Nothing Special   »   [go: up one dir, main page]
Skip to main content
Springer Nature Link
Log in

A Multimodal Assistive System for Helping Visually Impaired in Social Interactions

  • HAUPTBEITRAG
  • A MULTIMODAL ASSISTIVE SYSTEM
  • Published:
Informatik-Spektrum Aims and scope

Abstract

Access to non-verbal cues in social interactions is vital for people with visual impairment. It has been shown that non-verbal cues such as eye contact, number of people, their names and positions are helpful for individuals who are blind. In this paper, we present a real time multi-modal system that provides such non-verbal cues via audio and haptic interfaces. We assess the usefulness of the proposed system both quantitatively and qualitatively by gathering feedback with a focus group of visually impaired participants in a typical social interaction setting. The paper provides important insight about developing such technology for this significant part of society.

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

Access this article

Log in via an institution

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

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

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Ahmed T, Hoyle R, Connelly K, Crandall D, Kapadia A (2015) Privacy Concerns and Behaviors of People With Visual Impairments. In: Proceedings of CHI. ACM, pp 3523–3532

  2. Alletto S, Serra G, Calderara S, Solera F, Cucchiara R (2014) From Ego to Nos-Vision: Detecting Social Relationships in First-Person Views. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp 580–585

  3. Astler D, Chau H, Hsu K, Hua A, Kannan A, Lei L, Nathanson M, Paryavi E, Rosen M, Unno H et al. (2011) Increased Accessibility to Nonverbal Communication Through Facial and Expression Recognition Technologies for Blind/Visually Impaired Subjects. In: Proceedings ACM SIGACCESS Conference on Computers and accessibility. ACM, pp. 259–260

  4. Astler D, Chau H, Hsu K, Hua A, Kannan A, Lei L, Nathanson M, Paryavi E, Rosen M (2012) Facial and Expression Recognition for the Blind Using Computer Vision. Technical Report. University of Maryland

  5. Ba SO, Odobez J-M (2009) Recognizing visual focus of attention from head pose in natural meetings. IEEE T Sys Man Cy B 39(1):16–33

  6. Brady E, Morris MR, Zhong Y, White S, Bigham JP (2013) Visual Challenges in the Everyday Lives of Blind People. In: Proceedings of CHI. ACM, pp 2117–2126

  7. Chaudhry S, Chandra R (2015) Design of a Mobile Face Recognition System for Visually Impaired Persons. arXiv preprint arXiv:1502.00756

  8. Davis FD (1989) Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quart 319–340

  9. Fiannaca A, Apostolopoulous I, Folmer E (2014) Headlock: A Wearable Navigation Aid That Helps Blind Cane Users Traverse Large Open Spaces. In: Proceedings of the 16th International ACM SIGACCESS Conference on Computers & Accessibility. ACM, pp 19–26

  10. Kramer KM, Hedin DS, Rolkosky DJ (2010) Smartphone Based Face Recognition Tool for the Blind. In: Annual International Conference of the IEEE Engineering in Medicine and Biology. IEEE, pp 4538–4541

  11. Krishna S, Colbry D, Black J, Balasubramanian V, Panchanathan S (2008) A Systematic Requirements Analysis and Development of an Assistive Device to Enhance the Social Interaction of People Who Are Blind or Visually Impaired. In: Workshop on Computer Vision Applications for the Visually Impaired

  12. Kazemi V, Sullivan J (2014) One Millisecond Face Alignment with an Ensemble of Regression Trees. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp 1867–1874

  13. Matsushita Y, Ofek E, Tang X, Shum H-Y (2005) Full-Frame Video Stabilization. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), vol 1. IEEE, pp 50–57

  14. McDaniel T, Krishna S, Balasubramanian V, Colbry D, Panchanathan S (2008) Using a Haptic Belt to Convey Non-Verbal Communication Cues During Social Interactions to Individuals Who Are Blind. In: IEEE International Workshop on Haptic Audio Visual Environments and Games. HAVE 2008. IEEE, pp 13–18

  15. Meers S, Ward K (2007) Haptic Gaze-Tracking Based Perception of Graphical User Interfaces. In: Information Visualization. IEEE, pp 713–719

  16. Otsuka K, Takemae Y, Yamato J (2005) A Probabilistic Inference of Multiparty-Conversation Structure Based on Markov-Switching Models of Gaze Patterns, Head Directions, and Utterances. In: Proceedings of the 7th International Conference on Multimodal Interfaces. ACM, pp 191–198

  17. Panchanathan S, Chakraborty S, McDaniel T (2016) Social interaction assistant: a person-centered approach to enrich social interactions for individuals with visual impairments. IEEE J Sel Top Signal Process 10(5):

  18. Shilkrot R, Huber J, Liu C, Maes P, Nanayakkara SC (2014) A Wearable Text-Reading Device for the Visually-Impaired. In: CHI’14 Extended Abstracts on Human Factors in Computing Systems. ACM, pp 193–194

  19. Shinohara K, Wobbrock JO (2011) In the Shadow of Misperception: Assistive Technology Use and Social Interactions. In: Proceedings of CHI. ACM, pp 705–714

  20. Stiefelhagen R, Yang J, Waibel A (2002) Modeling focus of attention for meeting indexing based on multiple cues. IEEE T Neural Netw 13(4):928–938

  21. Venkatesh V, Morris MG, Davis GB, Davis FD (2003) User acceptance of information technology: toward a unified view. MIS Quart :425–478

  22. Velázquez R (2010) Wearable Assistive Devices for the Blind. In: Wearable and Autonomous Biomedical Devices and Systems for Smart Environment. Springer, pp 331–349

  23. Voit M, Stiefelhagen R (2006) Tracking Head Pose and Focus of Attention with Multiple Far-Field Cameras. In: Proceedings of the 8th International Conference on Multimodal Interfaces. ACM, pp 281–286

  24. Yang B, Chen S (2013) A comparative study on Local Binary Pattern (LBP) based face recognition: LBP histogram versus LBP image. Neurocomputing 120:365–379

  25. Yi C, Flores RW, Chincha R, Tian YL (2013) Finding objects for assisting blind people. Netw Model Anal Health Inform Bioinform 2(2):71–79

Download references

Author information

Authors and Affiliations

  1. Institute of Anthropomatics and Robotics, Karlsruhe Institute of Technology (KIT), 76131, Karlsruhe, Germany

    M. Saquib Sarfraz, Angela Constantinescu, Melanie Zuzej & Rainer Stiefelhagen

Authors
  1. M. Saquib Sarfraz
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Angela Constantinescu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Melanie Zuzej
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Rainer Stiefelhagen
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to M. Saquib Sarfraz.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sarfraz, M., Constantinescu, A., Zuzej, M. et al. A Multimodal Assistive System for Helping Visually Impaired in Social Interactions. Informatik Spektrum 40, 540–545 (2017). https://doi.org/10.1007/s00287-017-1077-7

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00287-017-1077-7

Search

Navigation