Skip to main content
SpringerLink
Log in

Analysis of Nursery School Observations for Understanding Children’s Behavior

  • Conference paper
Health Information Science (HIS 2012)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7231))

Included in the following conference series:

  • 1101 Accesses

Abstract

This paper introduces an on-going project with the goal of measuring and analyzing children’s behavior automatically. Some key technologies, including methodologies for acquiring data, tracking a target across different cameras over time, activity recognition, interaction analysis, and behavior summarization for a target child are presented. Some encouraging results from a real system we developed in a nursery school environment are also described. As these technologies enable the content-based retrieval, comparison, and summarization of large-scale observational data, they are applicable to various purposes, such as the assessment of children’s development, healthcare and diagnosis.

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 54.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 69.99
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

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Charman, T., Baird, G.: Practitioner Review: Diagnosis of Autism Spectrum Disorder in 2- and 3-year-old Children. Journal of Child Psychology and Psychiatry 43(3), 289–305 (2002)

    Article  Google Scholar 

  2. Ishikawa, T., Wang, Y., Kato, J.: Daily Digest Generation of Kindergartner from Surveillance Video. IEEJ Transactions on Electronics, Information and Systems 131(2), 385–392 (2011) (in Japanese)

    Article  Google Scholar 

  3. Kato, J., Ishikawa, T., Wang, Y., Ishii, K.: Video Digest Generation with Multisensor for Nursery School Kids. ICIC Express Letters 5(6), 1921–1927 (2011)

    Google Scholar 

  4. Weinberger, K.Q., Saul, K.: Distance Metric Learning for Large Margin Nearest Neighbour Classification. Journal of Machine Learning Research 10, 207–244 (2009)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Dept. of Systems and Social Informatics Graduate School of Information Science, Nagoya University, Nagoya, Japan

    Jien Kato & Yu Wang

Authors
  1. Jien Kato
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yu Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Victoria University, Melbourne, Australia

    Jing He

  2. School of Information Systems, Computing and Mathematics, Centre for Intelligent Data Analysis, Brunel University, St. John’s 103, UB8 3PH, London, UK

    Xiaohui Liu

  3. Departments of Radiology and Psychology, The University of Arizona, 1609 N. Campbell Avenue, 85724, Tucson, AZ, USA

    Elizabeth A. Krupinski

  4. Faculty of Health, Engineering and Science, School of Engineering and Science, Centre for Applied Informatics, Victoria University, Ballarat Road, Footscray, 8001, Melbourne City, VIC, Australia

    Guandong Xu

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Kato, J., Wang, Y. (2012). Analysis of Nursery School Observations for Understanding Children’s Behavior. In: He, J., Liu, X., Krupinski, E.A., Xu, G. (eds) Health Information Science. HIS 2012. Lecture Notes in Computer Science, vol 7231. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29361-0_18

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-29361-0_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-29360-3

  • Online ISBN: 978-3-642-29361-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation