research Topics
ANZSRC Field of Research (FoR)
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 |
ANZSRC Socio-Economic Objective (SEO)
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
Related Links
Publications
The random cluster model for robust geometric fitting
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 08-2014
Analyzing human movements from silhouettes using manifold learning
Publisher: IEEE
Date: 11-2006
DOI: 10.1109/AVSS.2006.25
Colour correction for multiple-camera system by using correspondences
Publisher: Institute of Image Information and Television Engineers
Date: 2007
DOI: 10.3169/ITEJ.61.213
Contour tracking with automatic motion model switching
Publisher: Elsevier BV
Date: 10-2003
A novel convolutional neural network structure for differential diagnosis of wide QRS complex tachycardia
Publisher: Elsevier BV
Date: 03-2023
Constraint Networks in Vision
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 1991
DOI: 10.1109/12.106221
Recognizing human activities from silhouettes: Motion subspace and factorial discriminative graphical model
Publisher: IEEE
Date: 06-2007
Incorporating knowledge via regularization theory: Applications in vision and image processing
Publisher: Springer Berlin Heidelberg
Date: 1990
Learning Affordance Segmentation: An Investigative Study
Publisher: IEEE
Date: 29-11-2020
Quantum Robust Fitting
Publisher: Springer International Publishing
Date: 2021
Robust data modelling using thin plate splines
Publisher: IEEE
Date: 11-2013
RATSAC - Random tree sampling for maximum consensus estimation
Publisher: IEEE
Date: 11-2017
Mode seeking over permutations for rapid geometric model fitting
Publisher: Elsevier BV
Date: 2013
Multi-scale Conditional Random Fields for over-segmented irregular 3D point clouds classification
Publisher: IEEE
Date: 06-2008
Accelerated hypothesis generation for multi-structure robust fitting
Publisher: Springer Berlin Heidelberg
Date: 2010
Visual tracking with automatic motion model switching
Publisher: Elsevier BV
Date: 03-2001
Using symmetry in robust model fitting
Publisher: Elsevier BV
Date: 12-2003
Human motion de-noising via greedy kernel principal component analysis filtering
Publisher: IEEE
Date: 2006
Clustering with Hypergraphs: The Case for Large Hyperedges
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2017
A simultaneous sample-and-filter strategy for robust multi-structure model fitting
Publisher: Elsevier BV
Date: 12-2013
Recovering the missing components in a large noisy low-rank matrix: Application to SFM
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 08-2004
DIV-CURL vector quasi-interpolation on a finite domain
Publisher: Elsevier BV
Date: 07-1999
Machine-Learning Assessed Abdominal Aortic Calcification is Associated with Long-Term Fall and Fracture Risk in Community-Dwelling Older Australian Women
Publisher: Wiley
Date: 30-10-2023
DOI: 10.1002/JBMR.4921
Message from the general co-chairs
Publisher: IEEE
Date: 09-2013
Fast stereo with background removal using phase correlation
Publisher: IEEE
Date: 11-2008
Reply to comments on 'joint detection and estimation of multiple objects from image observations'
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2012
Human action recognition by feature-reduced Gaussian process classification
Publisher: Elsevier BV
Date: 09-2009
Superpixel-Guided Two-View Deterministic Geometric Model Fitting
Publisher: Springer Science and Business Media LLC
Date: 19-05-2019
GuideNet: Learning Inter- Vertebral Guides in DXA Lateral Spine Images
Publisher: IEEE
Date: 11-2021
Subspace-based face recognition: Outlier detection and a new distance criterion
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.
As-projective-as-possible image stitching with moving DLT
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2014
Left ventricular motion reconstruction based on elastic vector splines
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.
Point correspondence validation under unknown radial distortion
Publisher: IEEE
Date: 11-2013
Simultaneously fitting and segmenting multiple-structure data with outliers
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2012
Deterministic Approximate Methods for Maximum Consensus Robust Fitting
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2021
Fast Point Cloud Registration using Semantic Segmentation
Publisher: IEEE
Date: 12-2019
Region of Interest Autoencoders with an Application to Pedestrian Detection
Publisher: IEEE
Date: 11-2017
Generalized framework for image and video object segmentation using affinity learning and message passing GNNS
Publisher: Elsevier BV
Date: 11-2023
Fast supervised hashing with decision trees for high-dimensional data
Publisher: IEEE
Date: 06-2014
Consensus Maximisation Using Influences of Monotone Boolean Functions
Publisher: IEEE
Date: 06-2021
Recognition of adult images, videos, and web page bags
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.
Efficient visual tracking by probabilistic fusion of multiple cues
Publisher: IEEE
Date: 2006
A multiple hypothesis tracker for multitarget tracking with multiple simultaneous measurements
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2013
KSM based machine learning for markerless motion capture
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.
Improved building detection by gaussian processes classification via feature space rescale and spectral kernel selection
Publisher: IEEE
Date: 06-2008
Motion Segmentation of RGB-D Sequences: Combining Semantic and Motion Information Using Statistical Inference
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Searching for Representative Modes on Hypergraphs for Robust Geometric Model Fitting
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2019
In defence of RANSAC for outlier rejection in deformable registration
Publisher: Springer Berlin Heidelberg
Date: 2012
Visual localization and segmentation based on foreground/background modeling
Publisher: IEEE
Date: 2010
Conformal Surface Alignment with Optimal Möbius Search
Publisher: IEEE
Date: 06-2016
Accelerated hypothesis generation for multistructure data via preference analysis
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2012
BoostML: An adaptive metric learning for nearest neighbor classification
Publisher: Springer Berlin Heidelberg
Date: 2010
Quasiconvex Plane Sweep for Triangulation with Outliers
Publisher: IEEE
Date: 10-2017
Efficient multi-structure robust fitting with incremental top-k lists comparison
Publisher: Springer Berlin Heidelberg
Date: 2011
Maximum Consensus by Weighted Influences of Monotone Boolean Functions
Publisher: IEEE
Date: 06-2022
Facial asymmetry in parents of children on the autism spectrum
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.
An Information-Theoretic Method to Automatic Shortcut Avoidance and Domain Generalization for Dense Prediction Tasks
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2023
Dynamic and hierarchical multi-structure geometric model fitting
Publisher: IEEE
Date: 11-2011
Mode-seeking on hypergraphs for robust geometric model fitting
Publisher: IEEE
Date: 12-2015
Multi-object filtering from image sequence without detection
Publisher: IEEE
Date: 2010
Robust Model Fitting Using Higher Than Minimal Subset Sampling
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 02-2016
Learning and matching of dynamic shape manifolds for human action recognition
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.
Robust total least squares based optic flow computation
Publisher: Springer Berlin Heidelberg
Date: 1997
Visual tracking of multiple objects with automatic motion model switching
Publisher: IEEE Comput. Soc
Date: 2000
Development of semi-automatic segmentation methods for measuring tibial cartilage volume
Publisher: IEEE
Date: 2005
Theoretical analysis of hough transform optimal cell size: Segmentation of nearby lines
Publisher: IEEE
Date: 11-2015
A semi-automatic system for measuring tibial cartilage volume
Publisher: IEEE
Date: 11-2005
Incremental kernel principal component analysis
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.
Fast sparse Gaussian processes learning for man-made structure classification
Publisher: IEEE
Date: 06-2007
EDITORIAL
Publisher: World Scientific Pub Co Pte Lt
Date: 04-2002
The Random Cluster Model for robust geometric fitting
Publisher: IEEE
Date: 06-2012
A compact architecture for wireless video surveillance over CDMA network
Publisher: IEEE
Date: 11-2006
DOI: 10.1109/AVSS.2006.4
Visual tracking of numerous targets via multi-Bernoulli filtering of image data
Publisher: Elsevier BV
Date: 10-2012
Sampling minimal subsets with large spans for robust estimation
Publisher: Springer Science and Business Media LLC
Date: 27-07-2014
Man-made structure segmentation using Gaussian processes and wavelet features
Publisher: IEEE
Date: 2006
Conditional random field for 3D point clouds with adaptive data reduction
Publisher: IEEE
Date: 10-2007
DOI: 10.1109/CW.2007.24
Error analysis in homography estimation by first order approximation tools: A general technique
Publisher: Springer Science and Business Media LLC
Date: 05-09-2009
Machine learning for abdominal aortic calcification assessment from bone density machine-derived lateral spine images
Publisher: Elsevier BV
Date: 08-2023
Adaptive human silhouette reconstruction based on the exploration of temporal information
Publisher: IEEE
Date: 03-2012
Show, Attend and Detect: Towards Fine-Grained Assessment of Abdominal Aortic Calcification on Vertebral Fracture Assessment Scans
Publisher: Springer Nature Switzerland
Date: 2022
Robust fitting of multiple structures: The statistical learning approach
Publisher: IEEE
Date: 09-2009
Multi-subregion based correlation filter bank for robust face recognition
Publisher: Elsevier BV
Date: 11-2014
Improving the speed of Kernel PCA on large scale datasets
Publisher: IEEE
Date: 11-2006
DOI: 10.1109/AVSS.2006.66
Unsupervised Learning for Maximum Consensus Robust Fitting: A Reinforcement Learning Approach
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
A new distance criterion for face recognition using image sets
Publisher: Springer Berlin Heidelberg
Date: 2006
DOI: 10.1007/11612032_56
Superpixel-based two-view deterministic fitting for multiple-structure data
Publisher: Springer International Publishing
Date: 2016
A consensus-based method for tracking: Modelling background scenario and foreground appearance
Publisher: Elsevier BV
Date: 03-2007
Robust adaptive-scale parametric model estimation for computer vision
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 11-2004
A broad autism phenotype expressed in facial morphology
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.
A global optimization approach to robust multi-model fitting
Publisher: IEEE
Date: 06-2011
Multi-structure model selection via kernel optimisation
Publisher: IEEE
Date: 06-2010
Informative shape representations for human action recognition
Publisher: IEEE
Date: 2006
An analysis of linear subspace approaches for computer vision and pattern recognition
Publisher: Springer Science and Business Media LLC
Date: 04-2006
Fast training of effective multi-class boosting using coordinate descent optimization
Publisher: Springer Berlin Heidelberg
Date: 2013
Object detection using a cascade of classifiers
Publisher: IEEE
Date: 2008
Color correction for multi-camera system by using correspondences
Publisher: ACM Press
Date: 2006
Background subtraction based on a robust consensus method
Publisher: IEEE
Date: 2006
ITSA: An Information-Theoretic Approach to Automatic Shortcut Avoidance and Domain Generalization in Stereo Matching Networks
Publisher: IEEE
Date: 06-2022
Finite sample bias of robust estimators in segmentation of closely spaced structures: A comparative study
Publisher: Springer Science and Business Media LLC
Date: 12-02-2010
Out-of-sample extrapolation of learned manifolds
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2008
Object tracking in image sequences using point features
Publisher: Elsevier BV
Date: 2005
PERFORMANCE MEASURES for ASSESSING CONTOUR TRACKERS
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.
Background initialization with a new robust statistical approach
Publisher: IEEE
Date: 2005
Human pose extraction from monocular videos using constrained non-rigid factorization
Publisher: British Machine Vision Association
Date: 2007
DOI: 10.5244/C.21.92
Assessing the performance of corner detectors for point feature tracking applications
Publisher: Elsevier BV
Date: 08-2004
A gradient-based metric learning algorithm for k-NN classifiers
Publisher: Springer Berlin Heidelberg
Date: 2010
Visual learning and recognition of sequential data manifolds with applications to human movement analysis
Publisher: Elsevier BV
Date: 05-2008
Efficient guided hypothesis generation for multi-structure epipolar geometry estimation
Publisher: Elsevier BV
Date: 2017
Impact of Neural Architecture Design on Cardiac Abnormality Classification Using 12-lead ECG Signals
Publisher: Computing in Cardiology
Date: 30-12-2020
Parametric model-based motion segmentation using surface selection criterion
Publisher: Elsevier BV
Date: 05-2006
Boosting histograms of descriptor distances for scalable multiclass specific scene recognition
Publisher: Elsevier BV
Date: 03-2011
M3T: Multi-class Multi-instance Multi-view Object Tracking for Embodied AI Tasks
Publisher: Springer Nature Switzerland
Date: 2023
Coupled depth slope model based upon augmented lagrangian techniques
Publisher: SPIE
Date: 09-1991
DOI: 10.1117/12.48419
Deterministic consensus maximization with biconvex programming
Publisher: Springer International Publishing
Date: 2018
As-projective-as-possible image stitching with moving DLT
Publisher: IEEE
Date: 06-2013
MDPE: A very robust estimator for model fitting and range image segmentation
Publisher: Springer Science and Business Media LLC
Date: 09-2004
Semantic Guided Long Range Stereo Depth Estimation for Safer Autonomous Vehicle Applications
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2022
Hypergraph modelling for geometric model fitting
Publisher: Elsevier BV
Date: 12-2016
Robust segmentation of visual data using ranked unbiased scale estimate
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.
Tracking and segmenting people with occlusions by a sample consensus based method
Publisher: IEEE
Date: 2005
Rank constraints for homographies over two views: Revisiting the rank four constraint
Publisher: Springer Science and Business Media LLC
Date: 13-09-2009
An exact penalty method for locally convergent maximum consensus
Publisher: IEEE
Date: 07-2017
DOI: 10.1109/CVPR.2017.48
Unsupervised Learning for Robust Fitting: A Reinforcement Learning Approach
Publisher: IEEE
Date: 06-2021
Simultaneously estimating the fundamental matrix and homographies
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2009
3D terrestrial LIDAR classifications with super-voxels and multi-scale Conditional Random Fields
Publisher: Elsevier BV
Date: 10-2009
Fast rotation search with stereographic projections for 3D registration
Publisher: IEEE
Date: 06-2014
A re-evaluation of mixture-of-gaussian background modeling
Publisher: IEEE
Date: 2005
Special issue on statistical methods in video processing
Publisher: Elsevier BV
Date: 02-2004
Using a fast multipole method to accelerate spline evaluations
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 1998
DOI: 10.1109/99.714590
A Hybrid Quantum-Classical Algorithm for Robust Fitting
Publisher: IEEE
Date: 06-2022
Feature detection with an improved anisotropic filter
Publisher: Springer Berlin Heidelberg
Date: 2006
DOI: 10.1007/11612704_64
Fast rotation search for real-time interactive point cloud registration
Publisher: ACM
Date: 14-03-2014
A bilinear approach to the parameter estimation of a general heteroscedastic linear system, with application to conic fitting
Publisher: Springer Science and Business Media LLC
Date: 06-10-2007
Joint detection and estimation of multiple objects from image observations
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2010
Clustering with hypergraphs: The case for large hyperedges
Publisher: Springer International Publishing
Date: 2014
Bayesian integration of audio and visual information for multi-target tracking using a CB-member filter
Publisher: IEEE
Date: 05-2011
Retrieving 3D CAD models using 2D images with optimized weights
Publisher: IEEE
Date: 10-2010
Superpixel-driven level set tracking
Publisher: IEEE
Date: 09-2012
A general two-step approach to learning-based hashing
Publisher: IEEE
Date: 12-2013
Segmentation by Continuous Latent Semantic Analysis for Multi-structure Model Fitting
Publisher: Springer Science and Business Media LLC
Date: 24-04-2021
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