Dr Lee Streeter

Lee Streeter

Senior Lecturer

Qualifications: PhD Waikato, MSc Physics Waikato

Papers Taught

Research Supervised



Lickfold, Carl.

Anastasia Mozhaeva

Mukhtar, Amir (submitted)

Anthonys, Gehan (to graduate)

Dissanayake, Nilakshi


Jacob Waas

Josefina Pehrson

Recently Completed


Seabright, Matthew


Corlett, Dale

Alqassab, Ali

Research Interests

Imaging, measurement, signal processing, mathematical modelling, and numerical methods.

Dr Streeter's research interests focus on and about time-of-flight range imaging. His current project is on solving the 'problem of motion', to correct motion blur and transform it into simultaneous distance and motion measurement. He is interested in time-of-flight in general, and has worked on all majors form of error in time-of-flight range imaging.


2021 Lee is the general chair for Image and Vision Computing New  Zealand. The website and call for papers may be found here.

2019 Lee was awarded the Royal Society of New Zealand Cooper Award.

2019 Lee won the Kudos Datamars Engineering Science Excellence Award.

Lee received congratulations in the NZ parliament:

2017 he was awarded the MBIE Smart Ideas to research the implementation of motion measurement and correction in time-of-flight for industrial applications. His work was highlighted at the 2018 Fieldays

2015 Lee was awarded the Marsden Fast Start to research the problem of motion in time-of-flight range imaging.

Find out more about Lee's Marsden grant awarded for his time-of-flight photography research:

Potential projects

I am actively looking for potential PhD students. If you have a good GPA, and possibly have one or more first author conference publications, I may be interested in hearing from you.

I am interested in all areas of computer vision, but especially with a focus on measurement and computational imaging (inverse problems in imaging). Some potential projects follow.

  • Ghost Imaging/Ghost Range Imaging.

I am interested in exploring the fascinating topic of ghost imaging, especially with focus on range imaging by ghost imaging. Ghost imaging allows one to measure an image from light that has never interacted with the scene. Instead the correlation between light that has interacted with the scene, captured using a single pixel detector, and light captured by the image sensor direct from the light source, revels the image "ghost".

  • Machine Learning for Time-of-Flight Range Imaging.

Machine learning is a hot topic today. Training computers to make decisions based on data is seeing wide uptake across many fields and industries. This open ended research problem is to apply current trends in machine learning to optimise time-of-flight range measurement.

  • The Systems Engineering of Error Correction in Time-of-Flight Range Imaging.

The UoW range imaging group leads the way internationally on understanding and improving time-of-flight range imaging. We have developed solutions to all the major error sources. However, an outstanding question is how to bring the existing solutions all together. Many appear incompatible with each other, and a significant research question is how to bring them together, solving multiple error sources at the same time.

  • Noise and Precision Optimisation in Time-of-Flight Range Imaging.

Time-of-Flight cameras, like any electronic device, have random error. This random error means that an object at, say, 2 metres from the camera might be measured slightly closer or further from the camera, and that error is unpredictable causing uncertainty. Mitigation of this error is key to producing the best possible range measurements. The research question is to draw from statistics and other sources of knowledge to best understand how random effects cause uncertainty and how to reduce their impact.

  • Motion Measurement/Velocimetry.
  • Applications of Depth Imaging.

Depth cameras provide rich information of objects within their field of view. The sky is the limit for new applications of depth imaging. Engineering solutions to problems might include behaviour analysis, human computer interface, security applications, health applications (ToF cameras operate in the infrared which can see into and beneath skin), tomographic imaging, etc.

Recent Publications

  • Mozhaeva, A. I., Vlasuyk, I. V., Potashnikov, A. M., Cree, M. J., & Streeter, L. (2021). The Method and Devices for Research the Parameters of the Human Visual System to Video Quality Assessment. In 2021 Systems of Signals Generating and Processing in the Field of on Board Communications, Conference Proceedings. doi:10.1109/IEEECONF51389.2021.9416081

  • Mozhaeva, A., Streeter, L., Vlasuyk, I., & Potashnikov, A. (2021). Full reference video quality assessment metric on base human visual system consistent with PSNR. In 2021 28th Conference of Open Innovations Association (FRUCT). Moscow, Russia - Presented Online: IEEE. doi:10.23919/FRUCT50888.2021.9347604

  • Mozhaeva, A., Potashnikov, A., Vlasuyk, I., & Streeter, L. (2021). Constant Subjective Quality Database: The Research and Device of Generating Video Sequences of Constant Quality. In 2021 International Conference on Engineering Management of Communication and Technology Proceedings. doi:10.1109/EMCTECH53459.2021.9618977

  • Wilson, M. T., Seshadri, S., Streeter, L. V., & Scott, J. B. (2020). Teaching physics concepts without much mathematics: ensuring physics is available to students of all backgrounds. Australasian Journal of Engineering Education, 25(1), 39-54. doi:10.1080/22054952.2020.1776027 Open Access version:

Find more research publications by Lee Streeter


Electronics; Engineering; Imaging

Measurement; Range Imaging, Motion Analysis; Signal Processing.

Contact Details

Email: lee dot streeter at
Room: CD.1.03
Phone: +64 7 838 4106