Paul Fieguth, PEng

Paul Fieguth, PEng
Professor, Associate Dean, Resources and Planning
Location: E7-7428
Phone: 519-888-4567 x43599,519-888-4567 x43600

Biography

Paul Fieguth is the Associate Dean, Resources & Planning for the Faculty of Engineering and a Professor in the Department of Systems Design Engineering. He is also a co-director of the Vision and Imaging Processing Lab) and the director of the Statistical Image Processing Lab) at the University of Waterloo.

His main areas of research lie in multiscale statistical modelling and machine learning. In particular, Professor Fieguth concentrates on the theory development and understanding of hierarchical/scale recursive estimation algorithms for multi-resolution stochastic processes. Such algorithms use a statistically meaningful strategy to break large estimation problems into smaller pieces, leading to vast improvements in efficiency.

Certainly a very pressing challenge is the amount of image data being collected -- satellite pictures, microscopic images, or Google Streetview. There are many image processing algorithms available for regular images, such as portraits from digital cameras, however for scientific imagery, such as satellite images of a forest, microscopic pictures of a cracks in concrete, or medical images of the body from an MRI, more specialized techniques are required.

Professor Fieguth's interests are to formulate mathematical models, such as the temperature of the earth's atmosphere or the expected topology of the brain, and to combine such models with measured data. Such mathematical operations are tremendously valuable for two reasons:

First, because they allow us to infer subtle results from the data, and second, because they allow us to test whether a given mathematical model makes sense or not, a crucial step in advancing our understanding. The problem, however, is that it is very difficult to solve these equations in a computer for large two- or three-dimensional problems. His research seeks to develop efficient alternatives to modeling and algorithms, either by examining the problem over a variety of scales, or by developing models having nonlocal connections.

Research Interests

  • Signal and Image Processing
  • Societal and Environmental Systems
  • Statistical Modeling
  • Multiscale Methods
  • Remote Sensing
  • Computer Vision
  • Pattern Analysis
  • Machine Learning

Education

  • 1995, Doctorate PhD, Massachusetts Institute of Technology, United States
  • 1993, SM, Massachusetts Institute of Technology, United States
  • 1991, Bachelor's BASc, University of Waterloo, Ontario

Awards

  • 2019 Distinguished Teaching Award, University of Waterloo
  • 2015 Award of Excellence in Graduate Supervision, University of Waterloo
  • 2011 IEEE Senior Member
  • 2018 Faculty of Engineering Outstanding Performance Award University of Waterloo
  • 2014 Faculty of Engineering Distinguished Performance Award University of Waterloo
  • 2001 Sanford Fleming Foundation Teaching Award, University of Waterloo

Service

  • 2020-2022 Associate Dean - Resources & Planning, Faculty of Engineering
  • 2020 Associate Dean - Outreach, Faculty of Engineering
  • 2019 Associate Dean - Undergraduate, Faculty of Engineering
  • 2019-2020 Associate Dean - Policies & Resources, Faculty of Engineering
  • 2017-2022 Board of Governors, University of Waterloo
  • 2016-2022 Senate, University of Waterloo
  • 2014-2016 Centre for Bioengineering and Biotechnology, University of Waterloo, Board Member
  • 2010-2019 Department Chair, Systems Design Engineering
  • 2005-2009 Associate Chair, Undergraduate, Systems Design Engineering
  • 2001-2002 Admissions, Systems Design Engineering

Professional Associations

  • 2018-2022 CESUN — Council of Engineering Systems Universities, Executive Committee
  • 2016-2022 Schlegel Research Institute for Aging, Board Member

Teaching*

  • SYDE 332 - Introduction to Complex Systems
    • Taught in 2017, 2018, 2019, 2020
  • SYDE 532 - Introduction to Complex Systems
    • Taught in 2021, 2022
  • SYDE 672 - Statistical Image Processing
    • Taught in 2018, 2020
  • SYDE 730 - Selected Topics in Societal-Environmental Systems
    • Taught in 2021, 2022

* Only courses taught in the past 5 years are displayed.

Selected/Recent Publications

  • A. Carrington, D. Manuel, P. Fieguth, T. Ramsay, V. Osmani, B. Wernly, C. Bennett, S. Hawken, O. Magwood, Y. Sheikh, M. McInnes, A. Holzinger, (2022), Deep ROC Analysis and AUC as Balanced Average Accuracy, for Improved Classifier Selection, Audit and Explanation, IEEE Transactions on Pattern Analysis and Machine Intelligence.
  • Zohreh Hosseinaee, Benjamin Ecclestone, Nicholas Pellegrino, Layla Khalili, Lyazzat Mukhangaliyeva, Paul Fieguth, and Parsin Haji Reza (2021), Functional photoacoustic remote sensing microscopy using a stabilized temperature-regulated stimulated Raman scattering light source, Optics Express, Volume 29, Issue 19, 29745-29754.
  • Xiaodan Hu, Mohamed A. Naiel, Zohreh Azimifar, Ibrahim Ben Daya, Mark Lamm, Paul Fieguth (2021), Non-stationary Content-Adaptive Projector Resolution Enhancement, Signal Processing: Image Communication, Volume 97, 116348.
  • Deniz Sera Ertay, Mohamed A Naiel, Mihaela Vlasea, Paul Fieguth (2021), Process Performance Evaluation and Classification via In-Situ Melt Pool Monitoring in Directed Energy Deposition, CIRP Journal of Manufacturing Science and Technology, Volume 35, 298-314.
  • Deniz Sera Ertay, Shima Kamyab, Mihaela Vlasea, Zohreh Azimifar, Thanh Ma, Allan Rogalsky, Paul Fieguth (2021), Towards Sub-Surface Pore Prediction Capabilities for Laser Powder Bed Fusion Using Data Science, Journal of Manufacturing Science and Engineering, Volume 143, 071016.
  • S. Farsangi, M. Naiel, M. Lamm, P. Fieguth, Efficient Direct Block Address Encoding for Single-Shot based 3D Reconstruction, Society for Information Display, 2021.
  • K. Sadatsharifi, M. Naiel, M. Lamm, P. Fieguth, Efficient Model Based Grid Intersection Detection for Single-Shot 3D Reconstruction, Canadian Conference on Electrical and Computer Engineering, 2021.
  • J. Tong, J. Shafiee, P. Fieguth, Incremental Generative Replay Embedding Toward an Effective Continual Learning Framework, Workshop on Continual Learning in Computer Vision CLVISION2021, 2021.
  • Paul Fieguth, Introduction to Complex Systems (Second Edition), Edition 2, 463 Pages, Springer Verlag, 2021.
  • A. Carrington, P. Fieguth, H. Qazi, A. Holzinger, H. Chen, F. Mayr, D. Manuel (2020), A new concordant partial AUC and partial c statistic for imbalanced data in the evaluation of machine learningalgorithms, BMC Medical Informatics and Decision Making, Volume 20, Issue 1, 1-12.
  • M. Naiel, D. Ertay, M. Vlasea, P. Fieguth (2020), Adaptive Vision-based Detection of Laser-Material Interaction for Directed Energy Deposition, Additive Manufacturing, Volume 36, 101468.
  • M. J. Shafiee, A. Jeddi, A. Nazemi, P. Fieguth, A. Wong (2020), Deep Neural Networks and Robust Autonomous Driving Systems, IEEE Signal Processing Magazine, Volume 38, Issue 1, 22-30.
  • B. Ecclestone, K. Bell, S. Abbasi, D. Dinakaran, F. van Landeghem, J. Mackey, P. Fieguth, P. Haji Reza (2020), Improving maximal safe brain tumor resection with photoacoustic remote sensing microscopy, Scientific Reports, Volume 10, 1-7.
  • S. Ertay, S. Kamyab, M. Vlasea, Z. Azimifar, H. Ma, A. Rogalsky, P. Fieguth, Prediction of Defects Based on Beam Path and Melt Pool Morphology Using Machine Learning for Laser Powder Bed Fusion, HI-AM Conference, Montreal, 2020.
  • A. Chung, P. Fieguth, A. Wong, Revisiting 2-Parent Evolutionary Synthesis for Efficient Deep Neural Networks, CVPR Workshop on WiCV, Online, 2020.
  • L. Haines, O. Kralj, S. Marschall, A. Gawish, P. Fieguth, N. Singal, H. Chew, D. Rootman, A. Slomovic, W. Hatch, K. Bizheva, L. Sorbara, Central corneal thickness changes after crosslinking combined with photorefractive keratectomy and associated predictive factors, Global Specialty Lens Symposium, Las Vegas, 2020.
  • J. Goetz, P. Fieguth, K. Kasiri*, X. Bodin, M. Marcer, A. Brenning (2019), Accounting for permafrost creep in high-resolution snow depth mapping by modelling sub-snow ground deformation, Remote Sensing of Environment, Volume 231, Issue 15, 111275.
  • L. Liu*, W. Ouyang, X. Wang, P. Fieguth, J. Chen, X. Liu, M. Pietikainen (2019), Deep Learning for Generic Object Detection: A Survey, International Journal on Computer Vision, Volume 128, Issue 2, 261-318.
  • J. Liu*, A. Scott, P. Fieguth (2019), Detection of Marginal Ice Zone in SAR Imagery using Curvelet based Features: A case study on the Canadian East Coast, SPIE Journal of Applied Remote Sensing, Volume 13, Issue 1, 014505.
  • L. Liu*, J. Chen, G. Zhao, P. Fieguth, X. Chen, M. Pietikainen (2019), Texture Classification in Extreme Scale Variations using GANet, IEEE Transactions on Image Processing, Volume 28, Issue 10, 3910-3922.
  • V. Sankar*, P. Fieguth, M. Lamm, Human Visual System Inspired Artifact Reduction in Projector Compensation, Society for Information Display — Display week symposium, Los Angeles, 2019.
  • X. Hu*, M. Naiel*, Z. Azimifar*, M. Lamm, P. Fieguth, Robust Visual Enhancement of Moving Contents in Projected Imagery, Society for Information Display — Display week symposium, Los Angeles, 2019.
  • X. Hu*, P. Fieguth, M. Naiel*, A. Wong, ClearGAN: Photo-Realistic High Resolution Text-to-Image Synthesis via Joint Inter-modal and Intra-modal Attention Modeling, Computer Vision and Pattern Recognition (CVPR) Workshop on Language and Vision, Los Angeles, 2019.
  • M. Post*, P. Fieguth, M. Naiel*, Z. Azimifar*, M. Lamm, FRESCO: Fast Radiometric Egocentric Screen Compensation, Computer Vision and Pattern Recognition (CVPR) NTIRE Workshop, Los Angeles, 2019.
  • X. Hu*, M. Naiel*, A. Wong, M. Lamm, P. Fieguth, RUNet: A Robust UNet Architecture for Image Super-Resolution, Computer Vision and Pattern Recognition (CVPR) Workshop on Women in Computer Vision, Los Angeles, 2019.
  • J. Shafiee*, P. Siva, A. Wong, P. Fieguth (2018), Real-time embedded motion detection via neural response mixture modeling, Journal of Signal Processing Systems, Volume 90, Issue 6, 931-946.
  • L. Liu*, J. Chen, P. Fieguth, G. Zhao, R. Chellappa, M. Pietikainen (2018), From BoW to CNN: Two Decades of Texture Representation for Texture Classification, International Journal of Computer Vision, Volume 127, Issue 1, 74-109.
  • A. Opal, W. Bradbeer*, C. Dyck*, D. Huynh*, C. Bachmann*, P. Fieguth, A Quantitative Impact Analysis of the Container Security Initiative (CSI), Transportation Research Board Annual Meeting, 2018.
  • P. Fieguth, Batteryless Solar and Demand-Side Control, Council of Engineering Systems Universities — Global Conference, Tokyo, 2018.
  • F. Saffih, P. Fieguth, Vehicle Longitudinal Acceleration Determination from Mobile Phone Sensor:An IoT System Solution for Intelligent Transportation, IEEE ISSPIT (International Symposium on Signal Processing and Information Technology), 2018.
  • L. Haines, O. Kralj, S. Marschall, A. Gawish*, P. Fieguth, N. Singal, H. Chew, D. Rootman, A. Slomovic, W. Hatch, K. Bizheva, L. Sorbara, Effect of age and pre-operative corneal topographyon epithelial and total corneal thickness changes after crosslinking surgery, American Academy of Optometry Annual Meeting, San Antonio, 2018.
  • X. Hu*, A. Chung*, P. Fieguth, A. Wong, F. Khalvati, M. Haider, ProstateGAN: Mitigating Data Bias via Prostate Diffusion Imaging Synthesis with Generative Adversarial Networks, NIPS 2018 Workshop on Machine Learning for Health, Montreal, 2018.
  • A. Chung*, P. Fieguth, A. Wong, Mitigating Architectural Mismatch During the Evolutionary Synthesis of Deep Neural Networks, NIPS 2018 Workshop on Meta-Learning, Montreal, 2018.
  • R. Bello-Cerezo*, P. Fieguth, F. Bianconi, LBP-Motivated Colour Texture Classification, ECCV Workshop on Compact and Efficient Feature Representation Learning, Munich, 2018.
  • P. Fieguth, Differential Equations, Agent Models, and Resilience, Council of Engineering Systems Universities (CESUN) --- Global Conference, Tokyo, 2018.
  • A. Hrynioswki*, I. BenDaya*, A. Gawish*, M. Lamm, A. Wong, P. Fieguth, Multi-Projector Resolution Enhancement through Biased Interpolation, Canada Robot Vision Conference, Toronto, 2018.
  • A. Ma, A. Gawish*, M. Lamm, A. Wong, P. Fieguth, Real-time Spatial-based Projector Resolution Enhancement, Society for Information Display --- Display week symposium, Los Angeles, 2018.
  • A. Carrington*, P. Fieguth, H. Chen, Measures of model interpretability for model selection, International Cross-Domain Conference for Machine Learning and Knowledge Extraction, Hamburg, 2018.
  • A. Chung*, P. Fieguth, A. Wong, Nature vs. Nurture: The Role of Environmental Resources in Evolutionary Deep Intelligence, Canada Robot Vision Conference, Toronto, 2018.
  • L. Liu*, P. Fieguth, Y. Guo, X. Wang, M. Pietikainen (2017), Local Binary Features for Texture Classification: Taxonomy and Experimental Study, Pattern Recognition, Volume 62, Issue C, 135-160.
  • J. Shafiee*, A. Wong, P. Fieguth, Forming a random field via stochastic cliques: From random graphs to fully connected random fields, Future Technologies Conference, Vancouver, 2017.
  • K. Carter, L. Haines, B. MacLellan, O. Kralj, A. Gawish*, P. Fieguth, K. Bizheva, L. Sorbara, Epithelial and Total Corneal Thickness Measurement with Optical Coherence Tomography in Keratoconics and Controls Wearing Various Lens Types, American Academy of Optometry, Chicago, 2017.
  • A. Chung*, A. Wong, P. Fieguth, The Mating Rituals of Deep Neural Networks: Learning Compact Feature Representations through Sexual Evolutionary Synthesis, ICCV Workshop on Compact and Efficient Feature Representation Learning, Venice, 2017.
  • P. Fieguth, Introduction to Complex Systems, 450 Pages, Springer Verlag, 2017.
  • M. Shafiee*, P. Siva, C. Scharfenberger, P. Fieguth, A. Wong (2016), NeRD: a Neural Response Divergence Approach to Visual saliency detection, IEEE Signal Processing Letters, Volume 23, Issue 10, 1404-1408.
  • C. Liu, A. Wong, A. Moayed, P. Fieguth, H. Bie, K. Bizheva (2016), Automatic tracking of pupillary dynamics from in-vivo functional optical coherence tomography images, Computer Methods in Biomechanics and Biomedical Engineering, Volume 4, Issue 5, 306-316.
  • M.J. Shafiee*, A. Wong, P. Fieguth (2016), Deep Randomly-connected Conditional Random Fields For Image Segmentation, IEEE Access, Volume 5, 366-378.
  • J. Liu*, K.A. Scott, A. Gawish*, P. Fieguth (2016), Automatic Detection of the Ice Edge in SAR Imagery using Curvelet Transform and Active Contour, Remote Sensing, Volume 8, Issue 6, 480.
  • L. Liu*, P. Fieguth, G. Zhao, M. Pietikainen, D. Hu (2016), Extended local binary patterns for face recognition, Information Sciences, Volume 358-359, 56-72.
  • L. Liu*, L. Wang, L. Zhao, P. Fieguth (2016), Random projections and Single BoW for fast and Robust texture segmentation, Information Sciences, Volume 370-371, 428-445.
  • L. Liu*, So. Lao, P. Fieguth, Y. Guo, X. Wang, M. Pietikainen (2016), Median Robust Extended Local Binary Pattern for Texture Classification, IEEE Transactions on Image Processing, Volume 25, Issue 3, 1368-1381.
  • L. Liu*, P. Fieguth, X. Wang, M. Pietikainen, D. Hu, Evaluation of LBP and Deep Texture Descriptors with a New Robustness Benchmark, European Conference on Computer Vision (ECCV), Amsterdam, 2016.
  • K. Kasiri*, P. Fieguth, D.A. Clausi, Self-similarity measure for multi-modal image registration, IEEE International Conference on Image Processing (ICIP), Phoenix, 2016.
  • K. Kasiri*, P. Fieguth, D.A. Clausi, Sorted self-similarity for multi-modal image registration, Engineering in Medicine and Biology Society (EMBC), Orlando, 2016.
  • M.J. Shafiee*, P. Siva, P. Fieguth, A. Wong, Embedded Motion Detection via Neural Response Mixture Background Modeling, Computer Vision and Pattern Recognition (CVPR), Las Vegas, 2016.
  • K. Kasiri*, D. Clausi, P. Fieguth (2015), Structural Representation: Reducing Multi-Modal Image Registration to Mono-Modal Problem, Vision Letters, Volume 1, VL120.
  • L. Liu*, P. Fieguth, D. Hu, X. Wei, G. Kuang (2015), Fusing Sorted Random Projections for Robust Texture and Material Classification, IEEE Transactions on Circuits and Systems for Video Technology, Volume 25, Issue 3, 482-496.
  • A. Wong, C. Liu, X. Wang, P. Fieguth, H. Bie (2015), Homotopic non-local regularized reconstruction from sparse positron emission tomography measurements, BMC Medical Imaging, Volume 15, Issue 10, 1.
  • E. Barshan*, P. Fieguth (2015), Stage-wise training: an improved feature learning strategy for deep models, Journal of Machine Learning Research, Volume 44, 49-59.
  • C. Koch, K. Georgieva, V. Kasireddy, B. Akinci, P. Fieguth (2015), A review on computer vision based defect detection and condition assessment of concrete and asphalt civil infrastructure, Advanced Engineering Informatics, Volume 29, 196-210.
  • M.J. Shafiee*, A. Chung*, A. Wong, P. Fieguth, Improved fine structure modeling via guided stochastic clique formation In fully connected conditional random fields, IEEE Conference on Image Processing, Quebec City, 2015.
  • E. Barshan*, P. Fieguth, A. Wong, Scalable multi-neighborhood learning for convolutional networks, 25th IEEE International Workshop on Machine Learning for Signal Processing, Boston, 2015.
  • G. Mwangi*, C. Garbe, P. Fieguth, Probabilistic Continuous Edge Detection using Local Symmetry, IEEE International Conference on Image Processing, Quebec City, 2015.
  • G. Mwangi*, C. Garbe, P. Fieguth,, Thermography Spatial Resolution Enhancement By Non-Rigid Registration with Visible Imagery, IEEE International Conference on Image Processing, Quebec City, 2015.
  • A. Gawish*, P. Fieguth, External forces for active contours using the undecimated wavelet transform, IEEE International Conference on Image Processing, Quebec City, 2015.
  • L. Liu*, P. Fieguth, M. Pietikäinen, S. Lao, Median Robust Extended Local Binary Pattern for Texture Classification, IEEE International Conference on Image Processing, Quebec City, 2015.
  • E. Barshan*, C. Scharfenberger, M. Lamm, P. Fieguth, Resolution Enhancement Based on Shifted Superposition, SID Symposium '15, San Jose, 2015.
  • L. Liu*, Y. Long, P. Fieguth, B. Yang, G. Zhao (2014), BRINT: Binary Rotation Invariant and Noise Tolerant Texture Classification, IEEE Transactions on Image Processing, Volume 23, Issue 7, 3071-3084.
  • K. Kasiri*, P. Fieguth, D. Clausi, Cross modality label fusion in multi-atlas segmentation, ICIP, Paris, 2014.
  • E. Barshan*, P. Fieguth, Scalable learning for restricted Boltzmann machines, ICIP, Paris, 2014.
  • J. Shafiee*, A. Wong, P. Siva, P. Fieguth, Efficient Bayesian inference using fully connected conditional random fields, ICIP, Paris, 2014.
  • L. Liu*, P. Fieguth, G. Zhao, M. Pietkainen, Extended local binary pattern fusion for face recognition, ICIP, Paris, 2014.
  • C. Scharfenberger, A. Jain*, A. Wong, P. Fieguth, Image salience detection via multi-scale statistical non-redundancy modeling, ICIP, Paris, 2014.
  • A. Gawish*, P. Fieguth, S. Marschall, K. Bizheva, Undecimated hierarchical active contours for OCT image segmentation, ICIP, Paris, 2014.
  • K. Kasiri*, D. Clausi, P. Fieguth, Multi-modal image registration using structural features, IEEE Engineering in Medicine and Biology Society, Chicago, IEEE EMBC, 2014.
  • A. Carrington*, P. Fieguth, H. Chen, A New Mercer Sigmoid Kernel for Clinical Data Classification, IEEE Engineering in Medicine and Biology Society, Chicago, IEEE EMBC, 2014.
  • S. Marschall, A. Gawish*, Y. Feng, L. Sorbara, P. Fieguth, K. Bizheva, Accuracy evaluation of scleral lens thickness and radius of curvature using high-resolution SD- and SS-OCT, SPIE Photonics West, San Francisco, SPIE, 2014.
  • S. Schwartz, C. Liu, A. Wong, D. Clausi, P. Fieguth, K. Bizheva (2013), Energy-guided learning approach to compressive FD-OCT, Optics Express, Volume 21, Issue 1, 329-344.
  • J. Eichel*, A. Wong, P. Fieguth, D. Clausi (2013), Robust Spectral Clustering using Statistical Sub-Graph Affinity Model, PLOS One, Volume 8, Issue 12, E82722.
  • W. Campaigne*, P. Fieguth (2013), Frozen State Hierarchical Annealing, IEEE Transactions on Image Processing, Volume 22, Issue 4, 1486-1497.
  • J. Shafiee *, Z. Azimifar*, P. Fieguth (2013), How Conditional Random Fields Learn Dynamics: An Example-Based Study, Computer Communication & collaboration, Volume 1, Issue 1.
  • F. Bachl*, P. Fieguth, C. Garbe, Bayesian Inference On Integrated Continuity Fluid Flows And Their Application To Dust Aerosols, IGARSS 2013, Melbourne, 2013.
  • L. Liu*, B. Yang, P. Fieguth, Z. Yang, Y. Wei, BRINT: A Binary Rotation Invariant and Noise Tolerant Texture Descriptor, ICIP 2013, Melbourne, 2013.
  • S. Marschall, A. Gawish*, Y. Feng, L. Sorbara, P. Fieguth, K. Bizheva, In-vivo imaging of keratoconic corneas using high-speed high-resolution swept-source OCT, SPIE, San Francisco, SPIE, vol. 8802, 2013.
  • C. Liu, A. Moyed, A. Wong, P. Fieguth, V. Chan, B. Bie, K. Bizheva, Automatic algorithm for measuring visually evoked pupil size changes from OCT images, SPIE, San Francisco, Ophthalmic Technologies XXIII, 2013.
  • Liu C*, Wong A, Bizheva K, Fieguth P (2012), Homotopic, non-local sparse reconstruction of optical coherence tomography imagery, Optics Express, Volume 20, Issue 9, 10200-10211.
  • Liu L, Fieguth P, Zhao L, Long Y, Kuang G (2012), Extended Local Binary Patterns for Texture Classification, Image and Vision Computing, Volume 30, Issue 2, 86-99.
  • Brenning A, Long S, Fieguth P (2012), Detecting rock glacier flow structures using Gabor filtering and IKONOS imagery, Remote Sensing of Environment, Volume 125, 227-237.
  • Azimifar Z*, Amiri M, Fieguth P, Jernigan E (2012), Empirical Study of Wavelet Domain Image Joint Statistics and Proposition of An Ef?cient Correlation Map, Journal of Mathematical Imaging and Vision, Volume 43, Issue 1, 24-38.
  • Kumar A*, Wong A, Fieguth P, Clausi D, Multi-Scale Tensor Vector Field Active Contour, ICIP 2012, Orlando, 2012.
  • Jain A*, Wong A, Fieguth P, Saliency Detection Via Statistical Non-Redundancy, ICIP 2012, Orlando, 2012.
  • Liu Y*, He D, Fieguth P, Adaptive Post-Filtering Based On Local Binary Patterns, ICIP 2012, Orlando, 2012.
  • Liu C*, Fieguth P, Garbe C, Background Subtraction And Dust Storm Detection, IGARSS 2012, Munich, 2012.
  • Bachl F, Fieguth P, Garbe C, Classifying And Tracking Dust Plumes From Passive Remote Sensing, IGARSS 2012, Munich, 2012.
  • Zaboli S*, Fieguth P, Bizheva K, Extraction of the optical attenuation coef?cient of human corneal stroma from UHROCT tomograms, SPIE Photonics West, San Fransisco, 2012.
  • Liu C*, Wong A, Bizheva K, Fieguth P, Bie H, Non-local sparse reconstruction of OCT images, SPIE Photonics West, San Fransisco, 2012.
  • Liu L*, Fieguth P, Clausi D (2011), Sorted random projections for robust rotation invariant texture classification, Pattern Recognition, Volume 45, Issue 6, 2405–2418.
  • Liu Y*, Wong A, Fieguth P (2011), Synthesis of Remote Sensing Label Fields Using a Tree-Structured Hierarchical Model, IEEE Trans. Geoscience and Remote Sensing, Volume 49, Issue 6, 2060-2070.
  • Liu L*, Fieguth P (2011), Extended local binary patterns for texture classification, Image and Vision Computing, Volume 30, Issue 2, 86-99.
  • Wong A, Mishra A*, Zhang W, Fieguth P, Clausi D (2011), Stochastic image denoising based on markov-chain Monte Carlo sampling, IEEE Trans. Signal Processing, Volume 91, Issue 8, 2112-2120.
  • Wong A, Scharcanski J, Fieguth P (2011), Automatic skin lesion segmentation via iterative stochastic region merging, IEEE Trans. Information Technology in Biomedicine, Volume 15, Issue 6, 929-936.
  • Mishra A*, Fieguth P, Clausi D (2011), Decoupled active contour for boundary detection, IEEE PAMI, Volume 33, Issue 2, 310-324.
  • Liu L*, Fieguth P (2011), Texture classification from random features, IEEE PAMI, Volume 34, Issue 3, 574-586.
  • Zhang W, Wong A, Mishra A*, Fieguth P, Clausi D (2011), Ef?cient Globally-Optimal Registration of Remote Sensing Imagery via Quasi-Random Scale Space Structural Correlation Energy Functional, IEEE Geoscience and Remote Sensing Letters, Volume 8, Issue 5, 997-1001.
  • Leigh A, Wong A, Clausi D, Fieguth P, Comprehensive analysis on the effects of noise estima- tion strategies on image noise artifact suppression performance, IEEE International Symposium of Multimedia, Dana Point, 2011.
  • Liu L*, Fieguth P, Kuang G, Zha H, Sorted Random Projections for Robust Texture Classi?cation, International Conference on Computer Vision (ICCV), Barcelona, 2011.
  • Mishra A*, Wong A, Fieguth P, Clausi D, Multi-Scale 3D Representation Via Volumetric Quasi- Random Scale Space, IEEE ICIP, Brussels, 2011.
  • Liu Y*, Wong A, Fieguth P, A Structure-guided Conditional Sampling Model for Video Resolu- tion Enhancement, IEEE ICIP, Brussels, 2011.
  • Liu L*, Fieguth P, Kuang G, Combining Sorted Random Features for Texture Classi?cation, IEEE ICIP, Brussels, 2011.
  • Kumar A*, Wong A, Mishra A*, Clausi D, Fieguth P, Tensor Vector Field Based Active Contours, IEEE ICIP, Brussels, 2011.
  • Moayedi F, Azimifar Z*, Fieguth P, Kazemi A, Adaptive Multi-Resolution CRF-based Contour Tracking, IEEE ICIP, Brussels, 2011.
  • Liu L*, Fieguth P, Kuang G, Generalized Local Binary Patterns for Texture Classi?cation, British Machine Vision Conference, Dundee, 2011.
  • Mishra A*, Fieguth P, Clausi D, From Active Contours to Active Surfaces, CVPR, Colorado Springs, 2011.
  • Zaboli S*, Fieguth P, Hyun C, Simpson T, Hutchings N, Sorbara L, Bizheva K, Hypoxia Induced Changes in the Total Attenuation Coef?cient of the Human Cornea Measured In-vivo with Ultrahigh Resolution Optical Coherence Tomography, The association for Research in Vision and Ophthalmology (ARVO2011), Fort Lauderdale, 2011.
  • Eichel J*, Clausi D, Fieguth P, Precise High-Speed Multi-Target Multi-Sensor Local Positioning System, Computer and Robot Vision (CRV), St. John, 2011.
  • Cavan N*, Fieguth P, Clausi D, Autocalibration: Finding In?nity in Projective Reconstructions, Computer and Robot Vision (CRV), St. John, 2011.
  • Eichel J*, Lee D, Wong A, Fieguth P, Clausi D, Bizheva K, Despeckling vs Averaging of retinal UHROCT tomograms: advantages and limitations, SPIE, San Jose, 2011.
  • Lee D, Bizheva K, Wong A, Eichel J*, Fieguth P, Clausi D, Despeckling vs averaging of retinal UHROCT tomograms: advantages and limitations, Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XV, San Jose, 2011.
  • Eichel J*, Lee D, Wong A, Fieguth P, Clausi D, Bizheva K, Quantitative comparison of despeckling and frame-averaging approaches to processing retinal OCT tomograms, BIOS, San Fransisco, 2011.
  • Fieguth P, Mishra A*, Wong A, Clausi D, Nonparametric sample-based methods for image understanding, 137-153, World Scienti?c Publishing, 2011.
  • Kachouie N*, Fieguth P, Gamble D, Jervis E, Ezziane Z, Khademhosseini A (2010), Constrained Watershed Method to Infer Morphology of Mammalian Cells in Microscopic Images, Cytometry A, Volume 77A, Issue 12, 1148-1159.
  • Wong A*, Clausi D, Fieguth P (2010), CPOL: complex phase order likelihood as a similar measure for MR-CT registration, Medical Image Analysis, Volume 14, Issue 1, 50-57.
  • Mishra A*, Wong A, Clausi D, Fieguth P (2010), Quasi-random nonlinear scale space, Pattern Recognition, Volume 31, Issue 13, 1850-1859.
  • Kachouie N*, Fieguth P, Jervis E (2010), A probabilistic cell model in background corrected image sequences, Biomedical Engineering Online, Volume 9, Issue 57, 1.
  • Wong A, Mishra A*, Fieguth P, Clausi D (2010), Sparse reconstruction of breast MRI using homotopic L0 minimization, IEEE Trans. on Biomedical Engineering, Volume 60, Issue 3, 743-752.
  • Liu L*, Fieguth P, Kuang G, Compressed sensing for robust texture classi?cation, 10th Asian Conference on Computer Vision (ACCV’10), Queens Town, 383-396, 2010.
  • Eichel J*, Clausi D, Bizheva K, Fieguth P, Automated 3D Reconstruction and Segmentation from Optical Coherence Tomography, ECCV, Crete, 2010.
  • Ahmadi E, Azimifar Z*, Fieguth P, Ayatollahi S, Image synthesis using conditional random ?elds, ICIP, 2010.
  • Shafaiee M J*, Azimifar Z*, Fieguth P, Model-based tracking: temporal conditional random ?elds, ICIP, 2010.
  • Wong A, Fieguth P, A new Bayesian source separation approach to blind decorrelation of SAR data, IGARSS, Honolulu, 4035-4038, 2010.
  • Liu Y*, Wong A, Fieguth P, Remote sensing image synthesis, IGARSS, Honolulu, 2467-2470, 2010.
  • Mishra A*, Wong A, Clausi D, Fieguth P, A Bayesian Information Flow Approach to Image Segmentation, CRV, Ottawa, 2010.
  • Wong A, Mishra A*, Clausi D, Fieguth P, Mammogram Image Superresolution Based on Statistical Moment Analysis, CRV, Ottawa, 2010.
  • Liu L*, Fieguth P, Texture Classi?cation using Compressed Sensing, CRV, Ottawa, 2010.
  • Wong A*, Mishra A*, Clausi D, Fieguth P, Quasi-Random Scale Space Approach to Robust Keypoint Extraction in High-Noise Environments, CRV, Ottawa, 2010.
  • Mishra A*, Fieguth P, Clausi D, Decoupled Active Surface for Volumetric Image Segmentation, CRV, Ottawa, 2010.
  • Zaboli S*, Tabibiazar A, Fieguth P, Organ Recognition using Gabor Filters, CRV, Ottawa, 2010.
  • Fieguth P, Statistical Image Processing and Multidimensional Modeling, 454 Pages, Springer, 2010.
  • Wong A*, Mishra A*, Yates J, Clausi D, Fieguth P, Callaghan J (2009), Intervertebral Disc Segmentation and Volumetric Reconstruction from Peripheral Quantitative Computed Tomography Imaging, IEEE Transactions on Biomedical Engineering, Volume 56, Issue 11, 2745-2751.
  • Mohebi A*, Fieguth P, Ioannidis M (2009), Statistical Fusion of Two-Scale Images of Porous Media, Advances in Water Resources, Volume 32, Issue 11, 1567-1579.
  • Alexander S*, Fieguth P, Ioannidis M, Vrscay E (2009), Hierarchical Annealing for Synthesis of Binary Porous Media Images, Mathematical Geosciences, Volume 41, Issue 4, 357-378.
  • Liu Y*, Fieguth P, Parallel Hidden Hierarchical Fields for Multi-scale Reconstruction, EMMCVPR, Bonn, 2009.
  • Mohebi A*, Liu Y*, Fieguth P, Hierachical Sampling with Constraints, ICIAR, Halifax, 2009.
  • Liu Y*, Fieguth P, Image Resolution Enhancement with Hierarchical Hidden Fields, ICIAR, Halifax, 2009.
  • Mishra A*, Fieguth P, Clausi D, A Robust Modular Wavelet Network Based Symbol Classifier, ICIAR, Halifax, 2009.
  • Mohebi A*, Fieguth P, Ioannidis M, Modeling and Reconstruction of Two-Scale Porous Media Using MRI Measurement, Fourth Biot Conference on Poromechanics, 2009.
  • Mishra A*, Eichel J*, Fieguth P, Clausi D, VizDraw: A Platform to Convert Online Hand Written Graphics into Computer Graphics, ICIAR, Halifax, 377-386, 2009.
  • Liu Y*, Mohebi A, Fieguth P, Modeling of Multiscale Porous Media Using Multiple Markov Random Fields, Fourth Biot Conference on Poromechanics, 2009.
  • Wong A, Clausi D, Fieguth P, SEC: Stochastic ensemble consensus approach to unsupervised SAR sea-ice segmentation, Canadian Conference on Computer and Robot Vision (CRV), Kelowna, 2009.
  • Mishra A*, Fieguth P, Clausi D, A robust modular wavelet network based symbol classi?er, Vision and Image Processing Workshop, Waterloo, 2009.
  • Mishra A*, Eichel J*, Fieguth P, Clausi D, VizDraw: A platform to convert online hand written graphics into computer graphics, Vision and Image Processing Workshop, Waterloo, 2009.
  • Wong A, Clausi D, Fieguth P, Adaptive Monte Carlo Retinex Method for Illumination and Re?ectance Separation and Color Image Enhancement, Canadian Conference on Computer and Robot Vision (CRV), Kelowna, 2009.
  • Wong A, Clausi D, Fieguth P, Adaptive Monte Carlo Retinex method for illumination and re?ectance separation and color image enhancement, Vision and Image Processing Workshop, Waterloo, 2009.
  • Eichel J*, Mishra A*, Clausi D, Fieguth P, Bizheva K, A Novel Algorithm for Extraction of the Layers of the Cornea, Canadian Conference on Computer and Robot Vision (CRV), Kelowna, 313-320, 2009.
  • Mishra A*, Eichel J*, Fieguth P, Clausi D, SmartDraw: A Platform to Convert Online Handwritten Graphics into Printed Graphics, Graduate Student Research Conference, Waterloo, 2009.
  • Eichel J*, Mishra A*, Clausi D, Fieguth P, Bizheva K, A Novel Algorithm for Extraction of the Layers of the Cornea, Graduate Student Research Conference, Waterloo, 2009.
  • Bizheva K, Hyun C, Eichel J*, Hariri S, Mishra K*, Clausi D, Fieguth P, Simpson T, Hutchings N, Evaluation of hypoxic swelling of human cornea with high speed ultrahigh resolution optical coherence tomography, SPIE, Lake Buena Vista, 2009.
  • Wong A, Mishra A*, Fieguth P, Clausi D, An Adaptive Monte Carlo Approach to Nonlinear Image Denoising, ICPR, Tampa, 2008.
  • Wong A, Clausi D, Fieguth P, Phase-Adaptive Image Signal Fusion using Complex-valued Wavelets, ICPR, Tampa, 2008.
  • Wong A, Clausi D, Fieguth P, Automatic Registration of Inter-band and Inter-sensor Images using Robust Complex Wavelet Feature Representations, PRRS, Tampa, 2008.
  • Mishra A*, Wong A, Clausi D, Fieguth P, Adaptive Nonlinear Image Denoising and Restoration Using a Cooperative Bayesian Estimation Approach, IEEE ICVGIP08, Bhubaneswar, 2008.
  • Amiri M, Azimifar Z*, Fieguth P, Correlated non-linear wavelet shrinkage, ICIP-08, San Diego, 2008.
  • Mishra A*, Fieguth P, Clausi D, Robust Snake Convergence Based On Dynamic Programming, ICIP, San Diego, 2008.
  • Wong A, Fieguth P, Clausi D, A Perceptually Adaptive Approach to Image Denoising using Anisotropic Non-local Means, ICIP, San Diego, 2008.
  • Mohebi A*, Fieguth P, Statistical Fusion and Sampling of Scienti?c Images, ICIP, San Diego, 2008.
  • Kachouie N*, Fieguth P, Background Estimation For Microscopic Cellular Images, ICIP, San Diego, 2008.
  • Zhang W, Wong A, Mishra A*, Fieguth P, Clausi D, Improved Interactive Medical Image Seg- mentation Using Enhanced Intelligent Scissors, EMBC’08, Vancouver, 2008.
  • Kachouie N*, Fieguth P, Jervis E, Watershed Deconvolution for Cell Segmentation, EMBC’08, Vancouver, 2008.
  • Wong A, Mishra A*, Fieguth P, Clausi D, Dunk N, Shape-Guided Active Contour Based Seg- mentation and Tracking of Lumbar Vertebrae in Video Fluoroscopy Using Complex Wavelets, EMBC’08, Vancouver, 2008.
  • Mishra A*, Fieguth P, Clausi D, Accurate Boundary Localization using Dy- namic Programming on Snakes, Canadian Conference on Computer and Robot Vision (CRV), Windsor, 261 - 268, 2008.
  • Kachouie N*, Fieguth P (2007), Extended-Hungarian-JPDA: Exact Single-Frame Stem Cell Tracking, IEEE Trans. on Biomedical Engineering, Volume 54, Issue 11, 2011-2019.
  • Tan P, Gamble D, Kelly K, Bains J, Wong J, Hughes N, Kachouie N*, Fieguth P, McNagnyl K, Jervis E, Imaging Informatics and Cell Shape Analysis: Examining the Role of NHERF-1 and Podocalyxin in Uropod Formation, Stem Cell Network Annual General Meeting, Toronto, 2007.
  • Nezamoddini-Kachouie N*, Fieguth P, Toward an Optimal Solution for Multitarget Tracking, ICIP, San Antonio, 2007.
  • Wesolkowski S*, Fieguth P, A Probabilistic Shading Invariant Color Distance Measure, EUSIPCO’07, Poznan, 2007.
  • Nezamoddini-Kachouie N*, Fieguth P, Stem Cell Localization: A Deconvolution Problem, International Conference of the IEEE Engineering in Medicine and Biology, Lyon, 2007.
  • Mohebi A*, Fieguth P, Constrained Sampling Using Simulated Annealing, ICIAR, Montreal, 2007.
  • Nezamoddini-Kachouie N*, Fieguth P, A Medical Texture Local Binary Pattern (MTLBP) for TRUS Prostate Segmentation, International Conference of the IEEE Engineering in Medicine and Biology, Lyon, 2007.
  • Sinha S*, Fieguth P (2006), Morphological Segmentation and Classi?cation of Underground Pipe Images, Machine Vision and Applications, Volume 17, Issue 1, 21-31.
  • Sinha S*, Fieguth P (2006), Segmentation of Buried Concrete Pipe Images, Automation in Construction, Volume 15, Issue 1, 47-57.
  • Jin F*, Fieguth P, Winger L (2006), Wavelet Video Denoising with Regularized Multiresolution Motion Estimation, EURASIP Journal on Applied Signal Processing, Volume 2006, 1-11.
  • Kachouie N*, Fieguth P, Ramunas J, Jervis E (2006), Probabilistic Model-Based Cell Tracking, International Journal of Biomedical Imaging, Volume 2006, 10 pages.
  • Sinha S*, Fieguth p (2006), Neuro-Fuzzy Network for the Classi?cation of Buried Pipe Defects, Automation in Construction, Volume 15, Issue 1, 73-83.
  • Sinha S*, Fieguth P (2006), Automated Detection of Crack Defects in Buried Concrete Pipe Images, Automation in Construction, Volume 15, Issue 1, 58-72.
  • Mohebi A*, Fieguth P, Posterior Sampling of Scienti?c Images, ICIAR, Montreal, 2006.
  • Campaigne W*, Fieguth P, Alexander S*, Frozen-State Hierarchical Annealing, ICIAR, Povoa de Varzim, 2006.
  • Nezamoddini-Kachouie N*, Fieguth P, Rahnamayan S, An Elliptical Level Set Method for Auto- matic TRUS Prostate Image Segmentation, IEEE-ISSPIT, Vancouver, 2006.
  • Nezamoddini-Kachouie N*, Fieguth P, Ramunas J, Jervis E, A Statistical Thresholding Method for Cell Tracking, IEEE-ISSPIT, Vancouver, 2006.
  • Nezamoddini-Kachouie N*, Fieguth P, A Combined Bayesshrink Wavelet-Ridgelet Technique for Image Denoising, IEEE-ICME, Toronto, 2006.
  • Wesolkowski S*, Fieguth P, Hierarchical Region Mean-Based Image Segmentation, Canadian Robotic Vision Conference CRV’06, Quebec City, 2006.
  • Kellah F*, Fieguth P, Murray J, Allen M (2005), Statistical processing of large image sequences, IEEE Trans. Image Processing, Volume 14, Issue 1, 80-93.
  • Venema H, Calamai P, Fieguth P (2005), Forest structure optimization using evolutionary programming and landscape ecology metrics, European J. of Operations Research, Volume 164, Issue 2, 423-439.
  • Jin F*, Fieguth P, Winger L, Image Denoising using Complex Wavelets and Markov Prior Models, ICIAR, Toronto, 2005.
  • Azimifar Z*, Fieguth P, Jernigan E, Correlated wavelet shrinkage: Models of local random ?elds across multiple resolutions, ICIP, Genoa, 2005.
  • kachouie N*, Lee L*, Fieguth P, A probabilistic living cell segmentation model, ICIP’05, Genoa, 2005.
  • Kachouie N*, Fieguth P, Ramunas J, Jervis E, A Narrow Band Level Set Method with Dynamic Velocity for Embryonic Stem Cell Cluster Segmentation, ICIAR, Toronto, 2005.
  • Quddus A, Fieguth P, Basir O, Adaboost and Support Vector Machines for White Matter Lesion Segmentation in MR Images, 27th International IEEE Medicine and Biology Conference, Shanghai, 2005.
  • Kachouie N*, Fieguth P, A Model-Based Hematopoietic Stem Cell Tracker, ICIAR, Toronto, 2005.
  • Alexander S*, Fieguth P, Vrscay E, Discrete-State Modeling of Porous Media over Multiple Scales, SIAM Conference on Mathematical and Computational Issues in the Geosciences, Avignon, 2005.
  • Kachouie N*, Fieguth P, A Gabor Based Technique for Image Denoising, CCECE’05, Saskatoon, 2005.

Patents

  • 2019 X. Hu, M. Naiel, Z. Azimifar, I. Daya, M. Lamm, P. Fieguth: Device, system and method for enhancing one or more of high contrast regions and moving regions in projected images, Filed Provisional Patent No. P7972US00.
  • 2018 M. Post, P. Fieguth, M. Lamm: Projection-surface photometric compensation, Filed US Patent No. P7758US00.
  • 2018 B. Ma, A. Gawish, A. Wong, P. Fieguth, M. Lamm: Real-time spatial-based resolution enhancement using shifted superposition, US Patent App.15/676,394 / P6932US00

Graduate Studies