Skip to main content

Characterizing Visual Acuity in the Use of Head Mounted Displays

  • Conference paper
  • First Online:
Advances in Computer Graphics (CGI 2021)

Abstract

In the real world, the sense of sight is dominant for humans, and having a normal vision is essential to perform well in many common tasks. There, ophthalmology has several tools to assess and correct a person’s vision. In VR, when wearing an HMD, even a user with normal vision is challenged by additional hurdles that affect the virtual environment’s perceptual acuity, negatively impacting their performance in the application task. Display resolution, but also soiled lenses and bad vergence adjustment are examples of possible issues. To better understand and tackle this problem, we provide a study on assessing visual acuity in a VR setup. We conducted an experimental evaluation with users and found out, among other results, that visual acuity in VR is significantly and considerably lower than in real environments. Besides, we found several correlations of the measured acuity and task performance with difficulty adjusting the HMD and use of prescription glasses.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

Notes

  1. 1.

    Reference removed for blind review.

  2. 2.

    1 Paris foot is equivalent to 324.8393 mm. 1 Paris foot = 1.06575 feet.

References

  1. Barten, P.G.: Contrast Sensitivity of the Human Eye and Its Effects on Image Quality. SPIE Press (1999)

    Google Scholar 

  2. Benkhaled, I., Marc, I., Lafon-Pham, D., Jeanjean, L.: Evaluation of colorimetric characteristics of head-mounted displays. In: Stephanidis, C. (ed.) HCI 2016. CCIS, vol. 617, pp. 175–180. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-40548-3_29

    Chapter  Google Scholar 

  3. Bian, Y., Leng, T., Ma, Y.: A proposed discomfort glare evaluation method based on the concept of ‘adaptive zone’. Build. Environ. 143, 306–317 (2018)

    Article  Google Scholar 

  4. Bodis-Wollner, I.: Visual acuity and contrast sensitivity in patients with cerebral lesions. Science 178(4062), 769–771 (1972)

    Article  Google Scholar 

  5. El Jamiy, F., Marsh, R.: Survey on depth perception in head mounted displays: distance estimation in virtual reality, augmented reality, and mixed reality. IET Image Proc. 13(5), 707–712 (2019)

    Article  Google Scholar 

  6. Erickson, A., Kim, K., Bruder, G., Welch, G.F.: Effects of dark mode graphics on visual acuity and fatigue with virtual reality head-mounted displays. In: 2020 IEEE Conference on Virtual Reality and 3D User Interfaces (VR), pp. 434–442. IEEE (2020)

    Google Scholar 

  7. Fidopiastis, C., Fuhrman, C., Meyer, C., Rolland, J.: Methodology for the iterative evaluation of prototype head-mounted displays in virtual environments: visual acuity metrics. Presence 14(5), 550–562 (2005)

    Article  Google Scholar 

  8. Ginsburg, A.P.: A new contrast sensitivity vision test chart. Optom. Vis. Sci. 61(6), 403–407 (1984)

    Article  Google Scholar 

  9. Goradia, I., Doshi, J., Kurup, L.: A review paper on Oculus Rift & project Morpheus. Int. J. Curr. Eng. Technol. 4(5), 3196–3200 (2014)

    Google Scholar 

  10. Goudé, I., Cozot, R., Le Meur, O.: A perceptually coherent TMO for visualization of 360\(^\circ \) HDR images on HMD. In: Gavrilova, M.L., Tan, C.J.K., Chang, J., Thalmann, N.M. (eds.) Transactions on Computational Science XXXVII. LNCS, vol. 12230, pp. 109–128. Springer, Heidelberg (2020). https://doi.org/10.1007/978-3-662-61983-4_7

    Chapter  Google Scholar 

  11. Guo, J., Weng, D., Duh, H.B.L., Liu, Y., Wang, Y.: Effects of using HMDs on visual fatigue in virtual environments. In: 2017 IEEE Virtual Reality (VR), pp. 249–250. IEEE (2017)

    Google Scholar 

  12. Hart, S.G., Staveland, L.E.: Development of NASA-TLX (task load index): results of empirical and theoretical research. In: Advances in Psychology, vol. 52, pp. 139–183. Elsevier (1988)

    Google Scholar 

  13. Hoskins, D.H., Jr.: Cataract surgery: maintaining the excellence. J. Cataract Refract. Surg. 22(6), 643–644 (1996)

    Article  Google Scholar 

  14. Kaur, K., Gurnani, B., Kannusamy, V., et al.: Myopia: current concepts and review of literature. TNOA J. Ophthalmic Sci. Res. 58(4), 280 (2020)

    Article  Google Scholar 

  15. Kemeny, A., Chardonnet, J.-R., Colombet, F.: Getting Rid of Cybersickness. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-59342-1

    Book  Google Scholar 

  16. Koenderink, J.J., Van Doorn, A.J.: Illuminance texture due to surface mesostructure. JOSA A 13(3), 452–463 (1996)

    Article  Google Scholar 

  17. Kooi, F.L., Bijl, P., Padmos, P.: Stereo acuity and visual acuity in head mounted displays. In: Proceedings of the Human Factors and Ergonomics Society Annual Meeting, vol. 50, pp. 2693–2696. SAGE Publications Sage CA: Los Angeles (2006)

    Google Scholar 

  18. Lacava, A.C., Centurion, V.: Teste de sensibilidade ao contraste e teste de ofuscamento no paciente portador de catarata. Arq. Bras. Oftalmol. 62(1), 38–43 (1999)

    Article  Google Scholar 

  19. Lasa, M.S.M., Datiles, M.B., III., Podgor, M.J., Magno, B.V.: Contrast and glare sensitivity: association with the type and severity of the cataract. Ophthalmology 99(7), 1045–1049 (1992)

    Article  Google Scholar 

  20. Matsuura, Y., Terada, T., Aoki, T., Sonoda, S., Isoyama, N., Tsukamoto, M.: Readability and legibility of fonts considering shakiness of head mounted displays. In: Proceedings of the 23rd International Symposium on Wearable Computers, pp. 150–159 (2019)

    Google Scholar 

  21. Messina, E., Evans, J.: Standards for visual acuity. National Institute for Standards and Technology (2006)

    Google Scholar 

  22. Ong, S.C., et al.: A novel automated visual acuity test using a portable head-mounted display. Optom. Vis. Sci. 97(8), 591–597 (2020)

    Article  Google Scholar 

  23. Panfili, L.: Effects of VR-displays on visual acuity

    Google Scholar 

  24. Parra, J.C.O., Pujol, J., Garcia, R.B., Sánchez-Magan, A., Muñoz, J.M.: New system based on HMD to objectively and automatically assess visual function and to perform visual therapy. Invest. Ophthalmol. Vis. Sci. 55(13), 755 (2014)

    Google Scholar 

  25. Pelli, D.G., Rubin, G.S., Legge, G.E.: Predicting the contrast sensitivity of low vision observers (A). J. Opt. Soc. Am. A 3, P56 (1986)

    Google Scholar 

  26. Pelli, D., Robson, J., et al.: The design of a new letter chart for measuring contrast sensitivity. In: Clinical Vision Sciences. Citeseer (1988)

    Google Scholar 

  27. Quevedo Junyent, L.J., Aznar-Casanova, J.A., da Silva, J.A.: Dynamic visual acuity. Trends Psychol. 26(3), 1283–1297 (2018)

    Google Scholar 

  28. Regan, D.: Low-contrast letter charts and sinewave grating tests in ophthalmological and neurological disorders. Clin. Vision Sci. 2(3), 235-+ (1988)

    Google Scholar 

  29. Snellen, H.: Letterproeven, tot bepaling der gezigtsscherpte, vol. 1. J. Greven (1862)

    Google Scholar 

  30. Sproule, D., Jacinto, R.F., Rundell, S., Williams, J., Perlmutter, S., Arndt, S.: Characterization of visual acuity and contrast sensitivity using head-mounted displays in a virtual environment: a pilot study. In: Proceedings of the Human Factors and Ergonomics Society Annual Meeting, vol. 63, pp. 547–551. SAGE Publications Sage CA: Los Angeles (2019)

    Google Scholar 

  31. Stevens, R., Rhodes, D., Hasnain, A., Laffont, P.Y.: Varifocal technologies providing prescription and VAC mitigation in HMDS using Alvarez lenses. In: Digital Optics for Immersive Displays, vol. 10676, p. 106760J. International Society for Optics and Photonics (2018)

    Google Scholar 

  32. Sukumar, V., Hess, H.L., Noren, K.V., Donohoe, G., Ay, S.: Study on threshold patterns with varying illumination using 1.3 m imaging system. Intell. Inf. Manag. 2(1), 21–25 (2010)

    Google Scholar 

  33. Thibodeaux, J.R.: Shotgun sighting device. US Patent 6,598,331, 29 July 2003

    Google Scholar 

  34. Vieri, C., et al.: An 18 megapixel 4.3ï443 ppi 120 Hz OLED display for wide field of view high acuity head mounted displays. J. Soc. Inf. Display 26(5), 314–324 (2018)

    Google Scholar 

  35. Williamson, T., Strong, N., Sparrow, J., Aggarwal, R., Harrad, R.: Contrast sensitivity and glare in cataract using the Pelli-Robson chart. Br. J. Ophthalmol. 76(12), 719–722 (1992)

    Article  Google Scholar 

Download references

Acknowledgements

This work was funded by the Brazilian funding agencies Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) - Finance Code 001, Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) project 311251/2020-0, and FAPERGS PqG 17/2551-0001192-9.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Anderson Maciel .

Editor information

Editors and Affiliations

Appendices

Appendix 1 – Background on Visual Acuity in Ophthalmology

Visual acuity refers to the clarity of vision and the ability to distinguish details in objects. Anatomically, it is the ability of the eye to focus the image on the retina  [30]. It is also the capability of the eye to distinguish small details appearing on the visual field at a specified distance [23]. Acuity can also be split into two types: static, when the object is perceived stationary; dynamic, when the observer, the object or both are in motion [27].

Standard objects used to assess acuity are often called optotypes. The most common set of optotypes used to measure static VA are the Snellen chart and the Landolt C, also known as a Landolt ring. Both were created more than 100 years ago. There are also other more recent optotypes in use today [8, 26]. We present them and their different uses for visual acuity assessment in the next subsections.

1.1 Snellen-Type Optotype

Herman Snellen, in 1862 [29] created a Table 1 composed by letters of different sizes (optotypes - Table 1) representing a visual angle of 5 min of arc (5’) at a distance of 5 m. The letters are composed by elements of \(\frac{1}{5}\) of this measure.

Table 1. Snellen-type optotype dimensions.

In his study [29], Snellen specifies the dimensions of the characters and the spaces that separate them. The visual acuity (V) is the maximum distance at which the optotype is recognized (d) divided by the distance at which it should be to form an angle of 5 arc-minutes (D) [29] as in Eq. 1:

$$\begin{aligned} V=\frac{d}{D} \end{aligned}$$
(1)

If d and D are equal and the optotype is visible at 20 Paris feetFootnote 2, then \(V=\frac{20}{20}=1\) is defined as a normal visual acuity.

Fig. 3.
figure 3

Calculation of the Static Visual Acuity (SVA) in a Snellen-type optotype. It is assumed that the observer looks at the letter from a distance of 5 m (\(d = 5\) m). Therefore, the height of the letter will be 7.25 mm and the thickness of the horizontal feature will be \(s = 1.45\) mm [27].

In the Snellen proposal, the minimum resolution angle is 1 arc-minute, as seen in Fig. 3. To determine the size of an optotype in the Snellen chart, the formula of Eq. 2 is used:

$$\begin{aligned} H=14.6\frac{D}{V} \end{aligned}$$
(2)

where H is the height of the optotype (in mm), D is the presentation distance (in meters), V is the visual acuity (in tenths) and the constant 14.6 represents the tangent of 5 multiplied by 10,000 to compensate for the use of millimeters and tenths in the other components.

In a Snellen chart, some letters are more easily readable than others and each row has a different number of letters. This causes the phenomena of non-proportional grouping and spacing between letters and rows, making reliability and reproducibility of using a Snellen chart low. Nevertheless, it is widely used and universally accepted.

1.2 Pelli-Robson Contrast Sensitivity

Besides the high-contrast VA measurement (black optotypes on a white background) provided by Snellen charts, other contrast levels can also be used to obtain a second measure of acuity. The principle is to use gray optotypes on the same white background, showing successively lighter and lighter grays.

Contrast is defined as the relative difference of luminance between a target and the background. The whole human visual system (HVS) is involved in object detection, meaning that while the eyes capture and convert light into electric signals, the brain processes and makes the decisions about the visual perception of objects [1, 32]. Contrast is used to determine what is detectable by the HVS. The objects are visible if they have a contrast greater than the contrast sensitivity (CS) [16, 32], which is defined as the minimum contrast necessary to detect a grid in some specified spatial frequency

CS was first measured in 1889 [28], but its value was recognized only after Bodis-Wolner work in 1972 [4].

Pelli et al. [25, 26] first proposed a chart with variable contrast letters sized at half a degree that can measure the CS of an individual with spatial frequencies between 3 and 5 c/deg. That is the best interval to determine whether an individual has a loss of sensitivity in the spatial frequency. Later, they came up with a new chart with single sized letters that change in contrast at each row to obtain information about the contrast sensitivity of any individual. Hence, they created a model that allows to choose the best parameters to accurately maximize the measurements provided by the test [25, 26].

Fig. 4.
figure 4

Miniature Pelli-Robson Letter-Sensitivity Chart

The most widely used chart presents a set of Sloan font letters with size of \(0.5^{\circ }\) at a distance of 3 m, although it can be used at shorter distances to assess individuals with subnormal vision. The chart is read from left to right, from top to bottom. Each row contains two groups of three letters. The letters within each group have the same contrast, while each successive group has lower contrast than the previous one. As seen in Fig. 4, there is a total of 48 optotypes on a white background, divided in 16 groups. The first group is black (contrast is \(100\%\)), and each subsequent group has a contrast reduction factor of 0.707 (0.15 log units). Thus, the contrast of the last group is \(0.56\%\) (2.25 log units below 100% [35].

The Pelli-Robson chart is considered a suitable technique to asses the visual function [19].

1.3 Glare and Disability Glare

Glare is a light phenomenon that causes difficulty, and may even disable, viewing of an object due to very bright light of artificial or natural origin. The light scatters in opacified regions of the eye capsule, causing ofuscating bright regions to appear in the field of view. Cataract is the most associated condition with glare testing. While most vision quality analyses are performed in a fixed viewing position and direction, glare depends on the viewing position and direction within a space [3], in such a way that specific central and peripheral glare tests are used. Lacava [18] concluded that the glare test associated with the contrast sensitivity test shows that the visual acuity provided by the Snellen Table does not correspond to everyday vision. Although the measurement of visual acuity using contrast sensitivity is not unanimous, it is considered more informative than the measurement of visual acuity using onkly the Snellen chart [35].

Hoskins [13] states that glare testing and contrast sensitivity play a role in quantifying or describing visual impairment in some patients.

1.4 Luminance, Contrast, Resolution and Field of View

In modern optics, the ability of the eye to resolve a line pair is one of many ways to determines the human eye-plus-brain acuity. This acuity is measured in the fovea zone as \(1/a=1.7\), where a is the number of arc minutes of field of view necessary to discriminate the two lines. This is roughly \(0.59'\) (arc minutes), or \(171.62\,{\upmu }\)rad microradian. As two pixels are necessary to see the two lines, it is said that the resolution of the human eye in good light conditions is about \(1'\) arc minute (\(290.89\,{\upmu }\)rad microradians. Outside the fovea zone, the resolution of the eye decreases considerably [29], so a moderate variation in contrast or illumination will reflect very little on the person’s visual acuity. Visual perception is rather influenced by the difference in intensity between the object and the background (contrast), the spatial frequency (inverse of the line thickness in regular optotypes) and the area of the object. As for the field of view, there is no consensus and it varies among people, but it is accepted that it is somewhere above \(180^\circ \) horizontally, limited at \(220^\circ \). The binocuar vision is, in turn, limited to the central \(120^\circ \) of the total field of view (FoV).

When referring to displays, the term resolution is often used to mean either display pixel pitch or pixel count, which may be confusing. When referring to HMDs, resolution more accurately refers to cycles (or lines) per unit angle that can be resolved [34], as seen above for the human vision. Typical VR optics have a focal length of about 40 mm [9], which amplifies the pixel size. So, HMDs use a larger amount of smaller pixels when compared to screens to try and increase both the perceived angular resolution and the FoV. An estimation is that to provide 60 pixels per degree (1 pixel per arc minute) or Snellen acuity of 20/20 for a FoV of \(150^\circ \), an HMD would require \(9600\times 9000\) pixels per eye [34].

Besides resolution, the luminance and contrast provided by a display are other items that could impact acuity. Luminance is the amount of visible light emitted per unit projected area of the display. It is relative to the amount of light emitted by the display system being expressed in candelas per squared meter (\(cd/m^2\)) [15]. Contrast, on the other hand, is the ratio between the highest and lowest luminance provided by the display.

Luminance is sometimes confused with brightness. In the real world, it can reach much higher values than in display systems, such as \(1.6\times 10^9\) cd/m\(^2\) for the sun at noon versus 50–300 cd/m\(^2\) at a maximum resolution on a computer monitor [15].

The technology used in today’s HMDs construction is based on two approaches [2]. The first, similar to the display of smartphones, televisions and computer monitors, is based on liquid crystals (LCD - Liquid-Crystal Displays), while the other is based on OLED (Organic Light-Emitting Diode). These technologies allow for different ranges in terms of luminance, color, contrast, refresh rate, etc., which combined with optical lenses and design decisions compose the final experience and acuity of these displays. In Table 2 we present a comparison of the technical specifications of some popular HMDs.

Table 2. A representative list of HMD display characteristics [2, 15]

Appendix 2 – Virtual Charts and Optotypes Used

Fig. 5.
figure 5

A row of optotypes as they are seen in the Peripheral and central glare test.

Fig. 6.
figure 6

Our virtual reproduction of the Snellen chart. An individual with normal visual acuity must be able to discriminate the characters until the line 8 (20/20 visual acuity).

Table 3. Acuity and corresponding sizes of each row of optotypes in our virtual snellen chart [29].
Table 4. Progressive sequence of letters used in the glare tests.
Table 5. Key to the Pelli-Robson contrast sensitivity chart [26] (left), and letters used with the left-eye and the right-eye (right) in the contrast sensitivity test.

Appendix 3 – Raw Data from Questionnaires

Fig. 7.
figure 7

Participants’ agreement with the following statements: (a) I found it was difficult to adjust the headset; (b) I felt comfortable as if I was actually at the virtual place where the tasks were performed.

Fig. 8.
figure 8

Results from the administration of the NASA Task-load Index questionnaire.

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

da Fontoura, V.S., Maciel, A. (2021). Characterizing Visual Acuity in the Use of Head Mounted Displays. In: Magnenat-Thalmann, N., et al. Advances in Computer Graphics. CGI 2021. Lecture Notes in Computer Science(), vol 13002. Springer, Cham. https://doi.org/10.1007/978-3-030-89029-2_44

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-89029-2_44

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-89028-5

  • Online ISBN: 978-3-030-89029-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics