Dr Zygmunt Szpak

Grant-Funded Researcher (C)

Australian Institute for Machine Learning - Projects

Faculty of Sciences, Engineering and Technology

I'm a computer scientist and senior research associate in the School of Computer Science at the University of Adelaide, South Australia. I work in the Australian Institute for Machine Learning on numerous industry-inspired computer vision and machine learning problems.

My Research
Career
Publications
Grants and Funding
Contact

When I am not engaged in a concrete industry project, my primary research endeavours are devoted to problems in projective parameter estimation, in the context of multiple-view geometry. The statistical estimation problems that I am interested in fall under the banner of non-linear errors-in-variables models.

You can find out more about my research themes here: https://zygmuntszpak.github.io/

Appointments

Date Position Institution name

2013 - ongoing Senior Research Associate The University of Adelaide
Language Competencies

Language Competency

Afrikaans Can speak

English Can read, write, speak and peer review

German Can read, write, speak and peer review

Polish Can read and speak

Date	Position	Institution name
2013 - ongoing	Senior Research Associate	The University of Adelaide

Language	Competency
Afrikaans	Can speak
English	Can read, write, speak and peer review
German	Can read, write, speak and peer review
Polish	Can read and speak

Education

Institution name	Country	Title
The University of Adelaide	Australia	PhD Computer Science
The University of KwaZulu-Natal	South Africa	MSc Computer Science (Cum Laude)
The University of KwaZulu-Natal	South Africa	Bachelor of Science Honours Computer Science (Summa Cum Laude)

Research Interests

Artificial Intelligence & Image Processing Computer Vision Pattern Recognition and Data Mining

Journals

Year	Citation
2021	Kuang, B., Pena, G., Szpak, Z., Edwards, S., Battersby, R., Cowled, P., . . . Fitridge, R. (2021). Assessment of a smartphone-based application for diabetic foot ulcer measurement.. Wound repair and regeneration : official publication of the Wound Healing Society [and] the European Tissue Repair Society, 29(3), 6 pages. DOI Scopus4 WoS4 Europe PMC1
2020	Pena, G., Kuang, B., Szpak, Z., Cowled, P., Dawson, J., & Fitridge, R. (2020). Evaluation of a Novel Three-Dimensional Wound Measurement Device for Assessment of Diabetic Foot Ulcers. ADVANCES IN WOUND CARE, 9(11), 9 pages. DOI Scopus6 WoS5 Europe PMC2
2020	Chojnacki, W., Szpak, Z., & Wadenbäck, M. (2020). The equivalence of two definitions of compatible homography matrices. Pattern Recognition Letters, 135, 38-43. DOI Scopus2 WoS1
2019	Chojnacki, W., & Szpak, Z. L. (2019). Determining ellipses from low-resolution images with a comprehensive image formation model. Journal of the Optical Society of America A, 36(2), 212-233. DOI
2015	Chojnacki, W., Szpak, Z., Brooks, M., & van Den Hengel, A. (2015). Enforcing consistency constraints in uncalibrated multiple homography estimation using latent variables. Machine Vision and Applications, 26(2-3), 401-422. DOI Scopus5 WoS4
2015	Szpak, Z., Chojnacki, W., & van den Hengel, A. (2015). Guaranteed ellipse fitting with a confidence region and an uncertainty measure for centre, axes, and orientation. Journal of Mathematical Imaging and Vision, 52(2), 173-199. DOI Scopus31 WoS29
2014	Szpak, Z., Chojnacki, W., Eriksson, A., & van den Hengel, A. (2014). Sampson distance based joint estimation of multiple homographies with uncalibrated cameras. Computer Vision and Image Understanding, 125, 200-213. DOI Scopus18 WoS15
2011	Szpak, Z., & Tapamo, J. (2011). Maritime surveillance: Tracking ships inside a dynamic background using a fast level-set. Expert Systems with Applications, 38(6), 6669-6680. DOI Scopus62 WoS50
2008	Szpak, Z. L., & Tapamo, J. -R. (2008). Automatic and interactive retinal vessel segmentation.. South Afr. Comput. J., 40, 23-30.

Conference Papers

Year	Citation
2019	Chojnacki, W., & Szpak, Z. L. (2019). Full explicit consistency constraints in uncalibrated multiple homography estimation. In Proceedings of the 14th Asian Conference on Computer Vision (ACCV 2018), as published in Lecture Notes in Computer Science Vol. 11361 (pp. 659-675). Cham, Switzerland: Springer. DOI Scopus1
2017	Neumann, A., Szpak, Z. L., Chojnacki, W., & Neumann, F. (2017). Evolutionary image composition using feature covariance matrices. In Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2017 Vol. abs/1703.03773 (pp. 817-824). online: ACM. DOI Scopus11 WoS6
2015	Szpak, Z., Chojnacki, W., & Van Den Hengel, A. (2015). Robust multiple homography estimation: an ill-solved problem. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition Vol. 07-12-June-2015 (pp. 2132-2141). Boston, MA: IEEE. DOI Scopus14 WoS11
2015	Faulkner, H., Shehu, E., Szpak, Z., Chojnacki, W., Tapamo, J., Dick, A., & Van Den Hengel, A. (2015). A study of the region covariance descriptor: impact of feature selection and image transformations. In Proceedings of the International Conference on Digital Image Computing: Techniques and Applications (pp. 1-8). Adelaide, SA.: IEEE. DOI Scopus6
2014	Ponte, G., Szpak, Z., Woolley, J., & Searson, D. (2014). Using specialised cyclist detection software to count cyclists and determine cyclist travel speed from video. In Proceedings of the 2014 Australasian Road Safety Research, Policing & Education Conference (pp. 1-13). Melbourne, Vic: ACRS.
2012	Szpak, Z., Chojnacki, W., & Van Den Hengel, A. (2012). A comparison of ellipse fitting methods and implications for multiple-view geometry estimation. In Proceedings of Digital Image Computing Techniques and Applications, DICTA 2012 (pp. 1-8). USA: IEEE. DOI Scopus10
2012	Szpak, Z., Chojnacki, W., & Van Den Hengel, A. (2012). Guaranteed ellipse fitting with the Sampson distance. In Proceedings of the12th European Conference on Computer Vision, ECCV 2012 Vol. 7576 LNCS (pp. 87-100). Germany: Springer-Verlag. DOI Scopus34 WoS24
2010	Chojnacki, W., Szpak, Z., Brooks, M., & Van Den Hengel, A. (2010). Multiple homography estimation with full consistency constraints. In Proceedings of DICTA 2010 (pp. 480-485). USA: IEEE. DOI Scopus10
2009	Szpak, Z., Tapamo, J., & Roy-Aikins, J. (2009). Design and implementation of an interactive interface for power plant simulation. In J. Otamendi, A. Bargiela, J. Montes, & L. Pedrera (Eds.), Proceedings - 23rd European Conference on Modelling and Simulation, ECMS 2009 (pp. 768-775). Rey Juan Carlos Univ, Madrid, SPAIN: EUROPEAN COUNCIL MODELLING & SIMULATION.

Z. Szpak, W. Chojnacki “Target Recognition and Measurement at the Limits of Resolution”, AUD 100k Defence Science Technology Organisation, 2017

Z. Szpak, W. Chojnacki “Parameter Estimation at the Limits of Resolution”, AUD 78k Defence Science Technology Organisation, 2016

Z. Szpak, J. Mackenzie “Sharing the knowledge required to successfully utilise object detection software for use in future research opportunities”, AUD 20k ECMS Faculty, Adelaide University, 2016

Position: Grant-Funded Researcher (C)
Phone: 83134479
Email: zygmunt.szpak@adelaide.edu.au
Fax: 83134366
Campus: North Terrace
Building: Australian Institute for Machine Learning, floor G
Org Unit: Australian Institute for Machine Learning - Projects

Dr Zygmunt Szpak

Appointments

Language Competencies

Education

Research Interests

Journals

Conference Papers

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