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arxiv: 2606.08441 · v1 · pith:XTZGVSCQnew · submitted 2026-06-07 · 💻 cs.HC

Comparing Controller-Free Pointing Techniques Across Depth for 2D Selection in Augmented Reality

Samiha Sultana , J. Felipe Gonzalez , Robert J. Teather This is my paper

Pith reviewed 2026-06-27 18:11 UTC · model grok-4.3

classification 💻 cs.HC
keywords augmented realitypointing techniquescontroller-free inputdepth variation2D target selectionISO 9241-411head pointingperformance evaluation
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The pith

Head-based pointing is the most accurate and consistent controller-free method for 2D AR selection across depths.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

This paper evaluates five controller-free pointing techniques for 2D target selection in augmented reality at distances of 2 m, 6 m, and 10 m. It applies the ISO 9241-411 protocol to measure movement time, accuracy, throughput, and workload via NASA TLX. Head- and eye-based methods outperformed hand-based ones (Finger, Wrist, Arm), with head input showing the highest accuracy and least variation as depth changed. Depth had significant effects on performance that interacted with target size and distance.

Core claim

Head- and eye-based pointing significantly outperformed the hand-based methods in movement time, accuracy, throughput, and workload. Head input was the most accurate and remained the most consistent across depth. Depth significantly impacted performance, with complex interactions with target size and distance.

What carries the argument

ISO 9241-411 evaluation of five controller-free techniques (Head, Eye, Finger, Wrist, Arm) across three fixed depths.

If this is right

  • Head input can be prioritized for AR tasks that span multiple depths.
  • Hand-based methods become less competitive as target distance increases.
  • Eye input offers strong performance but is less stable than head input across depths.
  • Workload ratings favor head and eye methods over finger, wrist, or arm gestures.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • AR interface designers may default to head tracking for distant or variable-depth targets.
  • Testing the same techniques while users walk or turn could reveal additional depth-related costs.
  • Hybrid inputs that switch between head and eye based on depth might reduce overall errors.

Load-bearing premise

The ISO 9241-411 protocol together with the five chosen techniques and three depths adequately represents performance differences in actual AR use.

What would settle it

Finding that any hand-based technique matches or exceeds head input in accuracy or throughput at 10 m depth under the same protocol would undermine the main result.

Figures

Figures reproduced from arXiv: 2606.08441 by J. Felipe Gonzalez, Robert J. Teather, Samiha Sultana.

Figure 1
Figure 1. Figure 1: The five controller-free pointing techniques for study: (a) Arm, (b) Wrist, (c) Finger, (d) Eye, and (e) Head. Each was [PITH_FULL_IMAGE:figures/full_fig_p001_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: The five pointing techniques, depicting ray origin [PITH_FULL_IMAGE:figures/full_fig_p003_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: (a) Study setup with different target depth conditions, (b) yellow cursor approaching target with 0.4m target width, [PITH_FULL_IMAGE:figures/full_fig_p004_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: Augmented Reality View of the task from participant’s perspective for Wrist. When the yellow cursor intersects the red target (seen in figure 3), the target turns green to provide visual feedback that it is ready for selection. three depths (2 m, 6 m, 10 m) with widths (0.2 m, 0.3 m, 0.4 m) and amplitudes (1.5 m, 2.5 m, 3.5 m), yielding nine 𝐼𝐷 levels (2.24– 4.21 bits). The software presented a 20 cm yello… view at source ↗
Figure 5
Figure 5. Figure 5: Movement Time vs Index of Difficulty (𝐹4,76 = 57.73, 𝑝 < .001, 𝜂 2 = 0.75) and depth (𝐹2,38 = 63.19, 𝑝 < .001, 𝜂 2 = 0.77) on movement time. Pairwise comparisons of the pointing techniques revealed that both Head (mean = 1.43 s, SD = 0.07 s) and Eye (mean = 1.55 s, SD = 0.10 s) were significantly faster than Arm (mean = 2.38 s, SD = 0.10 s), Wrist (mean = 2.43 s, SD = 0.15 s), and Finger (mean = 2.93 s, SD… view at source ↗
Figure 7
Figure 7. Figure 7: Error Rate per Technique and Depth. Error bars indicate standard error. Arm error rates were stable between 2 m and 6 m, while Eye and Finger degraded significantly at every depth interval. Head and Wrist remained stable between 6 m and 10 m, suggesting superior stability with greater depth. 5.3 Throughput There were significant main effects for Pointing Technique (𝐹1.83,34.81 = 56.45, 𝜂 2 = 0.75) and Dept… view at source ↗
Figure 6
Figure 6. Figure 6: Mean Movement Time per depth per technique. Error bars indicate standard error. It is also worth noting that amplitude and width influenced the finger and wrist pointing techniques, yielding significant Pointing Technique × Amplitude (𝐹3.96,75.29 = 3.68, 𝑝 < .01, 𝜂 2 = 0.16) and Pointing Technique × Width (𝐹8,152 = 11.39, 𝑝 < .001, 𝜂 2 = 0.38) interaction effects. Specifically, at an amplitude of 1.5 m, th… view at source ↗
Figure 8
Figure 8. Figure 8: Throughput per technique per depth. Error bars indicate standard error. For the effect of Depth, pairwise comparisons revealed that pointing from 2 m (mean = 2.00 bits/s, SD = 0.09 bits/s) had significantly higher (all 𝑝 < .001) 𝑇 𝑃 than both 6 m (mean = 1.89 bits/s, SD = 0.08 bits/s) and 10 m (mean = 1.57 bits/s, SD = 0.08 bits/s) [PITH_FULL_IMAGE:figures/full_fig_p006_8.png] view at source ↗
Figure 9
Figure 9. Figure 9: NASA TLX scores vs. criteria per Technique. [PITH_FULL_IMAGE:figures/full_fig_p007_9.png] view at source ↗
Figure 10
Figure 10. Figure 10: Subjective preference rankings per Technique. [PITH_FULL_IMAGE:figures/full_fig_p007_10.png] view at source ↗
read the original abstract

This paper presents a systematic evaluation of five controller-free pointing techniques for 2D target selection in AR, using ISO 9241-411. We compared them across multiple depths (2 m, 6 m, 10 m) in terms of movement time, accuracy, throughput, and workload (NASA TLX). Head- and eye-based pointing significantly outperformed the hand-based methods (Finger, Wrist, and Arm); Head input was the most accurate and remained the most consistent across depth. Depth significantly impacted performance, with complex interactions with target size and distance. Our results offer a comprehensive empirical basis for selecting appropriate controller-free techniques in depth-varying AR tasks.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 1 minor

Summary. This paper presents a systematic empirical evaluation of five controller-free pointing techniques (Head, Eye, Finger, Wrist, Arm) for 2D target selection in augmented reality. Using the ISO 9241-411 protocol, it compares the techniques across three fixed depths (2 m, 6 m, 10 m) on movement time, accuracy, throughput, and NASA TLX workload. The central claims are that head- and eye-based methods significantly outperform the hand-based methods, that head input is the most accurate and remains most consistent across depth, and that depth has significant effects with complex interactions involving target size and distance.

Significance. If the empirical ordering and depth-interaction results hold with adequate statistical support, the work supplies a practical, protocol-based comparison that can inform technique selection for depth-varying AR tasks. The use of a standard ISO metric set and direct multi-depth testing is a clear strength for reproducibility and applicability.

major comments (2)
  1. [Abstract] Abstract: the claims of 'significant outperformance' by head- and eye-based methods and of 'depth significantly impacted performance' are stated without any accompanying sample size, statistical test results, error bars, or exclusion criteria. These details are required to evaluate whether the reported ordering is load-bearing or could be explained by sampling variability.
  2. [Abstract / Methods] The manuscript relies on the assumption that the five chosen techniques plus the three fixed depths and ISO 9241-411 protocol adequately capture performance differences relevant to real AR use; however, no sensitivity analysis or comparison to alternative protocols is provided to test this assumption.
minor comments (1)
  1. [Abstract] The abstract would benefit from a brief parenthetical note on participant count and key statistical outcomes to make the summary self-contained.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their constructive comments on our manuscript. We provide point-by-point responses below, indicating where we agree and will revise the manuscript.

read point-by-point responses

  1. Referee: [Abstract] Abstract: the claims of 'significant outperformance' by head- and eye-based methods and of 'depth significantly impacted performance' are stated without any accompanying sample size, statistical test results, error bars, or exclusion criteria. These details are required to evaluate whether the reported ordering is load-bearing or could be explained by sampling variability.

    Authors: We agree that the abstract would benefit from additional statistical context. The full manuscript reports the study details including sample size, repeated-measures ANOVA results, and exclusion criteria in the Methods section, along with error bars in the figures. We will revise the abstract to concisely reference the participant count, note the statistical tests confirming the significant effects for technique and depth, and indicate the error bar conventions used. This will improve transparency without substantially lengthening the abstract. revision: yes

  2. Referee: [Abstract / Methods] The manuscript relies on the assumption that the five chosen techniques plus the three fixed depths and ISO 9241-411 protocol adequately capture performance differences relevant to real AR use; however, no sensitivity analysis or comparison to alternative protocols is provided to test this assumption.

    Authors: We respectfully maintain that the selected techniques, depths, and ISO 9241-411 protocol are appropriate and justified for the study's goals, as explained in the Introduction and Methods: the techniques cover common controller-free approaches in AR, the protocol is a standard for 2D pointing evaluation, and the depths span typical AR ranges. A sensitivity analysis or direct comparison to alternative protocols falls outside the scope of this controlled empirical comparison. However, we will partially revise by expanding the Methods and Limitations sections to more explicitly justify these choices and discuss generalizability constraints. revision: partial

Circularity Check

0 steps flagged

No significant circularity: purely empirical comparison study

full rationale

This is a standard user study paper that applies the ISO 9241-411 protocol to compare five controller-free pointing techniques at three fixed depths. The central claims (head pointing most accurate and depth-consistent) are direct empirical outcomes from measured movement time, error rate, throughput, and NASA TLX scores. No equations, fitted parameters, derivations, or predictions appear in the text. No self-citations are used to justify uniqueness or load-bearing premises. The protocol and metrics are external standards, making the study self-contained against external benchmarks with no reduction of results to inputs by construction.

Axiom & Free-Parameter Ledger

0 free parameters · 0 axioms · 0 invented entities

Empirical user study with no free parameters, axioms, or invented entities; relies on standard experimental design assumptions not detailed in the abstract.

pith-pipeline@v0.9.1-grok · 5642 in / 1060 out tokens · 24902 ms · 2026-06-27T18:11:14.006891+00:00 · methodology

discussion (0)

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Reference graph

Works this paper leans on

91 extracted references · 60 canonical work pages

  1. [1]

    ISO/TS 9241-411:2012 Ergonomics of human-system interaction Part 411: Evaluation methods for the design of physical input devices

    2012. ISO/TS 9241-411:2012 Ergonomics of human-system interaction Part 411: Evaluation methods for the design of physical input devices. https://www.iso. org/standard/54106.html https://www.iso.org/standard/54106.html

    2012

  2. [2]

    Mohammadreza Amini, Wolfgang Stuerzlinger, Robert J Teather, and Anil Ufuk Batmaz. 2025. A Systematic Review of Fitts’ Law in 3D Extended Reality. In Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems (CHI ’25). Association for Computing Machinery, New York, NY, USA, 1–25. https://doi.org/10.1145/3706598.3713623

    work page doi:10.1145/3706598.3713623 2025

  3. [3]

    Ferran Argelaguet and Carlos Andujar. 2009. Efficient 3D Pointing Selection in Cluttered Virtual Environments.IEEE Computer Graphics and Applications29, 6 (Nov. 2009), 34–43. https://doi.org/10.1109/MCG.2009.117 Conference Name: IEEE Computer Graphics and Applications

    work page doi:10.1109/mcg.2009.117 2009

  4. [4]

    Mayra Donaji Barrera Machuca and Wolfgang Stuerzlinger. 2019. The Effect of Stereo Display Deficiencies on Virtual Hand Pointing. InProceedings of the 2019 CHI Conference on Human Factors in Computing Systems (CHI ’19). Association for Computing Machinery, New York, NY, USA, 1–14. https://doi.org/10.1145/ 3290605.3300437

    arXiv 2019

  5. [5]

    Mohammad Raihanul Bashar, Mayra Donaji Barrera Machuca, Wolfgang Stuerzlinger, and Anil Ufuk Batmaz. 2025. The effect of visual depth on the vergence–accommodation conflict on 3D selection performance within virtual reality headsets: MR Bashar et al.The Visual Computer41, 12 (2025), 9645–9661. https://doi.org/10.1007/s00371-025-03990-x

    work page doi:10.1007/s00371-025-03990-x 2025

  6. [6]

    Anil Ufuk Batmaz, Mayra Donaji Barrera Machuca, Duc Minh Pham, and Wolfgang Stuerzlinger. 2019. Do Head-Mounted Display Stereo Deficiencies Affect 3D Pointing Tasks in AR and VR?. In2019 IEEE Conference on Virtual Reality and 3D User Interfaces (VR). 585–592. https://doi.org/10.1109/VR.2019.8797975 ISSN: 2642-5254

    work page doi:10.1109/vr.2019.8797975 2019

  7. [7]

    Bernardos, Gómez , David, , and José R

    Ana M. Bernardos, Gómez , David, , and José R. Casar. 2016. A Comparison of Head Pose and Deictic Pointing Interaction Methods for Smart Environments. International Journal of Human–Computer Interaction32, 4 (April 2016), 325–351. https://doi.org/10.1080/10447318.2016.1142054 Publisher: Taylor & Francis

    work page doi:10.1080/10447318.2016.1142054 2016

  8. [8]

    Jonas Blattgerste, Patrick Renner, and Thies Pfeiffer. 2018. Advantages of eye- gaze over head-gaze-based selection in virtual and augmented reality under varying field of views. InProceedings of the Workshop on Communication by Gaze Interaction (COGAIN ’18). Association for Computing Machinery, New York, NY, USA, 1–9. https://doi.org/10.1145/3206343.3206349

    work page doi:10.1145/3206343.3206349 2018

  9. [9]

    Doug Bowman, Vinh Ly, Joshua Campbell, and Virginia Tech. 2001. Pinch keyboard: Natural text input for immersive virtual environments. (Jan. 2001). http://hdl.handle.net/10919/20010

    2001

  10. [10]

    Bowman, Donald B

    Doug A. Bowman, Donald B. Johnson, and Larry F. Hodges. 1999. Testbed evaluation of virtual environment interaction techniques. InProceedings of the ACM symposium on Virtual reality software and technology (VRST ’99). Association for Computing Machinery, New York, NY, USA, 26–33. https://doi.org/10.1145/ 323663.323667

    arXiv 1999

  11. [11]

    Gavin Buckingham. 2021. Hand Tracking for Immersive Virtual Reality: Opportunities and Challenges.Frontiers in Virtual Reality2 (Oct. 2021). https: //doi.org/10.3389/frvir.2021.728461 Publisher: Frontiers

    work page doi:10.3389/frvir.2021.728461 2021

  12. [12]

    Hansberger

    Lizhou Cao, Huadong Zhang, Chao Peng, and Jeffrey T. Hansberger. 2023. Real- time multimodal interaction in virtual reality - a case study with a large virtual interface.Multimedia Tools Appl.82, 16 (Feb. 2023), 25427–25448. https://doi. org/10.1007/s11042-023-14381-6

    work page doi:10.1007/s11042-023-14381-6 2023

  13. [13]

    Sohan Chowdhury, William Delamare, Pourang Irani, and Khalad Hasan. 2023. PAWS: Personalized Arm and Wrist Movements With Sensitivity Mappings for Controller-Free Locomotion in Virtual Reality.Proc. ACM Hum.-Comput. Interact. 7, MHCI (Sept. 2023), 217:1–217:21. https://doi.org/10.1145/3604264

    work page doi:10.1145/3604264 2023

  14. [14]

    Sohan Chowdhury, A K M Amanat Ullah, Nathan Bruce Pelmore, Pourang Irani, and Khalad Hasan. 2022. WriArm: Leveraging Wrist Movement to Design Wrist+Arm Based Teleportation in VR. In2022 IEEE International Symposium on Mixed and Augmented Reality (ISMAR). 317–325. https://doi.org/10.1109/ ISMAR55827.2022.00047 ISSN: 1554-7868

    arXiv 2022

  15. [15]

    Clark, Aakash B

    Logan D. Clark, Aakash B. Bhagat, and Sara L. Riggs. 2020. Extending Fitts’ law in three-dimensional virtual environments with current low-cost virtual reality technology.International Journal of Human-Computer Studies139 (July 2020), 102413. https://doi.org/10.1016/j.ijhcs.2020.102413

    work page doi:10.1016/j.ijhcs.2020.102413 2020

  16. [16]

    Smith, and Andrew T

    Nathan Cournia, John D. Smith, and Andrew T. Duchowski. 2003. Gaze- vs. hand-based pointing in virtual environments. InCHI ’03 extended abstracts on Human factors in computing systems - CHI ’03. ACM Press, Ft. Lauderdale, Florida, USA, 772. https://doi.org/10.1145/765891.765982

    work page doi:10.1145/765891.765982 2003

  17. [17]

    Crossman

    E.R.F.W. Crossman. 1957. The speed and accuracy of hand movements. The Nature and Acquisition of Industrial Skill

    1957

  18. [18]

    Czerwinski, Greg Smith, Tim Regan, B

    M. Czerwinski, Greg Smith, Tim Regan, B. Meyers, G. Robertson, and G. Starkweather. 2003. Toward Characterizing the Productivity Benefits of Very Large Displays. https://www.semanticscholar.org/ paper/Toward-Characterizing-the-Productivity-Benefits-of-Czerwinski- Smith/d3076f1e3c19bcf2a46922294aa67ddb1d36b34b

    2003

  19. [19]

    Elkin, Matthew Kay, James J

    Lisa A. Elkin, Matthew Kay, James J. Higgins, and Jacob O. Wobbrock. 2021. An Aligned Rank Transform Procedure for Multifactor Contrast Tests. InThe 34th Annual ACM Symposium on User Interface Software and Technology (UIST ’21). Association for Computing Machinery, New York, NY, USA, 754–768. https: //doi.org/10.1145/3472749.3474784

    work page doi:10.1145/3472749.3474784 2021

  20. [20]

    Min Chul Cha, Lee, S.C.: Not merely useful but also amusing: Impact of perceived usefulness and perceived enjoyment on the adop- tion of ai-powered coding assistant

    Ajoy S. Fernandes, Murdison , T. Scott, , and Michael J. Proulx. 2025. Looking in Depth: Targeting by Eye and Controller Input for Multi-Depth Target Placement. International Journal of Human–Computer Interaction41, 13 (July 2025). https: //doi.org/10.1080/10447318.2024.2401657 Publisher: Taylor & Francis, pages = 7952–7967,

    work page doi:10.1080/10447318.2024.2401657 2025

  21. [21]

    Paul M. Fitts. 1954. The information capacity of the human motor system in controlling the amplitude of movement.Journal of Experimental Psychology47, 6 (1954), 381–391. https://doi.org/10.1037/h0055392 Place: US Publisher: American Psychological Association

    work page doi:10.1037/h0055392 1954

  22. [22]

    Anton Franzluebbers and Kyle Johnsen. 2023. Versatile Mixed-method Locomotion under Free-hand and Controller-based Virtual Reality Interfaces. In Proceedings of the 29th ACM Symposium on Virtual Reality Software and Technology (VRST ’23). Association for Computing Machinery, New York, NY, USA, 1–10. https://doi.org/10.1145/3611659.3615701

    work page doi:10.1145/3611659.3615701 2023

  23. [23]

    Julien Gori, Olivier Rioul, Yves Guiard, and Michel Beaudouin-Lafon. 2018. The perils of confounding factors: how Fitts’ law experiments can lead to false conclusions. InProceedings of the 2018 CHI Conference on Human Factors in Computing Systems. 1–10. https://doi.org/10.1145/3173574.3173770

    work page doi:10.1145/3173574.3173770 2018

  24. [24]

    Scott MacKenzie, and Per Bækgaard

    John Paulin Hansen, Vijay Rajanna, I. Scott MacKenzie, and Per Bækgaard. 2018. A Fitts’ law study of click and dwell interaction by gaze, head and mouse with a head-mounted display. InProceedings of the Workshop on Communication by Gaze Interaction (COGAIN ’18). Association for Computing Machinery, New York, NY, USA, 1–5. https://doi.org/10.1145/3206343.3206344

    work page doi:10.1145/3206343.3206344 2018

  25. [25]

    Faizan Haque, Mathieu Nancel, and Daniel Vogel. 2015. Myopoint: Pointing and Clicking Using Forearm Mounted Electromyography and Inertial Motion Sensors. InProceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems (CHI ’15). Association for Computing Machinery, New York, NY, USA, 3653–3656. https://doi.org/10.1145/2702123.2702133

    work page doi:10.1145/2702123.2702133 2015

  26. [26]

    Sandra G. Hart. 2006. Nasa-Task Load Index (NASA-TLX); 20 Years Later. Proceedings of the Human Factors and Ergonomics Society Annual Meeting50, 9 (Oct. 2006), 904–908. https://doi.org/10.1177/154193120605000909 Publisher: SAGE Publications Inc

    work page doi:10.1177/154193120605000909 2006

  27. [27]

    Juan David Hincapié-Ramos, Xiang Guo, Paymahn Moghadasian, and Pourang Irani. 2014. Consumed endurance: a metric to quantify arm fatigue of mid- air interactions. InProceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI ’14). Association for Computing Machinery, New York, NY, USA, 1063–1072. https://doi.org/10.1145/2556288.2557130

    work page doi:10.1145/2556288.2557130 2014

  28. [28]

    Hoffman, Ahna R

    David M. Hoffman, Ahna R. Girshick, Kurt Akeley, and Martin S. Banks. 2008. Vergence–accommodation conflicts hinder visual performance and cause visual fatigue.Journal of Vision8, 3 (March 2008), 33. https://doi.org/10.1167/8.3.33

    work page doi:10.1167/8.3.33 2008

  29. [29]

    Juan Pablo Hourcade and Natasha Bullock-Rest. 2012. How small can you go? analyzing the effect of visual angle in pointing tasks. InProceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI ’12). Association for Computing Machinery, New York, NY, USA, 213–216. https://doi.org/10.1145/ 2207676.2207706

    arXiv 2012

  30. [30]

    Rachel Huang, Carisa Harris-adamson, Dan Odell, and David Rempel. 2019. Design of finger gestures for locomotion in virtual reality.Virtual Reality & Intelligent Hardware1, 1 (Feb. 2019), 1–9. https://doi.org/10.3724/SP.J.2096- 5796.2018.0007

    work page doi:10.3724/sp.j.2096- 2019

  31. [31]

    Rajendran, and Kellogg S

    Izabelle Janzen, Vasanth K. Rajendran, and Kellogg S. Booth. 2016. Modeling the Impact of Depth on Pointing Performance. InProceedings of the 2016 CHI Conference on Human Factors in Computing Systems (CHI ’16). Association for Computing Machinery, New York, NY, USA, 188–199. https://doi.org/10.1145/ 2858036.2858244

    arXiv 2016

  32. [32]

    Adam Jones, J

    J. Adam Jones, J. Edward Swan, Gurjot Singh, Eric Kolstad, and Stephen R. Ellis

  33. [33]

    InProceedings of the 5th symposium on Applied perception in graphics and visualization (APGV ’08)

    The effects of virtual reality, augmented reality, and motion parallax on egocentric depth perception. InProceedings of the 5th symposium on Applied perception in graphics and visualization (APGV ’08). Association for Computing Machinery, New York, NY, USA, 9–14. https://doi.org/10.1145/1394281.1394283

    work page doi:10.1145/1394281.1394283

  34. [34]

    Chaowanan Khundam. 2015. First person movement control with palm normal and hand gesture interaction in virtual reality. In2015 12th International Joint Conference on Computer Science and Software Engineering (JCSSE). 325–330. https: //doi.org/10.1109/JCSSE.2015.7219818

    work page doi:10.1109/jcsse.2015.7219818 2015

  35. [35]

    Daehwa Kim, Keunwoo Park, and Geehyuk Lee. 2021. AtaTouch: Robust Finger Pinch Detection for a VR Controller Using RF Return Loss. InProceedings of the 2021 CHI Conference on Human Factors in Computing Systems (CHI ’21). Association for Computing Machinery, New York, NY, USA, 1–9. https://doi. org/10.1145/3411764.3445442

    work page doi:10.1145/3411764.3445442 2021

  36. [36]

    Haejun Kim, Yuhwa Hong, Jihae Yu, Shuping Xiong, and Woojoo Kim. 2025. The Effect of Target Depth on Performance of Multi-directional Tapping Task in Virtual Reality. InProceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (CHI EA ’25). Association for Computing Machinery, New York, NY, USA, 1–8. https://doi.org...

    work page doi:10.1145/3706599.3719893 2025

  37. [37]

    Peters and S

    Regis Kopper, Doug A. Bowman, Mara G. Silva, and Ryan P. McMahan. 2010. A human motor behavior model for distal pointing tasks.International Journal of Human-Computer Studies68, 10 (Oct. 2010), 603–615. https://doi.org/10.1016/j. ijhcs.2010.05.001

    work page doi:10.1016/j 2010

  38. [38]

    A. J. Kovacs, J. J. Buchanan, and C. H. Shea. 2008. Perceptual influences on Fitts’ law.Experimental Brain Research190, 1 (Sept. 2008), 99–103. https://doi.org/10. 1007/s00221-008-1497-3

    2008

  39. [39]

    Lee, and Mark Billinghurst

    Mikko Kytö, Barrett Ens, Thammathip Piumsomboon, Gun A. Lee, and Mark Billinghurst. 2018. Pinpointing: Precise Head- and Eye-Based Target Selection for Augmented Reality. InProceedings of the 2018 CHI Conference on Human Factors in Computing Systems (CHI ’18). Association for Computing Machinery, New York, NY, USA, 1–14. https://doi.org/10.1145/3173574.3173655

    work page doi:10.1145/3173574.3173655 2018

  40. [40]

    LaViola, Ernst Kruijff, Ryan P

    Joseph J. LaViola, Ernst Kruijff, Ryan P. McMahan, Doug A. Bowman, and Ivan Poupyrev. 2017.3D user interfaces: theory and practice(second edition ed.). Addison-Wesley

    2017

  41. [41]

    Jihyeon Lee, Jinwook Kim, and Jeongmi Lee. 2023. Comparison of Virtual Reality Teleportation Targeting Method Performance depending on the Teleport Distance. In2023 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct). 742–745. https://doi.org/10.1109/ISMAR-Adjunct60411.2023. 00160 ISSN: 2771-1110

    work page doi:10.1109/ismar-adjunct60411.2023 2023

  42. [42]

    Chiuhsiang Joe Lin, Sui-Hua Ho, and Yan-Jyun Chen. 2015. An investigation of pointing postures in a 3D stereoscopic environment.Applied Ergonomics48 (May 2015), 154–163. https://doi.org/10.1016/j.apergo.2014.12.001

    work page doi:10.1016/j.apergo.2014.12.001 2015

  43. [43]

    Lars Lischke, Valentin Schwind, Kai Friedrich, Albrecht Schmidt, and Niels Henze

  44. [44]

    InProceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA ’16)

    MAGIC-Pointing on Large High-Resolution Displays. InProceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA ’16). Association for Computing Machinery, New York, NY, USA, 1706–1712. https://doi.org/10.1145/2851581.2892479

    work page doi:10.1145/2851581.2892479 2016

  45. [45]

    Lystbæk, Peter Rosenberg, Ken Pfeuffer, Jens Emil Grønbæk, and Hans Gellersen

    Mathias N. Lystbæk, Peter Rosenberg, Ken Pfeuffer, Jens Emil Grønbæk, and Hans Gellersen. 2022. Gaze-Hand Alignment: Combining Eye Gaze and Mid-Air Pointing for Interacting with Menus in Augmented Reality.Proc. ACM Hum.- Comput. Interact.6, ETRA (May 2022), 145:1–145:18. https://doi.org/10.1145/ 3530886

    2022

  46. [46]

    Scott MacKenzie

    I. Scott MacKenzie. 1992. Fitts’ Law as a Research and Design Tool in Human- Computer Interaction.Human–Computer Interaction7, 1 (March 1992), 91–139. https://doi.org/10.1207/s15327051hci0701_3 Publisher: Taylor & Francis

    work page doi:10.1207/s15327051hci0701_3 1992

  47. [47]

    Pavel Manakhov, Ludwig Sidenmark, Ken Pfeuffer, and Hans Gellersen. 2024. Filtering on the Go: Effect of Filters on Gaze Pointing Accuracy During Physical Locomotion in Extended Reality.IEEE Transactions on Visualization and Computer Graphics30, 11 (Nov. 2024), 7234–7244. https://doi.org/10.1109/TVCG.2024. 3456153

    work page doi:10.1109/tvcg.2024 2024

  48. [48]

    Madhur Mangalam, Sanjay Oruganti, Gavin Buckingham, and Christoph W. Borst

  49. [49]

    2024), 166

    Enhancing hand-object interactions in virtual reality for precision manual tasks.Virtual Reality28, 4 (Nov. 2024), 166. https://doi.org/10.1007/s10055-024- 01055-3

    work page doi:10.1007/s10055-024- 2024

  50. [50]

    Meta. 2025. Meta Quest MR, VR Headsets & Accessories. https://www.meta. com/ca/quest

    2025

  51. [51]

    Mifsud, Adam S

    Domenick M. Mifsud, Adam S. Williams, Francisco Ortega, and Robert J. Teather

  52. [52]

    In2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW)

    Augmented Reality Fitts’ Law Input Comparison Between Touchpad, Pointing Gesture, and Raycast. In2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW). 590–591. https://doi.org/10.1109/ VRW55335.2022.00146

    arXiv 2022

  53. [53]

    Scott MacKenzie, Per Bækgaard, and Vijay Rajanna

    Katsumi Minakata, John Paulin Hansen, I. Scott MacKenzie, Per Bækgaard, and Vijay Rajanna. 2019. Pointing by gaze, head, and foot in a head-mounted display. InProceedings of the 11th ACM Symposium on Eye Tracking Research & Applications (ETRA ’19). Association for Computing Machinery, New York, NY, USA, 1–9. https://doi.org/10.1145/3317956.3318150

    work page doi:10.1145/3317956.3318150 2019

  54. [54]

    Mark R. Mine. 1995.Virtual Environment Interaction Techniques. Technical Report. University of North Carolina at Chapel Hill, USA. https://www.cs.unc. edu/techreports/95-018.pdf

    1995

  55. [55]

    Pedro Monteiro, Guilherme Gonçalves, Bruno Peixoto, Miguel Melo, and Maximino Bessa. 2023. Evaluation of Hands-Free VR Interaction Methods During a Fitts’ Task: Efficiency and Effectiveness.IEEE Access11 (2023), 70898–70911. https://doi.org/10.1109/ACCESS.2023.3293057 Conference Name: IEEE Access

    work page doi:10.1109/access.2023.3293057 2023

  56. [56]

    Aunnoy K Mutasim, Anil Ufuk Batmaz, and Wolfgang Stuerzlinger. 2021. Pinch, Click, or Dwell: Comparing Different Selection Techniques for Eye-Gaze-Based Pointing in Virtual Reality. InACM Symposium on Eye Tracking Research and Applications (ETRA ’21 Short Papers). Association for Computing Machinery, New York, NY, USA, 1–7. https://doi.org/10.1145/3448018.3457998

    work page doi:10.1145/3448018.3457998 2021

  57. [57]

    Myers, Rishi Bhatnagar, Jeffrey Nichols, Choon Hong Peck, Dave Kong, Robert Miller, and A

    Brad A. Myers, Rishi Bhatnagar, Jeffrey Nichols, Choon Hong Peck, Dave Kong, Robert Miller, and A. Chris Long. 2002. Interacting at a distance: measuring the performance of laser pointers and other devices. InProceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI ’02). Association for Computing Machinery, New York, NY, USA, 33–40....

    arXiv 2002

  58. [58]

    Djallil Naceri, Ryad Chellali, Fabien Dionnet, and Simone Toma. 2010. Depth Perception Within Virtual Environments: Comparison Between two Display Technologies.International Journal on Advances in Intelligent Systems3 (Jan. 2010), 51–64. https://www.researchgate.net/publication/242330470

    arXiv 2010

  59. [59]

    Irani, and Michel Beaudouin-Lafon

    Mathieu Nancel, Olivier Chapuis, Emmanuel Pietriga, Xing-Dong Yang, Pourang P. Irani, and Michel Beaudouin-Lafon. 2013. High-precision pointing on large wall displays using small handheld devices. InProceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI ’13). Association for Computing Machinery, New York, NY, USA, 831–840. https:/...

    arXiv 2013

  60. [60]

    Bakdauren Narbayev, A K M Amanat Ullah, Jaisie Sin, Patricia Lasserre, and Khalad Hasan. 2025. Exploring Pointing and Confirmation Techniques for Teleportation Across Varying Elevations in Virtual Reality . In2025 IEEE International Symposium on Mixed and Augmented Reality (ISMAR). IEEE Computer Society, Los Alamitos, CA, USA, 1671–1681. https://doi.org/1...

    arXiv 2025

  61. [61]

    Ian Oakley, John Sunwoo, and Il-Yeon Cho. 2008. Pointing with fingers, hands and arms for wearable computing. InCHI ’08 Extended Abstracts on Human Factors in Computing Systems (CHI EA ’08). Association for Computing Machinery, New York, NY, USA, 3255–3260. https://doi.org/10.1145/1358628.1358840

    work page doi:10.1145/1358628.1358840 2008

  62. [62]

    Natalia Ocampo, J Felipe Gonzalez, and Robert J Teather. 2025. Comparing Hand and Controller Avatars with Hand Tracking and Controller-Based Interaction. In2025 IEEE International Symposium on Mixed and Augmented Reality (ISMAR). IEEE, 164–174. https://doi.org/10.1109/ISMAR67309.2025.00029

    work page doi:10.1109/ismar67309.2025.00029 2025

  63. [63]

    Ken Pfeuffer, Benedikt Mayer, Diako Mardanbegi, and Hans Gellersen. 2017. Gaze + pinch interaction in virtual reality. InProceedings of the 5th Symposium on Spatial User Interaction (SUI ’17). Association for Computing Machinery, New York, NY, USA, 99–108. https://doi.org/10.1145/3131277.3132180

    work page doi:10.1145/3131277.3132180 2017

  64. [64]

    Aniruddha Prithul, Jiwan Bhandari, Walker Spurgeon, and Eelke Folmer. 2022. Evaluation of Hands-free Teleportation in VR. InProceedings of the 2022 ACM Symposium on Spatial User Interaction (SUI ’22). Association for Computing Machinery, New York, NY, USA, 1–6. https://doi.org/10.1145/3565970.3567683

    work page doi:10.1145/3565970.3567683 2022

  65. [65]

    Yuan Yuan Qian and Robert J. Teather. 2017. The eyes don’t have it: an empirical comparison of head-based and eye-based selection in virtual reality. InProceedings of the 5th Symposium on Spatial User Interaction (SUI ’17). Association for Computing Machinery, New York, NY, USA, 91–98. https://doi.org/10.1145/ 3131277.3132182

    arXiv 2017

  66. [66]

    Alexander Schäfer, Gerd Reis, and Didier Stricker. 2021. Controlling Teleportation- Based Locomotion in Virtual Reality with Hand Gestures: A Comparative Evaluation of Two-Handed and One-Handed Techniques.Electronics10, 6 (Jan. 2021), 715. https://doi.org/10.3390/electronics10060715 Number: 6 Publisher: Multidisciplinary Digital Publishing Institute

    work page doi:10.3390/electronics10060715 2021

  67. [67]

    Alexander Schäfer, Gerd Reis, and Didier Stricker. 2022. Controlling Continuous Locomotion in Virtual Reality with Bare Hands Using Hand Gestures. InVirtual Reality and Mixed Reality, Gabriel Zachmann, Mariano Alcañiz Raya, Patrick Bourdot, Maud Marchal, Jeanine Stefanucci, and Xubo Yang (Eds.). Springer International Publishing, Cham, 191–205. https://do...

    work page doi:10.1007/978-3-031- 2022

  68. [68]

    Mengdi Shi, Tao Hu, and Jiawen Yu. 2022. Pointing Cursor Interaction in Virtual Reality from the Perspective of Distance Perception | IIETA. https://doi.org/10. 18280/ts.390209

    2022

  69. [69]

    Garth Shoemaker, Takayuki Tsukitani, Yoshifumi Kitamura, and Kellogg S. Booth

  70. [70]

    ACM Trans

    Two-Part Models Capture the Impact of Gain on Pointing Performance. ACM Trans. Comput.-Hum. Interact.19, 4 (2012), 28:1–28:34. https://doi.org/10. 1145/2395131.2395135

    arXiv 2012

  71. [71]

    Shaishav Siddhpuria, Sylvain Malacria, Mathieu Nancel, and Edward Lank. 2018. Pointing at a Distance with Everyday Smart Devices. InProceedings of the 2018 CHI Conference on Human Factors in Computing Systems (CHI ’18). Association for Computing Machinery, New York, NY, USA, 1–11. https://doi.org/10.1145/ 3173574.3173747

    arXiv 2018

  72. [72]

    Ludwig Sidenmark and Hans Gellersen. 2019. Eye, Head and Torso Coordination During Gaze Shifts in Virtual Reality.ACM Trans. Comput.-Hum. Interact.27, 1 (2019), 4:1–4:40. https://doi.org/10.1145/3361218

    work page doi:10.1145/3361218 2019

  73. [73]

    Ludwig Sidenmark and Hans Gellersen. 2019. Eye&Head: Synergetic Eye and Head Movement for Gaze Pointing and Selection. InProceedings of the 32nd Annual ACM Symposium on User Interface Software and Technology (UIST ’19). Association for Computing Machinery, New York, NY, USA, 1161–1174. https: //doi.org/10.1145/3332165.3347921

    work page doi:10.1145/3332165.3347921 2019

  74. [74]

    Ludwig Sidenmark, Franziska Prummer, Joshua Newn, and Hans Gellersen. 2023. Comparing Gaze, Head and Controller Selection of Dynamically Revealed Targets in Head-Mounted Displays.IEEE Transactions on Visualization and Computer Graphics29, 11 (Nov. 2023), 4740–4750. https://doi.org/10.1109/TVCG.2023. 3320235

    work page doi:10.1109/tvcg.2023 2023

  75. [75]

    Siddhanth Raja Sindhupathiraja, A K M Amanat Ullah, William Delamare, and Khalad Hasan. 2024. Exploring Bi-Manual Teleportation in Virtual Reality. In 2024 IEEE Conference Virtual Reality and 3D User Interfaces (VR). 754–764. https: //doi.org/10.1109/VR58804.2024.00095 ISSN: 2642-5254

    work page doi:10.1109/vr58804.2024.00095 2024

  76. [76]

    William Soukoreff and I

    R. William Soukoreff and I. Scott MacKenzie. 2004. Towards a standard for pointing device evaluation, perspectives on 27 years of Fitts’ law research in HCI.International Journal of Human-Computer Studies61, 6 (Dec. 2004), 751–789. https://doi.org/10.1016/j.ijhcs.2004.09.001 Comparing Controller-Free Pointing Techniques Across Depth for 2D Selection in Au...

    work page doi:10.1016/j.ijhcs.2004.09.001 2004

  77. [77]

    Da Tao, Xiaofeng Diao, Tieyan Wang, Jingya Guo, and Xingda Qu. 2021. Freehand interaction with large displays: Effects of body posture, interaction distance and target size on task performance, perceived usability and workload.Applied Ergonomics93 (May 2021), 103370. https://doi.org/10.1016/j.apergo.2021.103370

    work page doi:10.1016/j.apergo.2021.103370 2021

  78. [78]

    Teather, Andriy Pavlovych, Wolfgang Stuerzlinger, and I

    Robert J. Teather, Andriy Pavlovych, Wolfgang Stuerzlinger, and I. Scott MacKenzie. 2009. Effects of tracking technology, latency, and spatial jitter on object movement. In2009 IEEE Symposium on 3D User Interfaces. 43–50. https://doi.org/10.1109/3DUI.2009.4811204

    work page doi:10.1109/3dui.2009.4811204 2009

  79. [79]

    Teather and Wolfgang Stuerzlinger

    Robert J. Teather and Wolfgang Stuerzlinger. 2013. Pointing at 3d target projections with one-eyed and stereo cursors. InProceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI ’13). Association for Computing Machinery, New York, NY, USA, 159–168. https://doi.org/10.1145/ 2470654.2470677

    arXiv 2013

  80. [80]

    Eleftherios Triantafyllidis and Zhibin Li. 2021. The Challenges in Modeling Human Performance in 3D Space with Fitts’ Law. InExtended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems (CHI EA ’21). Association for Computing Machinery, New York, NY, USA, 1–9. https://doi.org/10.1145/ 3411763.3443442

    arXiv 2021

Showing first 80 references.