Skip to main content

Character-IoT (CIoT): Toward Human-Centered Ubiquitous Computing

  • Chapter
  • First Online:
Character Computing

Part of the book series: Human–Computer Interaction Series ((HCIS))

  • 743 Accesses

Abstract

Character Computing envisions systems that can detect, synthesize, and adapt to human character. The development and realization of this field hinge upon the availability of data about human character traits and states. This data must be comprehensive enough to model the embedded causality in the triad of behavior–situation–character that makes up the core of Character Computing. Acquiring this data requires an intelligent and scalable platform for sensing, processing, analysis, and decision support, which we label as Character-IoT (CIoT). This chapter investigates how this CIoT can be realized. A comprehensive study of sensing modalities in the areas of affective and personality computing is presented to identify the technologies that can be adopted in Character Computing. This includes facial expressions, speech, text, gestures, and others. We also highlight artificial intelligence techniques that are most commonly used in areas of affective and personality computing and analyze which ones are suitable for Character Computing. Finally, we propose an architectural framework for CIoT that can be adopted by future researchers in this field.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 139.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 179.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 179.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Abowd G, Dey A, Brown P, Davies N, Smith M, Steggles P (1999) Towards a better understanding of context and context-awareness. In: Handheld and ubiquitous computing, pp 304–307

    Google Scholar 

  • Acampora G, Cook DJ, Rashidi P, Vasilakos AV (2013) A survey on ambient intelligence in healthcare. Proc IEEE 101(12):2470–2494

    Article  Google Scholar 

  • Alarcao SM, Fonseca MJ (2018) Emotions recognition using eeg signals: a survey. IEEE Trans Affect Comput 1–1

    Google Scholar 

  • Anagnostopoulos C-K, Iliou T, Giannoukos I (2015) Features and classifiers for emotion recognition from speech: a survey from 2000 to 2011. Artif Intell Rev 43(2):155–177

    Article  Google Scholar 

  • Batrinca L, Mana N, Lepri B, Pianesi F, Sebe N (2011) Please, tell me about yourself: automatic personality assessment using short self-presentations. In: Proceedings of the 13th international conference on multimodal interfaces, ICMI ’11, pp 255–262

    Google Scholar 

  • Bellavista P, Corradi A, Fanelli M, Foschini L (2012) A survey of context data distribution for mobile ubiquitous systems. ACM Comput Surv 44(4):24:1–24:45

    Google Scholar 

  • Benkhelifa E, Welsh T, Hamouda W (2018) A critical review of practices and challenges in intrusion detection systems for iot: toward universal and resilient systems. IEEE Commun Surv Tutor 20(4):3496–3509

    Article  Google Scholar 

  • Biel J, Gatica-Perez D (2013) The youtube lens: crowdsourced personality impressions and audiovisual analysis of vlogs. IEEE Trans Multimed 15(1):41–55

    Article  Google Scholar 

  • Calvo R, D’Mello S (2010) Affect detection: an interdisciplinary review of models, methods, and their applications. IEEE Trans Affect Comput 1(1):18–37

    Article  Google Scholar 

  • Cao Z, Simon T, Wei S-E, Sheikh Y (2016) Realtime multi-person 2d pose estimation using part affinity fields. CoRR

    Google Scholar 

  • Chen L, Hoey J, Nugent CD, Cook DJ, Yu DJ (2012) Sensor-based activity recognition. IEEE Trans Syst Man Cybernet Part C Appl Rev 42(6):790–808

    Article  Google Scholar 

  • Colombo A, Cusano C, Schettini R (2006) 3d face detection using curvature analysis. J Pattern Recognit 39(3):444–455

    Article  Google Scholar 

  • Corneanu C, Simon M, Cohn J, Guerrero S (2016) Survey on rgb, 3d, thermal, and multimodal approaches for facial expression recognition: history, trends, and affect-related applications. IEEE Trans Pattern Anal Mach Intell 38(8):1548–1568

    Article  Google Scholar 

  • Cristani M, Vinciarelli A,  Segalin C, Perina A (2013) Unveiling the multimedia unconscious: Implicit cognitive processes and multimedia content analysis. In: Proceedings of the 21st ACM international conference on multimedia, MM ’13

    Google Scholar 

  • Dhall A, Goecke R, Lucey S, Gedeon T (2011) Acted facial expressions in the wild database. Technical Report, TR-CS-11-02

    Google Scholar 

  • Einstein G, Kennedy SH, Downar J (2013) Gender/sex differences in emotions. Medicographia 35(3):271–280

    Google Scholar 

  • Ekman P (1982) Emotion in the human face. Cambridge University Press, Cambridge

    Google Scholar 

  • Ekman P (1971) Universal and cultural differences in facial expression of emotion. Nebraska Symp Motiv 19:207–283

    Google Scholar 

  • El-Mougy A, Al-Shiab I, Ibnkahla M (2019) Scalable personalized iot networks. Proc IEEE 107(4):695–710

    Google Scholar 

  • El-Sayed H, Sankar S, Prasad M, Puthal D, Gupta A, Mohanty M, Lin C (2018) Edge of things: the big picture on the integration of edge, iot and the cloud in a distributed computing environment. IEEE Access 6:1706–1717

    Article  Google Scholar 

  • Erb B, Meissner D, Kargl F, Steer B, Cuadrado F,  Margan D, Pietzuch P (2018) Graphtides: a framework for evaluating stream-based graph processing platforms. In: Proceedings of the 1st ACM SIGMOD joint international workshop on graph data management experiences & systems (GRADES) and network data analytics (NDA), pp 3:1–3:10

    Google Scholar 

  • Fragopanagos N, Taylor J (2005) Emotion recognition in human-computer interaction. J Neural Netw 18(4):389–405

    Article  Google Scholar 

  • Giannakopoulos T, Pikrakis A, Theodoridis S (2009) dimensional approach to emotion recognition of speech from movies. In: IEEE international conference on acoustics, speech and signal processing

    Google Scholar 

  • Golbeck J, Robles C, Edmondson M, Turner K (2011) Predicting personality from twitter. In: 2011 IEEE third international conference on privacy, security, risk and trust and 2011 IEEE third international conference on social computing

    Google Scholar 

  • Golbeck J, Robles C, Turner K (2011) Predicting personality with social media. In: CHI ’11 extended abstracts on human factors in computing systems, CHI EA ’11

    Google Scholar 

  • Greene S, Thapliyal H, Caban-Holt A (2016a) A survey of affective computing for stress detection. IEEE Consum Electron Mag 5(4):44–56

    Article  Google Scholar 

  • Greene S, Thapliyal H, Caban-Holt A (2016b) A survey of affective computing for stress detection: evaluating technologies in stress detection for better health. IEEE Consum Electron Mag 5(4):44–56

    Article  Google Scholar 

  • Griffin HJ, Aung MS, Romera-Paredes B, McLoughlin C, McKeown G,  Curran W, Bianchi-Berthouze N (2013) Laughter type recognition from whole body motion. In: Humane association’s conference on affective computing and intelligent interaction

    Google Scholar 

  • Jones M, Viola P (2003) Fast multi-view face detection. Mitsubishi Elec. Research Lab, Technical Report, TR2003-96

    Google Scholar 

  • Kaptein M, Markopoulos P, de Ruyter B, Aarts E (2010) Persuasion in ambient intelligence. J Ambient Intell Hum Comput 1(1):43–56

    Article  Google Scholar 

  • Kipp M, Martin J-C (2008) Gesture and emotion: can basic gestural form features discriminate emotions? In: IEEE conference on affective computing and intelligent interaction

    Google Scholar 

  • Kumar VDA, Subramanian M, Gopalakrishnan G, Vengatesan K, Elangovan D, Chitra B (2019) Implementation of the pulse rhythmic rate for the efficient diagnosing of the heartbeat. Healthcare Technol Lett 6(2):48–52

    Article  Google Scholar 

  • Mairesse F, Walker MA, Mehl M, Moore R (2007) Using linguistic cues for the automatic recognition of personality in conversation and text. J Artif Intell Res 30(1):457–500

    Article  Google Scholar 

  • Makris P, Skoutas DN, Skianis C (2013) A survey on context-aware mobile and wireless networking: on networking and computing environments’ integration. IEEE Commun Surv Tutor 15(1):362–386

    Article  Google Scholar 

  • Mao X, Chen L, Fu L (2009) Multi-level speech emotion recognition based on hmm and ann. In: Proceedings of of world congress on computer science and information engineering

    Google Scholar 

  • McCrae R, Costa P (1996) The five factor model of personality: theoretical perspective. The Guilford Press

    Google Scholar 

  • Noroozi F, Corneanu C, Kaminska D, Sapinski T, Escalera S, Anbarjafari G (2018) Survey on emotional body gesture recognition. IEEE Trans Affect Comput

    Google Scholar 

  • Olguin Olguin D,   Gloor P, Pentland A (2009) Capturing individual and group behavior with wearable sensors. In: AAAI spring symposium - Technical Report, pp. 68–74

    Google Scholar 

  • Papandreou G, Zhu T, Kanazawa N, Toshev A, Tompson J, Bregler C, Murphy K (2017) Towards accurate multi-person pose estimation in the wild. Comput Vis Pattern Recognit 3(4):6

    Google Scholar 

  • Pease A, Pease B (2004) The Definitive Book of Body Language. In: Peace international

    Google Scholar 

  • Perera C, Zaslavsky A, Christen P, Georgakopoulos D (2014) Context aware computing for the internet of things: a survey. IEEE Commun Surv Tutor 16(1):414–454

    Article  Google Scholar 

  • Rashidi P, Cook DJ, Holder LB, Schmitter-Edgecombe M (2011) Discovering activities to recognize and track in a smart environment. IEEE Trans Knowl Data Eng 23(4):527–539

    Article  Google Scholar 

  • Russel J, Mehrabian A (1977) Evidence for a three-factor theory of emotions. J Res Personal 11:273–294

    Article  Google Scholar 

  • Senecal S, Cuel L, Aristidou A, Magnenat-Thalmann N (2016) Continuous body emotion recognition system during theater performances. Comput Animat Virtual Worlds 27(3):311–320

    Article  Google Scholar 

  • Sirohey S (1998) Human face segmentation and identification. Technical Report

    Google Scholar 

  • Soylemez O,  Ergen B, Soylemez N (2017) A 3d facial expression recognition system based on svm classifier using distance based features. In: IEEE conference on signal processing and communications applications (SIU)

    Google Scholar 

  • Staiano J, Lepri B, Aharony N, Pianesi F, Sebe N, Pentland A (2012) Friends don’t lie: Inferring personality traits from social network structure. In: Proceedings of the 2012 ACM conference on ubiquitous computing, UbiComp ’12, pp 321–330

    Google Scholar 

  • Steele F, Evans DC, Green RK (2009) Is your profile picture worth 1000 words? photo characteristics associated with personality impression agreement

    Google Scholar 

  • Tam G, Cheng Z-Q, Lai Y-K, Langbein F, Liu Y, Marshall D, Martin R, Sun X-F, Rosin P (2013) Registration of 3d point clouds and meshes: a survey from rigid to nonrigid. IEEE Trans Vis Comput Graph 19(7):1199–1217

    Article  Google Scholar 

  • Tomkins S (2008) Affect, Imagery consciousness. Springer Publications, Berlin

    Google Scholar 

  • Tompson JJ, Jain A, LeCun Y, Bregler C (2014) Joint training of a convolutional network and a graphical model for human pose estimation. In: Advances in neural information processing systems

    Google Scholar 

  • Trujillo L, Olague G, Hammoud R, Hernandez B (2005) Automatic feature localization in thermal images for facial expression recognition. In: IEEE conference on computer vision and pattern recognition

    Google Scholar 

  • Vinciarelli A, Mohammadi G (2014) A survey of personality computing. IEEE Trans Affect Comput 5(3):273–291

    Article  Google Scholar 

  • Vu HA, Yamazaki Y,  Dong F, Hirota K (2011) Emotion recognition based on human gesture and speech information using rt middleware. In: IEEE conference on fuzzy systems (FUZZ)

    Google Scholar 

  • Wang S, He M, Gao Z, He S, Ji Q (2014) Emotion recognition from thermal infrared images using deep boltzmann machine. ACM J Front Comput Sci 8(4):609–618

    Article  MathSciNet  Google Scholar 

  • Wang N, Gao X, Tao D, Yang H, Li X (2018) Facial feature point detection: a comprehensive survey. J Neurocomput 275:50–65

    Article  Google Scholar 

  • Wang S, Pan B, Chen H, Ji Q (2018) Thermal augmented expression recognition. IEEE Trans Cybern 48(7):2203–2214

    Article  Google Scholar 

  • Wu C-H, Liang W-B (2011) Emotion recognition of affective speech based on multiple classifiers using acoustic-prosodic information and semantic labels. IEEE Trans Affect Comput 2(1):10–21

    Article  Google Scholar 

  • Yang C,  Ji L, Liu G (2009) Study to speech emotion recognition based on twinssvm. In: Proceedings of 5th international conference on natural computation

    Google Scholar 

  • Yoshitomi Y, Asada T, Shimada K, Tabuse M (2010) Facial expression recognition for speaker using thermal image processing and speech recognition system. In: International conference on applied computer science

    Google Scholar 

  • Zeng Z, Pantic M, Roisman G, Huang T (2009) A survey of affect recognition methods: audio, visual, and spontaneous expressions. IEEE Trans Pattern Anal Mach Intell 31(1):39–58

    Article  Google Scholar 

  • Zen G, Lepri B,  Ricci E, Lanz O (2010) Space speaks: Towards socially and personality aware visual surveillance. In: Proceedings of the 1st ACM international workshop on multimodal pervasive video analysis, MPVA ’10, pp 37–42

    Google Scholar 

  • Zhang CC, Zhang Z (2010) A survey of recent advances in face detection. Microsoft Research, Technical Report, MSR-TR-2010-66

    Google Scholar 

  • Zhen Q, Huang D, Wang Y, Chen L (2016) Muscular movement model-based automatic 3d/4d facial expression recognition. IEEE Trans Multimed 18(7):1438–1450

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Amr El Mougy .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

El Mougy, A. (2020). Character-IoT (CIoT): Toward Human-Centered Ubiquitous Computing. In: El Bolock, A., Abdelrahman, Y., Abdennadher, S. (eds) Character Computing. Human–Computer Interaction Series. Springer, Cham. https://doi.org/10.1007/978-3-030-15954-2_7

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-15954-2_7

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-15953-5

  • Online ISBN: 978-3-030-15954-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics