Skip to main content

Research Repository

Advanced Search

All Outputs (59)

Assessing the Non-Uniqueness of a Well Test Interpretation Model Using a Bayesian Approach (2020)
Presentation / Conference Contribution
Cumming, J., Botsas, T., Jermyn, I., & Gringarten, A. (2020, December). Assessing the Non-Uniqueness of a Well Test Interpretation Model Using a Bayesian Approach. Presented at SPE Virtual Europec 2020

Objectives/Scope: A stable, single-well deconvolution algorithm has been introduced for well test analysis in the early 2000’s, that allows to obtain information about the reservoir system not always available from individual flow periods, for exampl... Read More about Assessing the Non-Uniqueness of a Well Test Interpretation Model Using a Bayesian Approach.

Statistical Characterisation of Fluvial Sand Bodies: Implications for Complex Reservoir Models (2019)
Presentation / Conference Contribution
Franzel, M., Jones, S., Jermyn, I., Allen, M., & McCaffrey, K. (2019, December). Statistical Characterisation of Fluvial Sand Bodies: Implications for Complex Reservoir Models. Presented at Petroleum Geostatistics 2019

The three-dimensional geometry of fluvial channel sand bodies has received considerably less attention than their internal sedimentology, despite the importance of sandstone body geometry for subsurface reservoir modelling. The aspect ratio (width/th... Read More about Statistical Characterisation of Fluvial Sand Bodies: Implications for Complex Reservoir Models.

Shape-constrained and unconstrained density estimation using geometric exploration (2018)
Presentation / Conference Contribution
Dasgupta, S., Pati, D., Jermyn, I. H., & Srivastava, A. (2018, June). Shape-constrained and unconstrained density estimation using geometric exploration. Presented at IEEE Statistical Signal Processing Workshop (SSP)., Freiburg, Germany

The problem of nonparametrically estimating probability density functions (pdfs) from observed data requires posing and solving optimization problems on the space of pdfs. We take a geometric approach and explore this space for optimization using act... Read More about Shape-constrained and unconstrained density estimation using geometric exploration.

Elastic 3D shape analysis using square-root normal field representation (2017)
Presentation / Conference Contribution
Laga, H., Jermyn, I. H., Kurtek, S., & Srivastava, A. (2017, December). Elastic 3D shape analysis using square-root normal field representation. Presented at 56th IEEE Conference on Decision and Control., Melbourne, Australia

Shape is an important physical property of natural and man-made 3D objects that characterizes their external appearances. Understanding differences between shapes, and modeling the variability within and across shape classes, hereinafter referred to... Read More about Elastic 3D shape analysis using square-root normal field representation.

Numerical inversion of SRNFs for efficient elastic shape analysis of star-shaped objects (2014)
Presentation / Conference Contribution
Xie, Q., Jermyn, I., Kurtek, S., & Srivastava, A. (2014, September). Numerical inversion of SRNFs for efficient elastic shape analysis of star-shaped objects. Presented at Proc. European Conference on Computer Vision (ECCV), Zurich

The elastic shape analysis of surfaces has proven useful in several application areas, including medical image analysis, vision, and graphics. This approach is based on defining new mathematical representations of parameterized surfaces, including th... Read More about Numerical inversion of SRNFs for efficient elastic shape analysis of star-shaped objects.

A multi-layer phase field model for extracting multiple near-circular objects (2012)
Presentation / Conference Contribution
Molnar, C., Kato, Z., & Jermyn, I. (2012, November). A multi-layer phase field model for extracting multiple near-circular objects. Presented at 21st International Conference on Pattern Recognition (ICPR2012)., Tsukuba, Japan

This paper proposes a functional that assigns low `energy' to sets of subsets of the image domain consisting of a number of possibly overlapping near-circular regions of approximately a given radius: a `gas of circles'. The model can be used as a pri... Read More about A multi-layer phase field model for extracting multiple near-circular objects.

Elastic shape matching of parameterized surfaces using square root normal fields (2012)
Presentation / Conference Contribution
Jermyn, I. H., Kurtek, S., Klassen, E., & Srivastava, A. (2012, October). Elastic shape matching of parameterized surfaces using square root normal fields. Presented at 12th European Conference on Computer Vision (ECCV), Florence, Italy

In this paper we define a new methodology for shape analysis of parameterized surfaces, where the main issues are: (1) choice of metric for shape comparisons and (2) invariance to reparameterization. We begin by defining a general elastic metric on t... Read More about Elastic shape matching of parameterized surfaces using square root normal fields.

A phase field method for tomographic reconstruction from limited data (2012)
Presentation / Conference Contribution
Hewett, R. J., Jermyn, I., Heath, M. T., & Kamalabadi, F. (2012, September). A phase field method for tomographic reconstruction from limited data. Presented at British Machine Vision Conference 2012 (BMVC), Guildford, Surrey

Classical tomographic reconstruction methods fail for problems in which there is extreme temporal and spatial sparsity in the measured data. Reconstruction of coronal mass ejections (CMEs), a space weather phenomenon with potential negative effects o... Read More about A phase field method for tomographic reconstruction from limited data.

A multi-layer `gas of circles' Markov random field model for the extraction of overlapping near-circular objects (2011)
Presentation / Conference Contribution
Nemeth, J., Kato, Z., & Jermyn, I. (2011, August). A multi-layer `gas of circles' Markov random field model for the extraction of overlapping near-circular objects. Presented at 13th International Conference Advanced Concepts for Intelligent Vision Systems (ACIVS 2011), Ghent

We propose a multi-layer binary Markov random field (MRF) model that assigns high probability to object configurations in the image domain consisting of an unknown number of possibly touching or overlapping near-circular objects of approximately a gi... Read More about A multi-layer `gas of circles' Markov random field model for the extraction of overlapping near-circular objects.

A theoretical and numerical study of a phase field higher-order active contour model of directed networks (2010)
Presentation / Conference Contribution
El Ghoul, A., Jermyn, I., & Zerubia, J. (2010, November). A theoretical and numerical study of a phase field higher-order active contour model of directed networks. Presented at 10th Asian Conference on Computer Vision, Queenstown

We address the problem of quasi-automatic extraction of directed networks, which have characteristic geometric features, from images. To include the necessary prior knowledge about these geometric features, we use a phase field higher-order active co... Read More about A theoretical and numerical study of a phase field higher-order active contour model of directed networks.

Segmentation of networks from VHR remote sensing images using a directed phase field HOAC model (2010)
Presentation / Conference Contribution
El Ghoul, A., Jermyn, I., & Zerubia, J. (2010, September). Segmentation of networks from VHR remote sensing images using a directed phase field HOAC model. Presented at ISPRS-Technical-Commission III Symposium on Photogrammetric Computer Vision and Image Analysis (PCV), Saint Mande

We propose a new algorithm for network segmentation from very high resolution (VHR) remote sensing images. The algorithm performs this task quasi-automatically, that is, with no human intervention except to fix some parameters. The task is made diffi... Read More about Segmentation of networks from VHR remote sensing images using a directed phase field HOAC model.

Extraction of arbitrarily shaped objects using stochastic multiple birth-and-death dynamics and active contours (2010)
Presentation / Conference Contribution
Kulikova, M., Jermyn, I., Descombes, X., Zhizhina, E., & Zerubia, J. (2010, January). Extraction of arbitrarily shaped objects using stochastic multiple birth-and-death dynamics and active contours. Presented at SPIE Conference on Electronic Imaging, San Jose, USA

We extend the marked point process models that have been used for object extraction from images to arbitrarily shaped objects, without greatly increasing the computational complexity of sampling and estimation. The approach can be viewed as an extens... Read More about Extraction of arbitrarily shaped objects using stochastic multiple birth-and-death dynamics and active contours.

A marked point process model with strong prior shape information for extraction of multiple, arbitrarily-shaped objects (2009)
Presentation / Conference Contribution
Kulikova, M., Jermyn, I., Descombes, X., Zhizhina, E., & Zerubia, J. (2009, December). A marked point process model with strong prior shape information for extraction of multiple, arbitrarily-shaped objects. Presented at Fifth International Conference on Signal-Image Technology & Internet-Based Systems (SITIS), 2009, Marrakesh

We define a method for incorporating strong prior shape information into a recently extended Markov point process model for the extraction of arbitrarily-shaped objects from images. To estimate the optimal configuration of objects, the process is sam... Read More about A marked point process model with strong prior shape information for extraction of multiple, arbitrarily-shaped objects.

A Markov random field model for extracting near-circular shapes (2009)
Presentation / Conference Contribution
Blaskovics, T., Kato, Z., & Jermyn, I. (2009, November). A Markov random field model for extracting near-circular shapes. Presented at 16th IEEE International Conference on Image Processing (ICIP) 2009, Cairo

We propose a binary Markov random field (MRF) model that assigns high probability to regions in the image domain consisting of an unknown number of circles of a given radius. We construct the model by discretizing the `gas of circles' phase field mod... Read More about A Markov random field model for extracting near-circular shapes.

A phase field higher-order active contour model of directed networks (2009)
Presentation / Conference Contribution
El Ghoul, A., Jermyn, I., & Zerubia, J. (2009, September). A phase field higher-order active contour model of directed networks. Presented at 2009 IEEE 12th International Conference on Computer Vision Workshops (Non-Rigid Shape Analysis and Deformable Image Alignment), at ICCV, Kyoto

The segmentation of directed networks is an important problem in many domains, e.g. medical imaging (vascular networks) and remote sensing (river networks). Directed networks carry a unidirectional flow in each branch, which leads to characteristic g... Read More about A phase field higher-order active contour model of directed networks.

Inflection point model under phase field higher-order active contours for network extraction from VHR satellite images (2009)
Presentation / Conference Contribution
El Ghoul, A., Jermyn, I., & Zerubia, J. (2009, August). Inflection point model under phase field higher-order active contours for network extraction from VHR satellite images. Presented at 17th European Signal Processing Conference 2009, Glasgow, Scotland

The segmentation of networks is important in several imaging domains, and models incorporating prior shape knowledge are often essential for the automatic performance of this task. We incorporate such knowledge via phase fields and higher-order activ... Read More about Inflection point model under phase field higher-order active contours for network extraction from VHR satellite images.

Bayesian classification of shapes hidden in point cloud data (2009)
Presentation / Conference Contribution
Srivastava, A., & Jermyn, I. (2009, January). Bayesian classification of shapes hidden in point cloud data. Presented at IEEE 13th Digital Signal Processing Workshop and 5th IEEE Signal Processing Education Workshop, 2009 (DSP/SPE 2009 ), Marco Island, USA

An interesting challenge in image processing is to classify shapes of polygons formed by selecting and ordering points in a 2D cluttered point cloud. This kind of data can result, for example, from a simple preprocessing of images containing objects... Read More about Bayesian classification of shapes hidden in point cloud data.

Lattice Green functions and diffusion for modelling traffic routing in ad hoc networks (2009)
Presentation / Conference Contribution
Sigelle, M., Jermyn, I., Perreau, S., & Jayasuriya, A. (2009, December). Lattice Green functions and diffusion for modelling traffic routing in ad hoc networks. Presented at 7th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, 2009. WiOPT 2009., Seoul

We describe basic properties of Markov chains on finite state spaces and their application to Green functions, partial differential equations, and their (approximate) solution using random walks on a graph. Attention is paid to the influence of bound... Read More about Lattice Green functions and diffusion for modelling traffic routing in ad hoc networks.

Phase diagram of a long bar under a higher-order active contour energy: application to hydrographic network extraction from VHR satellite images (2008)
Presentation / Conference Contribution
El Ghoul, A., Jermyn, I., & Zerubia, J. (2008, December). Phase diagram of a long bar under a higher-order active contour energy: application to hydrographic network extraction from VHR satellite images. Presented at 19th International Conference on Pattern Recognition, Tampa, Florida

The segmentation of networks is important in several imaging domains, and models incorporating prior shape knowledge are often essential for the automatic performance of this task. Higher-order active contours provide a way to include such knowledge,... Read More about Phase diagram of a long bar under a higher-order active contour energy: application to hydrographic network extraction from VHR satellite images.