Staff Directory

Marius miknis profile

Contact Details


Fellow of the Higher Education Academy (FHEA)
PhD in Efficient 3D Imaging for Embedded Systems
BSc (Hons) Professional Computer Games Development


Technocamps lecturer (2012 – 2014):

  • Develop and deliver computing based material to promote computer science across schools in Wales


Lecturer – Computer game development


• Miknis, M., Davies, R., Plassmann P., Ware, A. 2016. CSC Journals, “Efficient point cloud pre-processing using the Point Cloud Library”
• Miknis, M., Davies, R., Plassmann P., Ware, A. 2015. IEEE, “Near real-time point cloud processing using the PCL”
• Miknis, M., Plassmann P., Jones, C. 2014. IEEE, “Virtual environment stereo image capture using the Unreal Development Kit”


Computer Science Tutor/Demonstrator, University of South Wales (2013 – 16)
• Demonstrated and tutored to computer science undergraduates in C++ Programming, Real-time Rendering (DX11) Games Programming, Data Structures & Algorithms and Even Driven programming modules.

Workshop Development & Delivery Officer – SAW (2014 – 15)
• Supported technical growth in Wales by developing and delivering computing based workshops to businesses across Wales.

Lecturer / Workshop Developer – Technocamps (2012 – 14)
• Develop and deliver computing based material to promote computer science across schools in Wales. This included running interactive workshops in schools, colleges and universities on computing based subjects such as robotics, programming and networking.

Guest workshops for Software Alliance Wales:
• Introduction to Computer Vision using OpenCV 2.4.9
USW (22nd – 23rd July 2014)
– Pembroke (22nd – 23rd September 2014)

Guest lecture at Le Creusot University (France):
• Introduction to OpenCV using 2.4.6 (23rd – 24th June 2014)

Guest lecture at Brno University(Czech Republic):
• Introduction to OpenCV using 2.4.5 (24th – 25th May 2013)


The current project seeks to produce a near real-time, 360 degrees, 3D data acquisition system based on stereo-photogrammetry. At the moment such 3D data acquisition is computationally expensive, slow and produces large amounts of sparse data. In order to overcome these problems this project seeks to research and implement stereo-matching algorithms that utilise the power of graphical processors in embedded hardware. This includes research and implementation of segmentation and stitching algorithms to allow for full 360 degree 3D data acquisition.

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