The Sullivan Doctoral Thesis Prize
The British Machine Vision Association has established a prize fund to commemorate the contribution made by the late Professor Geoff Sullivan to the advancement of the field of Computer Vision in the United Kingdom. The prize is considered for award, on an annual basis, to the best doctoral thesis submitted to a UK University, in the field of computer or natural vision.
Recommendations for the prize are considered by a Selection Panel appointed annually by the BMVA Executive Committee.
The decision of the Selection Panel is announced at the annual British Machine Vision Conference, at which the presentation will be made.
2019 Prize Nominations
The BMVA Executive Committee seeks nominations for the Sullivan Prize for theses examined during the calendar year 2018. Internal examiners and supervisors may act as nominators, but the committee would like to receive an accompanying report and endorsement of the nomination from the external examiner of the thesis. The closing date for theses to be considered for the award of the 2019 prize is 31st May 2019.
- Karel Lebeda, University of Surrey. 2D and 3D Tracking and Modelling
- Xiatian Zhu, Queen Mary, University of London. Semantic Structure Discovery in Surveillance Videos
- Vibhav Vineet, Oxford Brookes University. Recognition, Reorganisation, Reconstruction and Reinteraction for Scene Understanding
- Mattias Heinrich, University of Oxford. Deformable lung registration for pulmonary image analysis of MRI and CT scans
- Patrick Ott, University of Leeds (joint winner). Segmentation Features, Visibility Modeling and Shared Parts for Object Detection
- Shoaib Ehsan, University of Essex (joint winner). Improving the Effectiveness of Local Feature Detection
- Marco Paladini, Queen Mary, University of London. Deformable and Articulated 3D Reconstruction from monocular video sequences
- Charles Bibby, Oxford University. Probabilistic Methods for Enhanced Marine Situational Awareness
- Olly Oechsle, University of Essex. Towards the Automatic Construction of Machine Vision Systems using Genetic Programming
- Pawan Kumar Mudigonda, Oxford Brookes University. Combinatorial and Convex Optimization for Probabilistic Models in Computer Vision
- Pushmeet Kohli, Oxford Brookes University. Minimizing Dynamic and Higher Order Energy Functions using Graph Cuts
- Josef Sivic, University of Oxford. Efficient visual search of images and videos
- Rob Fergus, University of Oxford. Visual Object Category Recognition
- Björn Stenger, University of Cambridge. Model-based hand tracking using a hierarchical Bayesian filter
- Jonathon Starck, University of Surrey. Human Modelling from Multiple Views
- Rhodri Davies, University of Manchester. Learning Shape: Optimal Models for Analysing Shape Variability
- Albert Chung, University of Oxford. Vessel and aneurysm reconstruction using speed and flow coherence information in phase contrast magnetic resonance angiograms.
- Gareth J Edwards, University of Manchester. Learning to identify faces in images and sequences.
- Richard Bowden, Brunel University. Learning non-linear Models of Shape and Motion
- Neil Johnson, University of Leeds. Learning Object Behaviour Models
The prize of £750 is considered for presentation annually for the best doctoral thesis.
Submissions must be in the broad areas of computer vision, including computational studies of natural vision.
The submission period is by calendar year.
Valid submission dates are based on the date of the successful viva voce exam, as evidenced by the signed examiners' reports.
Submissions must be in electronic form. The thesis must first be submitted into the thesis archive. Other submission materials should be emailed to .
Accompanying the thesis should be a supporting statement from the research supervisor and a recommendation from the external examiner, including the examiner's report. These should be in PDF form.
Each submission will be assessed by independent reviewers who will be appointed by the selection panel.