Skip to main content
SpringerLink
Log in

Exploring the effectiveness of an augmented reality dressing room

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

Abstract

In this paper, we describe our experience with the design of an augmented reality dressing room in which 3D models of a dress are overlaid with a color image from a camera to provide the function of a sort of virtual mirror. In such a way, the customer can move around to understand if a dress suits and fits them well. The project is implemented in Unity 4 Pro in combination with the Microsoft Kinect 2 for the tracking process. Design issues and technical implementation as well as the prospects for further development of the techniques are discussed. To assess the validity of our proposal, we have conducted a user study using 47 participants with different levels of experience with video games and devices used to play them. The empirical method used is qualitative. To this end, we used questionnaire-based surveys. The obtained results suggest that our solution represents a viable means to simulate dressing rooms, and participants in the study found the interaction with our 3D models to be natural for understanding if a dress suits and fits them well. Overall, the participants found our application very useful from a practical point of view.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16

Similar content being viewed by others

Notes

  1. Please read the paper on-screen or as a color-printed paper version; we utilize color pictures.

References

  1. Ahn T, Ryu S, Han I (2007) The impact of web quality and playfulness on user acceptance of online retailing. Inf Manag 44(3):263–275. https://doi.org/10.1016/j.im.2006.12.008

    Article  Google Scholar 

  2. Araki N, Muraoka Y (2008) Follow-the-trial-fitter: real-time dressing without undressing. In: Third International conference on digital information management, 2008. ICDIM 2008, pp 33–38

  3. Berger K, Meister S, Nair R, Kondermann D (2013) Time-of-flight and depth imaging. Sensors, algorithms, and applications: Dagstuhl 2012 seminar on time-of-flight imaging and GCPR 2013 workshop on imaging new modalities, chap. A state of the art report on kinect sensor setups in computer vision. Springer, Berlin, pp 257–272

    Google Scholar 

  4. Brooke J (2013) Sus: a retrospective. J Usab Stud 8(2):29–40. http://dl.acm.org/citation.cfm?id=2817912.2817913

    Google Scholar 

  5. Cordero R (2010) Can technology help fashion etailers tackle ‘try before you buy’? http://www.businessoffashion.com/articles/fashion-tech/fashion-2-0-can-technology-help-fashion-etailers-tackle-try-before-you-buy

  6. Developer W (2016) Kinect for Windows features. https://www.microsoft.com/en-us/kinectforwindows/meetkinect/features.aspx

  7. Developer W (2016) Kinect SDK 2.0. https://www.microsoft.com/en-us/kinectforwindows/develop/

  8. Developer W (2016) Tracking users with kinect skeletal tracking. https://msdn.microsoft.com/en-us/library/jj131025.aspx

  9. Erra U, Colonnese V (2015) Experiences in the development of an augmented reality dressing room. In: Proceedings of international conference augmented and virtual reality, pp 467–474

  10. Facecake marketing technologies, inc. (2016) http://www.facecake.com/

  11. Fitnect (2016). http://www.fitnect.hu/

  12. Greuter S, Roberts D J (2014) Spacewalk: movement and interaction in virtual space with commodity hardware. In: Proceedings of the 2014 conference on interactive entertainment, IE2014. ACM, New York, pp 1:1–1:7

  13. Holte M B (2013) Virtual, augmented and mixed reality. systems and applications: 5th international conference, VAMR 2013, held as part of HCI international 2013, Las Vegas, NV, USA, July 21-26, 2013, Proceedings, Part II, chap. The virtual dressing room: a perspective on recent developments. Springer, Berlin, pp 241–250

  14. Holte M B, Gao Y, Petersson Brooks E (2015) The virtual dressing room: a usability and user experience study. Springer International Publishing, Cham, pp 429–437

    Google Scholar 

  15. Isikdogan F, Kara G (2012) A real time virtual dressing room application using kinect. Comput Vis Course Project

  16. Juristo N, Moreno A (2001) Basics of software engineering experimentation. Kluwer Academic Publishers

  17. Kitchenham B, Pfleeger S, Pickard L, Jones P, Hoaglin D, El Emam K, Rosenberg J (2002) Preliminary guidelines for empirical research in software engineering. IEEE Trans Soft Eng 28(8):721–734

    Article  Google Scholar 

  18. Kjærside K, Kortbek KJ, Hedegaard H, Grønbæk K (2005) ARDressCode: augmented dressing room with tag-based motion tracking and real-time clothes simulation. In: Central European multimedia and virtual reality conference

  19. Lin Y L, Wang M J J (2016) The development of a clothing fit evaluation system under virtual environment. Multimed Tools Appl 75(13):7575–7587

    Article  Google Scholar 

  20. Magnenat-Thalmann N, Laperrière R, Thalmann D (1988) Joint-dependent local deformations for hand animation and object grasping. In: Proceedings on graphics interface ’88. Canadian Information Processing Society, Toronto, pp 26–33

  21. Martin C G, Oruklu E (2012) Human friendly interface design for virtual fitting room applications on android based mobile devices. J Signal Inf Process 3(4):481–490

    Google Scholar 

  22. Michael N, Drakou M, Lanitis A (2017) Model-based generation of personalized full-body 3D avatars from uncalibrated multi-view photographs. Multimed Tools Appl 76(12):14,169–14,195

    Article  Google Scholar 

  23. Oppenheim A N (2000) Questionnaire design, interviewing and attitude measurement continuum

  24. Parent R (2012) Computer animation: algorithms and techniques, 3rd edn. Morgan Kaufmann Publishers Inc., San Francisco

    Google Scholar 

  25. Presle P (2012) A virtual dressing room based on depth data. Institut für Softwaretechnik und Interaktive Systeme, Master’s thesis

    Google Scholar 

  26. Sands W (2015) Reinventing retail: what businesses need to know for 2015 whitepaper. http://www.walkersands.com/futureofretail

  27. Shaikh A A, Shinde P S, Singh S R, Chandra S, Khan R A (2014) A review on virtual dressing room for e-shopping using augmented reality. Int J Soft Comput Eng (IJSCE) 4(5):98–102

    Google Scholar 

  28. Shotton J, Sharp T, Kipman A, Fitzgibbon A, Finocchio M, Blake A, Cook M, Moore R (2013) Real-time human pose recognition in parts from single depth images. Commun ACM 56(1):116–124

    Article  Google Scholar 

  29. Szymczyk M, Von Hungen A, Callens B, Forsman H, Benoff J (2011) Providing a simulation of wearing items such as garments and/or accessories. http://www.google.com/patents/US20110040539. US Patent App. 12/822,168

  30. Technologies U (2016) Unity game engine. https://unity3d.com/

  31. Wang R, Du H, Zhou F, Deng D, Liu Y (2014) An adaptive neural fuzzy network clothing comfort evaluation model and application in digital home. Multimed Tools Appl 71(2):395–410

    Article  Google Scholar 

  32. Wohlin C, Runeson P, Höst M, Ohlsson M, Regnell B, Wesslén A (2012) Experimentation in software engineering. Kluwer

  33. Zugara (2009) Can technology help fashion etailers tackle ‘try before you buy?’ http://zugara.com/virtual-dressing-room-technology/virtual-dressing-room-kiosk.

Download references

Author information

Authors and Affiliations

  1. Dipartimento di Matematica, Informatica ed Economia, Università degli Studi della Basilicata, Potenza, Italy

    Ugo Erra, Giuseppe Scanniello & Valerio Colonnese

Authors
  1. Ugo Erra
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Giuseppe Scanniello
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Valerio Colonnese
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ugo Erra.

Appendix: surveys

Appendix: surveys

We report the questionnaires used in our study.

1.1 A.1 Pre-questionnaire

  • Q1: Do you like video gaming?

    Strongly disagree○○○○○ Strongly agree

  • Q2: What do you consider your experience with video games?

    Non-expert ○○○○○ Expert

  • Q3: How many hours per week do you spend playing video games?

    □ Less than one hour □ Between one and seven hours □ Between eight and fourteen hours

    □ Between fifteen and twenty-one hours □ More than twenty-one hours

  • Q4: Which types of video games do you play?

    □ First-Person Shooter □ Adventure □ Role-Playing Games □ Strategy/Tactical □ Sports □ Fighting □ Dance/Rhythm □ Survival Horror □ Other (Add here which one) □ None (I do not play any video games)

  • Q5: Which [–]type of device do you use when playing video games?

    □ Mouse/keyboard □ Kinect □ Joypad □ PlayStation □ Other (Add here which one) □ None

  • Q6: Do you have vision deficiencies?

    Yes ○ No ○

  • Q7: If you answered ‘‘Yes’’ to the previous question, which type of deficiency do you have?

    • Open Question

  • Q8: Do you wear glasses?

    Yes ○ No ○

  • Q9: What do you consider your IT experience?

    Non-expert ○○○○○ Expert

  • Q10: Have you heard of the term Augmented Reality?

    Yes ○ No ○

  • Q11: What do you consider your experience with Augmented Reality?

    Non-expert ○○○○○ Expert

  • Q12: With which of these input devices do you have more confidence?

    □ Kinect □ Leap Motion □ PlayStation Move □ Wii Mote □ None (No familiarity with natural user interfaces)

  • Q13: Have you heard of the Kinect?

    Yes ○ No ○

  • Q14: If you answered “Yes” to the previous question, what is your experience with the Kinect?

    Non-expert ○○○○○ Expert

1.2 A.2 Final questionnaire

Browsing the clothing catalog:

  • T1_a: Browse the content of the clothing catalog was straightforward?

    Strongly disagree ○○○○○ Strongly agree

  • T1_b: The virtual dressing room was responsive during the execution of the actions needed to browse the content of the clothing catalog.

    Strongly disagree ○○○○○ Strongly agree

  • T1_c: The interaction was natural during the execution of the actions while browsing the content of the clothing catalog.

    Strongly disagree ○○○○○ Strongly agree

  • T1_d: Have you experienced one of the following contraindications while browsing the content of the clothing catalog? Please select all that apply.

    □ High sensibility □ Lack of the field of view of the device □ Movement limitations □ Motor difficulties □ Dizziness □ Nausea □ Tennis elbow □ Tiredness □ Other □ None

Questions on dress suitability

  • T2_a: The interact with the virtual dressing room while determining the suitability of a dress was straightforward?

    • Same answer options as T1_a

  • T2_b: The virtual dressing room was responsive during the execution of the actions needed to complete the task of determining the suitability of a dress.

    • Same answer options as T1_b

  • T2_c: The interaction was natural during the execution of the actions while determining the suitability of a dress?

    • Same answer options as T1_c

  • T2_d: Have you experienced (while determining the suitability of a dress) one of the following contraindications? Please select all that apply.

    • Same answer options as T1_d

1.3 Perceived Usefulness (PU)

  1. PU1.

    Using the virtual dressing room would enable me to accomplish tasks more quickly.

    very unlikely ○○○○○ very likely

  2. PU2.

    Using the virtual dressing room would improve my performance (more satisfaction related to the possibility of trying more clothes in less time) when shopping.

    very unlikely ○○○○○ very likely

  3. PU3.

    Using the virtual dressing room would reduce the time to choose an item of clothing.

    very unlikely ○○○○○ very likely

  4. PU4.

    Using the virtual dressing room would make the decision-making process more interesting/exciting.

    very unlikely ○○○○○ very likely

  5. PU5.

    Would you recommend the virtual dressing room for a commercial activity?

    very unlikely ○○○○○ very likely

1.4 Perceived Ease of Use (EOU)

  1. EOU1.

    Learning to operate the virtual dressing room would be easy for me.

    very unlikely ○○○○○ very likely

  2. EOU2.

    I would find it easy to get the virtual dressing room to do what I want it to do.

    very unlikely ○○○○○ very likely

  3. EOU3.

    My interaction with the virtual dressing room would be clear and understandable.

    very unlikely ○○○○○ very likely

  4. EOU4.

    I would find the virtual dressing room easy to use.

    very unlikely ○○○○○ very likely

1.5 Perceived Playfulness (PP)

  1. PP1.

    When interacting with the virtual dressing room, I do not realize the time elapsed.

    very unlikely ○○○○○ very likely

  2. PP2.

    When interacting with the virtual dressing room, I am not aware of any noise.

    very unlikely ○○○○○ very likely

  3. PP3.

    Using the virtual dressing room ensures that I have fun when performing my task.

    very unlikely ○○○○○ very likely

  4. PP4.

    Using the virtual dressing room arouses my imagination.

    very unlikely ○○○○○ very likely

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Erra, U., Scanniello, G. & Colonnese, V. Exploring the effectiveness of an augmented reality dressing room. Multimed Tools Appl 77, 25077–25107 (2018). https://doi.org/10.1007/s11042-018-5758-2

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-018-5758-2

Keywords

Search

Navigation