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},}
StereoDiffusion: Training-Free Stereo Image Generation Using Latent Diffusion Models
Lezhong Wang, Jeppe Revall Frisvad, Mark Bo Jensen, and 1 more author
In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, Jun 2024
@inproceedings{Wang_2024_CVPR,author={Wang, Lezhong and Frisvad, Jeppe Revall and Jensen, Mark Bo and Bigdeli, Siavash Arjomand},title={StereoDiffusion: Training-Free Stereo Image Generation Using Latent Diffusion Models},booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},month=jun,year={2024},pages={7416-7425},}
Digitizing translucent object appearance by validating computed optical properties
Duc Minh Tran, Mark Bo Jensen, Pablo Santafé-Gabarda, and 4 more authors
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},}
2023
Performance Comparison of Meshlet Generation Strategies
Mark Bo Jensen, Jeppe Revall Frisvad, and J. Andreas Bærentzen
Journal of Computer Graphics Techniques (JCGT), Dec 2023
@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},}
2022
Using virtual reality for anatomical landmark annotation in geometric morphometrics
Dolores Messer, Michael Atchapero, Mark B Jensen, and 8 more authors
@article{messer2022Landmark,title={Using virtual reality for anatomical landmark annotation in geometric morphometrics},author={Messer, Dolores and Atchapero, Michael and Jensen, Mark B and Svendsen, Michelle S and Galatius, Anders and Olsen, Morten T and Frisvad, Jeppe R and Dahl, Vedrana A and Conradsen, Knut and Dahl, Anders B and others},journal={PeerJ},volume={10},pages={e12869},year={2022},publisher={PeerJ Inc.},}
PhD Thesis
Virtual Reality-Based Visualization of Large Geometric Data
@phdthesis{jensen2022vrvis,author={Jensen, Mark Bo},title={Virtual Reality-Based Visualization of Large Geometric Data},school={Technical University of Denmark},year={2022},}
2021
Tools for Virtual Reality Visualization of Highly Detailed Meshes
Mark B. Jensen, Egill I. Jacobsen, Jeppe Revall Frisvad, and 1 more author
In VisGap - The Gap between Visualization Research and Visualization Software, Dec 2021
@inproceedings{jensen2021Tools,booktitle={VisGap - The Gap between Visualization Research and Visualization Software},editor={Gillmann, Christina and Krone, Michael and Reina, Guido and Wischgoll, Thomas},title={{Tools for Virtual Reality Visualization of Highly Detailed Meshes}},author={Jensen, Mark B. and Jacobsen, Egill I. and Frisvad, Jeppe Revall and Bærentzen, J. Andreas},year={2021},publisher={The Eurographics Association},isbn={978-3-03868-149-6},doi={10.2312/visgap.20211088},}
