Mark Bo Jensen

I am an Assistant professor at the Technical University of Denmark. My research focuses on the emerging field of Perception Engineering, utilizing Extended Reality Technologies to model, understand, and explore human perception and cognition. An inter-disciplinary field requiring the collaboration between many fields from engineering to cognitive sciences. I bring to this field an expertiece in real-time computer graphics gained from more than 10 years of experience, and a passion for creating more immersive and convincing extended reality experiences.

I am also a co-founder of AL-EYE, where we develop software that turns mixed reality headsets with eye tracking into disability aids for people with low vision, hearing loss, or motor disability with the goal of creating a ‘universal disability aids’ that provide multisensory support individualised for each user. My passion and research interests are exploring computer graphics in the context of extended reality to create more immersive and convincing extended reality experiences.

I previously worked as a team lead at Dalux where I oversaw the development of their inhouse Vulkan-based mobile render engine, and I was an external lecturere at the Technical University of Denmark, teaching a course about creating XR-based experiences.

I obtained a Ph.D. in Computer Graphics by doing research that pushes graphics hardware to create high performance Virtual Reality-based visualization of scientific data. Through out my research I have developed a bespoke Vulkan-based 3D engines for VR-based visualization, I am developing a course on XR experiences, and have supervised various Graphics related projects. I have a background as a Technical Artist and Pipeline Engineer in the games and VFX industry before obtaining a MSc in Engineering.

selected publications

Virtual Reality: The Future Of Visual Field Testing

Kacper Błażej Gąsior*, Mark Bo Jensen*, Jonas Ulveman Maare, and 2 more authors

In ACM Symposium on Applied Perception 2024, 2024

Abs Bib PDF

One of the most important tests available to assess human vision is the visual field test, or perimetry. While imaging of the fundus and standard tests such as Snellen charts can assess factors such as acuity, and identify damaged parts of the retina, only the visual field test can measure the subjective field of view of perception from the patient side. We introduce a Virtual Reality (VR)-based perimetry test. A systematic test for measuring the visual field function conducted in VR. The VR-based test is precise enough to supersede the standard perimetry test carried out on either a Goldmann or Octopus test machine. Using VR allows for a more comfortable experience and opens up for further development that can potentially be used to map out other deficiencies of the visual field function. It also provides the ability to gamify the test allowing it to be carried out on children. Here we present some of the considerations and implementation details which ensure that our software has the necessary capabilities of producing correct measurements and valid results.
@inproceedings{gasior2024VisualField, author = {G\k{a}sior*, Kacper B\l{}a\.{z}ej and Jensen*, Mark Bo and Maare, Jonas Ulveman and Doherty, Kevin and Mulvey, Fiona Br\'{\i}d}, title = {Virtual Reality: The Future Of Visual Field Testing}, year = {2024}, isbn = {9798400710612}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, url = {https://doi.org/10.1145/3675231.3678877}, doi = {10.1145/3675231.3678877}, booktitle = {ACM Symposium on Applied Perception 2024}, articleno = {23}, numpages = {2}, keywords = {mixed reality, perimetry test, virtual reality, vision loss, visual field}, location = {Dublin, Ireland}, series = {SAP '24}, }
Digitizing translucent object appearance by validating computed optical properties

Duc Minh Tran, Mark Bo Jensen, Pablo Santafé-Gabarda, and 4 more authors

Appl. Opt., Jun 2024

Abs Bib PDF

The optical properties available for an object are most often fragmented and insufficient for photorealistic rendering of the object. We propose a procedure for digitizing a translucent object with sufficient information for predictive rendering of its appearance. Based on object material descriptions, we compute optical properties and validate or adjust this object appearance model based on comparison of simulation with spectrophotometric measurements of the bidirectional scattering-surface reflectance distribution function (BSSRDF). To ease this type of comparison, we provide an efficient simulation tool that computes the BSSRDF for a particular light-view configuration. Even with just a few configurations, the localized lighting in BSSRDF measurements is useful for assessing the appropriateness of computed or otherwise acquired optical properties. To validate an object appearance model in a more common lighting environment, we render the appearance of the obtained digital twin and assess the photorealism of our renderings through pixel-by-pixel comparison with photographs of the physical object.
@article{tran2024Translucent, author = {Tran, Duc Minh and Jensen, Mark Bo and Santaf\'{e}-Gabarda, Pablo and K\"{a}llberg, Stefan and Ferrero, Alejandro and Hannemose, Morten Rieger and Frisvad, Jeppe Revall}, journal = {Appl. Opt.}, keywords = {Absorption coefficient; Bidirectional reflectance distribution function; Camera calibration; Optical properties; Spectral properties; Turbid media}, number = {16}, pages = {4317--4331}, publisher = {Optica Publishing Group}, title = {Digitizing translucent object appearance by validating computed optical properties}, volume = {63}, month = jun, year = {2024}, url = {https://opg.optica.org/ao/abstract.cfm?URI=ao-63-16-4317}, doi = {10.1364/AO.521974}, }

Performance Comparison of Meshlet Generation Strategies

Mark Bo Jensen, Jeppe Revall Frisvad, and J. Andreas Bærentzen

Journal of Computer Graphics Techniques (JCGT), Dec 2023

Bib PDF Code

@article{jensen2023Meshlet,
  author = {Jensen, Mark Bo and Frisvad, Jeppe Revall and B{\ae}rentzen, J. Andreas},
  title = {Performance Comparison of Meshlet Generation Strategies},
  year = {2023},
  month = dec,
  day = {8},
  journal = {Journal of Computer Graphics Techniques (JCGT)},
  volume = {12},
  number = {2},
  pages = {1--27},
  url = {http://jcgt.org/published/0012/02/01/},
  issn = {2331-7418},
}