Qualifications and Awards
- 2011 D.Phil. in Computer Science.
- 2009 Best Paper Award in Telemedicine and e-Health Section, HSI 2009.
- 2008 Professor Yasuhiko Dote Award for Best Workshop Paper, CSTST 2008.
- 2006 Hoare Prize for Computer Science.
MA (Oxon.), DPhil
Postdoctoral Research Associate
- Stipendiary Lecturer in Computer Science (Hertford)
- Research Member (Wolfson)
Research and Development Summary
My current role (which commenced in November 2013) is focused on object detection and tracking as part of Stephen Hicks' smart glasses project, and straddles the divide between research and development. Initial work has focused on the real-time detection of planar objects such as hospital signs using template-matching techniques based on the LINE-2D approach of Hinterstoisser et al.
Stuart Golodetz obtained his DPhil in Computer Science at the University of Oxford in 2011, working on 3D image segmentation and feature identification. He then spent two interesting years in industry, working for SunGard in the area of credit risk management and for Semmle in the areas of logic programming and software analytics. He is currently working as a Research Associate in the Nuffield Department of Clinical Neurosciences at the University of Oxford. His areas of interest include object detection and tracking, medical image analysis, computer games development and the intricacies of different programming languages, especially C++. He was a session chair for the 6th International Symposium on Image and Signal Processing and Analysis, ISPA 2009. He is a member of the Association of C and C++ Users (ACCU) and has written a variety of articles for their magazines.
Two tree-based methods for the waterfall
Golodetz SM. et al, (2014), Pattern Recognition, 47, 3276 - 3292
Automatic spine identification in abdominal CT slices using image partition forests
Golodetz S. et al, (2009), ISPA 2009 - Proceedings of the 6th International Symposium on Image and Signal Processing and Analysis, 121 - 126
Region analysis of abdominal CT scans using image partition forests
Golodetz S. et al, (2008), 5th International Conference on Soft Computing as Transdisciplinary Science and Technology, CSTST '08 - Proceedings, 432 - 437
On-the-fly adaptation of regression forests for online camera relocalisation
Cavallari T. et al, (2017), Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017, 2017-January, 218 - 227
Simpler editing of graph-based segmentation hierarchies using zipping algorithms
Golodetz S. et al, (2017), Pattern Recognition, 70, 44 - 59
Struck: Structured Output Tracking with Kernels.
Hare S. et al, (2016), IEEE Trans Pattern Anal Mach Intell, 38, 2096 - 2109
The Thermal Infrared Visual Object Tracking VOT-TIR2015 Challenge Results
Felsberg M. et al, (2016), Proceedings of the IEEE International Conference on Computer Vision, 2016-February, 639 - 651
Staple: Complementary learners for real-time tracking
Bertinetto L. et al, (2016), Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2016-January, 1401 - 1409