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About Us

The Visual Information Laboratory of the University of Bristol exists to undertake innovative, collaborative and interdisciplinary research resulting in world leading technology in the areas of computer vision, image and video communications, content analysis and distributed sensor systems. VI-Lab was formed in 2010, merging the two well established research groups, Signal Processing (EEEng) and Computer Vision (CS). The two constituent groups offer shared and complementary strengths and, with a history of successful collaboration since 1993, their merger has created one of the largest groupings of its type in the UK.

Rate-distortion Optimization Using Adaptive Lagrange Multipliers

Fan Zhang and David Bull ABSTRACT This page introduces the work of rate-distortion optimisation using adaptive Lagrange Multipliers. In current standardized hybrid video encoders, the Lagrange multiplier determination model is a key component in rate-distortion optimization….

FRQM: A Frame Rate Dependent Video Quality Metric

Fan Zhang, Alex Mackin and David Bull ABSTRACT This page introduces the work of an objective quality metric (FRQM), which characterises the relationship between variations in frame rate and perceptual video quality. The proposed method…

BVI-SR Video Database

This page will contain a download link to the BVI-SR (Spatial Resolution) video database if accepted into ICIP 2018  

VI-Lab PhD Research Opportunities

Funded Opportunities VI-Lab currently has fully funded PhD opportunities in the following areas: _________________________________________________________________________ Title: Development of super resolution and three-dimensional intra-coronary intra-vascular ultrasound imaging Supervisors: Professor Alin Achim and Dr Kalpa De Silva (Bristol…


The MultiDrone Consortium organized the first Drone Cinematography Workshop at the University of Bristol on 6 December 2017. The aim of the workshop was to bring together experts in drone cinematography – users, producers, and…

BVISS: Pattern Recognition without Features or Training

Professor Fred Stentiford – UCL Pattern recognition is usually implemented through the use of a selected set of plausible features that characterise the data being studied. In addition it is also necessary to identify a…

BVISS: Augmenting vision, the easy and the hard way

Dr Stephen Hicks – Oxford University – Research Fellow in Neuroscience and Visual Prosthetics, Nuffield Department of Clinical Neurosciences Mobile computing, augmented reality, deep learning. Consumer-grade devices are coming of age with a dazzling array…

BVI Seminar, Filipe Cristino, Bangor University

Seminar title, abstract and biography to be announced

BVI Seminar: Attentional selection of colour is determined by both cone-based and hue-based representations

Jasna Martinovic, University of Aberdeen What is the nature of representations that sustain attention to colour? In other words, is attention to colour predominantly determined by the low-level, cone-opponent chromatic mechanisms established at subcortical processing…

BVI Seminar: Eye Movements in Low and Normally Sighted Vision

Brian Sullivan, University of Bristol, School of Experimental Psychology  I will present two studies examining human eye movements and discuss my role at the University of Bristol. The first study concerns patients with central vision loss who…

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