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Research facilities

We have a diverse range of facilities and systems that underpin our cutting-edge research.

These include dedicated resources for:

Network ports and cables

Motion capture

Our motion capture lab includes a 3dMD Dynamic 3D face capture system, Phasespace infra-red motion capture technology and an Ascension MotionStar electro-magnetic sensor-based motion capture area.

The lab also has a variety of related equipment, including:

  • Pulhemus Fastrak: A desktop 16 sensor motion capture system
  • Cybergloves: Datagloves for capturing hand motion data
  • nVisor SX head-mounted display
  • Occulus Rift head-mounted display.

We use eye tracking equipment, including SensoMotoric Instruments RED250 Mobile eye tracking glasses, to better understand how human vision works.

3D data capture

The Visual Computing group has extensive experience in 3D mesh and geometry processing and uses:

  • Minolta Vivid 3D Laser Scanner
  • Fastscan Cobra Hand Held 3D scanner
  • Free FormConcept: A 3D Haptic device for 3D input and force feedback
  • Cube X Duo 3D Printer.

Knowledge representation and reasoning

We make use of the University’s Advance Research Computing facilities to process and store large data sets from sources that include ClueWeb12, WikiLinks, Web Data Commons, UMBC, English Gigaword, Google N-gram, and Wikipedia dumps.

Cloud computing

We have an 8-node computational cluster with InfiniBand interconnect used to support cloud computing. This includes installation of MPI, CometCloud and Kubernetes (a container-based framework), used in collaboration with our international partners, Rutgers University (USA), the University of Zaragoza (Spain) and IFSSTAR (Paris).

Computational modelling

We have two NVIDIA GPU Kelper nodes used to support molecular dynamics and computational science work with the School of Engineering and the School of Mathematics.

Internet of Things research

Co-funded by CircleIT, our Internet of Things laboratory includes devices from Zolertia, Libellium (to support ad-hoc device networking), Raspberry Pi 3 and Arduino boards, to expand work in IoT-Cloud integration and our ongoing focus on Edge computing.

Computational music

Our computational music researchers have active interests in symbolic modelling, music analysis and audio processing, and use a number of instruments, including keyboards, mixers, processing facilities and control surfaces.

Our audio editing software includes Cubase, Native Instruments Komplete, and Kontakt, Assorted Software Synthesisers and Samples.

We are experimenting with an 'Auditory Pixels' System - a bespoke 3D sound point source location projection system comprising a 20 speaker array and acoustically transparent screen for video projection.