Skip to main content
SpringerLink
Log in

Data Workflow for Extension Framework to Interpret and Transform Human Behavior

  • Conference paper
  • First Online:
Proceedings of SAI Intelligent Systems Conference (IntelliSys) 2016 (IntelliSys 2016)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 16))

Included in the following conference series:

  • 2687 Accesses

Abstract

In this paper, a framework to interpret human behavior is proposed. The framework consists of the data work flow along with the proposed datasets. Consideration of the multimodal aspects of technology, human sciences, and behavior sciences has been proposed. It is established fact by psychology that human nature is unpredictable and many times human behaves in contradictory and incompatible manner. Hence, Extenics the emerging discipline addressing contradictory incompatible issues and also transformation of human behavior as transformation is proposed along with interpretation. This paper proposes the dataflow, the framework and a format for collection of dataset for human behavior interpretation.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight 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

  1. Ekman. www.paulekman.com

  2. Bakker, I., van der Voordt, T., Vink, P., de Boon, J.: Pleasure, arousal, dominance: Mehrabian and Russell revisited (2014). http://link.springer.com/article/10.1007/s12144-014-9219-4

  3. Fogg: Proceedings of the 4th International Conference on Persuasive Technology, pp. 42–46. ACM (2009). http://bjfogg.com/fbg_files/page7_1.pdf, www.BehaviorGrid.org

  4. http://www.oralytics.com/2012/06/data-science-is-multidisciplinary.html

  5. http://i2.wp.com/sciencereview.berkeley.edu/wp-content/uploads/2014/04/spring_2014_azam_01.jpg

  6. http://i0.wp.com/sciencereview.berkeley.edu/wp-content/uploads/2014/04/spring_2014_azam_05.jpg

  7. Wang, L., Hu, W., Tan, T.: Recent developments in human motion analysis. Pattern Recogn. 36(3), 585–601 (2003)

    Article  Google Scholar 

  8. Moeslund, T., Hilton, A., Krüger, V.: A survey of advances in vision-based human motion capture and analysis. Comput. Vis. Image Underst. 104(2–3), 90–126 (2006)

    Article  Google Scholar 

  9. Poppe, R.: A survey on vision-based human action recognition. Image Vis. Comput. 28(6), 976–990 (2010)

    Article  Google Scholar 

  10. Ong, S., Ranganath, S.: Automatic sign language analysis: a survey and the future beyond lexical meaning. IEEE Trans. Pattern Anal. Mach. Intell. 27(6), 873–891 (2005)

    Article  Google Scholar 

  11. Salah, A., Sebe, N., Gevers, T.: Communication and automatic interpretation of affect from facial expressions. In: Gokcay, D., Yildirim, G. (eds.) Affective Computing and Interaction: Psychological, Cognitive and Neuroscientific Perspectives. IGI Global, Hershey (2010)

    Google Scholar 

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

    Article  Google Scholar 

  13. Vinciarelli, A., Pantic, M., Bourlard, H.: Social signal processing: survey of an emerging domain. Image Vis. Comput. 27(12), 1743–1759 (2009)

    Article  Google Scholar 

  14. Zahariadis, T., Daras, P., Bouwen, J., Niebert, N., Griffin, D., Alvarez, F., Camarillo, G.: Towards a content-centric internet. In: Towards the Future Internet - Emerging Trends from European Research, pp. 227–236. IOS Press (2010). ISBN 978-1-60750-539-6

    Google Scholar 

  15. Daras, P., Axenopoulos, A., Darlagiannis, V., Tzovaras, D., Le Bourdon, X., Joyeux, L., Verroust-Blondet, A., Croce, V., Steiner, T., Massari, A., Camurri, A., Morin, S., Mezaour, A.D., Sutton, L., Spiller, S.: Introducing a unified framework for content object description. Int. J. Multimed. Intell. Secur. 2(3–4), 351–375 (2010). http://www.cs.upc.edu/~tsteiner/papers/2010/rucod-specification-ijmis2010.pdf

  16. Croce, V.: STAR 2013, Lausanne, 18–19 January 2013. http://vcl.iti.gr/is/UC/RUCoD.pdf

  17. Pei-xu, W., Jian-qun, L.: Solution to creating multi-function product based on extension design methods. J. Guangdong Univ. Technol. (3), 10–17 (2015)

    Google Scholar 

  18. Zhi-wei, Y., Xing-sen, L.: Modeling of basic-element and its application. J. Guangdong Univ. Technol. (3), 5–9 (2015)

    Google Scholar 

  19. Yongwei, Y., Shedong, R., Lianqiang, Y., Shenhao, G., Zhiqin, Q.: Fault diagnosis for automobile coating equipments based on extension neural network. J. Syst. Simul. (3), 542–548 (2015)

    Google Scholar 

  20. Liang-wei, L., Chun-yan, Y.: Study on ceramic logistics packaging design based on gene extension modular design. J. Guangdong Univ. Technol. (2), 11–16 (2015)

    Google Scholar 

  21. Li, Z., Gao, F.: Extension model modeling for Oracle bone inscriptions based on HowNet. Comput. Mod. (5), 30–34 (2015)

    Google Scholar 

  22. Chen, G., Yu, Z., Zhou, P.: Application of improved matter-element extension model to goaf safety evaluation. Jiangxi Nonferrous Met. (4), 91–96 (2015)

    Google Scholar 

  23. Li, W., Xiao, H., Ning, X., Zuo, X., Chen, Z.: Application of extension theory to large span tunnel collapse risk evaluation. J. Nat. Disasters, (3), 97–103 (2015). School of Civil Engineering and Machanics, Central South University of Forestry and Technology

    Google Scholar 

  24. Xiao, H.: Research on the creative imitation innovation based on basic element. Oper. Res. Manag. Sci. (5), 264–269 (2015)

    Google Scholar 

  25. Yu, Z., Li, X.: Modeling of basic-element and its application. J. Guangdong Univ. Technol. (3), 5–9 (2015)

    Google Scholar 

  26. Lu, B., Wang, H., Zhou, H., Liang, Y., Mi, J.: Research on parking guidance system evaluation based on fuzzy matter element. J. Shandong Jiao tong Univ. (2), 21–26 (2014). School of Transportation, Lanzhou Jiao tong University, School of Transportation and logistics, Southwest Jiao tong University

    Google Scholar 

  27. Sun, X.: Extension model of command decision. Ship Electron. Eng. (2), 37–40 (2015)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Sarvepalli Radhakrishnan University, Hoshangabad Road, Misrod, Bhopal, India

    Ravi Limaye

  2. Sagar Institute of Research and Technology, Ayodhya Bypass Road, Bhopal, 462 041, India

    Akhilesh R. Upadhyay

Authors
  1. Ravi Limaye
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Akhilesh R. Upadhyay
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Akhilesh R. Upadhyay .

Editor information

Editors and Affiliations

  1. Faculty of Computing and Engineering, School of Computing and Mathematics, University of Ulster at Jordanstown, Newtownabbey, United Kingdom

    Yaxin Bi

  2. The Science and Information (SAI) Organization, Bradford, West Yorkshire, United Kingdom

    Supriya Kapoor

  3. The Science and Information (SAI) Organization, Bradford, West Yorkshire, United Kingdom

    Rahul Bhatia

Appendix A

Appendix A

(Dataset Measurement Matrix)

  

Baseline

Expected

Observed

Subject

Baseline data

Historic data

Psychological test data

Personality test data

   
 

Posed data (face)

Posed data (gestures)

Posed data (voice)

Posed data (biometric)

   

Situation

Expectation levels data

(as per situation)

Competency test data

   

Other humans

Expectation levels data

(as per situation)

Competency test data posed data (face)

Posed data (gestures)

Posed data (voice)

posed data (biometric)

   

Objective

Spontaneous data (face)

Spontaneous data (gestures)

Spontaneous data (voice)

Spontaneous data (biometric)

   

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG

About this paper

Cite this paper

Limaye, R., Upadhyay, A.R. (2018). Data Workflow for Extension Framework to Interpret and Transform Human Behavior. In: Bi, Y., Kapoor, S., Bhatia, R. (eds) Proceedings of SAI Intelligent Systems Conference (IntelliSys) 2016. IntelliSys 2016. Lecture Notes in Networks and Systems, vol 16. Springer, Cham. https://doi.org/10.1007/978-3-319-56991-8_79

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-56991-8_79

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-56990-1

  • Online ISBN: 978-3-319-56991-8

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation