Dr Rhian DaviesPhD student
I completed my undergraduate degree of BSc Mathematics at the University of Lancaster in July 2011. In the summer between graduating and starting STOR-i, I completed a research internship with the advanced modelling and data measurement platform at Unilever Port Sunlight.
I joined the STOR-i program in 2011, completed the Masters of Research degree in September 2012 and am currently a first year PhD student. My research project considers a probabilistic approach to video analysis with a particular focus on the automatic detection of anomalous behaviour. I am supervised jointly by Lyudmila Mihaylova, Nicos Pavlidis and Idris Eckley.
My research interests are:-signal and image processing-pattern recognition-compressed sensing
Compressive Sensing is a new exciting topic arising in the area of signal processing. It's a method for reducing the amount of data required from a signal to be able to later reconstruct the signal accurately. One can imagine many scenarios where this technique could be useful in real life applications. One application of interest to me is visual surveillance, and in particular applying compressive sensing to background subtraction. This is a method frequently used in video analysis to separate foreground and background in CCTV footage.
Efficient analysis of data streams
Davies, R. 2017 Lancaster University. 132 p.
The effect of recovery algorithms on compressive sensing background subtraction
Davies, R., Mihaylova, L., Pavlidis, N., Eckley, I. 10/2013 In: Sensor Data Fusion. IEEE p. 1-6. 6 p.
- Modelling and Inference
- Statistical Learning
- STOR-i Centre for Doctoral Training