The Computational Vision and Imaging Technology (CVIT) Research Group is an interdisciplinary research group providing a synthesis between the scientific disciplines associated with computational vision, image science, image engineering and visual science.
- A. Tsifouti, S. Triantaphillidou, M.-C. Larabi, G. Doré, E. Bilissi and A. Psarrou. A case study in identifying acceptable bitrates for human face recognition tasks, Elsevier, Signal Processing: Image Communication, 36(0), 14-28p, (2015).
- A. Tsifouti, S. Triantaphillidou, M.-C. Larabi, G. Doré, E. Bilissi and A. Psarrou. The effects of scene content parameters, compression, and frame rate on the performance of analytics systems, Proc. SPIE 9396, Image Quality and System Performance XII, 93960X (January 8, 2015).
- Fry E., Triantaphillidou S., Jarvis J. and Gupta G. (2015), Image quality optimization, via application of contextual contrast sensitivity and discrimination functions, Proc. IS&T/SPIE Electronic Imaging: Image Quality & System Performance XII, V.9396, 93960K. (Best Student Paper award).
Computational Vision and imaging Technology Research Group, 115 New Cavendish Street, London W1W 6UW