Skip to main content

Semantically Enhancing Multimedia Lifelog Events

  • Conference paper
Advances in Multimedia Information Processing – PCM 2014 (PCM 2014)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8879))

Included in the following conference series:

Abstract

Lifelogging is the digital recording of our everyday behaviour in order to identify human activities and build applications that support daily life. Lifelogs represent a unique form of personal multimedia content in that they are temporal, synchronised, multi-modal and composed of multiple media. Analysing lifelogs with a view to supporting content-based access, presents many challenges. These include the integration of heterogeneous input streams from different sensors, structuring a lifelog into events, representing events, and interpreting and understanding lifelogs. In this paper we demonstrate the potential of semantic web technologies for analysing lifelogs by automatically augmenting descriptions of lifelog events. We report on experiments and demonstrate how our results yield rich descriptions of multi-modal, multimedia lifelog content, opening up even greater possibilities for managing and using lifelogs.

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 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
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. Gurrin, G., Smeaton, A.F., Doherty, A.R.: Lifelogging: Personal Big Data. Foundations and Trends in Information Retrieval 8(1), 1–125 (2014)

    Article  Google Scholar 

  2. Doherty, A.R., Pauly-Takacs, K., Caprani, N., et al.: Experiences of Aiding Autobiographical Memory Using the SenseCam. HCI 27(1-2), 151–174 (2012)

    Google Scholar 

  3. Doherty, A.R., Smeaton, A.F.: Automatically segmenting lifelog data into events. In: WIAMIS 2008, pp. 20–23. IEEE Computer Society, Washington, DC (2008)

    Google Scholar 

  4. Beckett, D.: Turtle-Terse RDF triple language. W3C Technical Report (2007)

    Google Scholar 

  5. Silva, A.R., Pinho, S., Macedo, L.M., Moulin, C.J.: Benefits of SenseCam Review on Neuropsychological Test Performance. AJPM 44(3), 302–307 (2013)

    Google Scholar 

  6. O’Loughlin, G., Cullen, S.J., McGoldrick, A., et al.: Using a wearable camera to increase the accuracy of dietary analysis. AJPM 44(3), 297–301 (2013)

    Google Scholar 

  7. Wang, P., Smeaton, A.F.: Using visual lifelogs to automatically characterise everyday activities. Information Sciences 230, 147–161 (2013)

    Article  Google Scholar 

  8. Doherty, A., Smeaton, A.F.: Automatically augmenting lifelog events using pervasively generated content from millions of people. Sensors 10(3), 1423–1446 (2010)

    Article  Google Scholar 

  9. Dobbins, C., Merabti, M., Fergus, P., et al.: Exploiting linked data to create rich human digital memories. Computer Communications (2013)

    Google Scholar 

  10. Ashbrook, D., Starner, T.: Using GPS to learn significant locations and predict movement across multiple users. Personal UbiCom 7(5), 275–286 (2003)

    Google Scholar 

  11. Rodden, K.: How do people organise their photographs? In: Proceedings of the BCS IRSG Colloquium (1999)

    Google Scholar 

  12. Platt, J.C.: AutoAlbum: Clustering digital photographs using probabilistic model merging. In: CBAIVL 2000, pp. 96–100. IEEE Computer Society (2000)

    Google Scholar 

  13. Little, S., Jargalsaikhan, I., Clawson, K., et al.: Interactive Surveillance Event Detection at TRECVid2012. In: ICMR 2013, pp. 301–302 (2013)

    Google Scholar 

  14. Reuter, T., Papadopoulos, S., Petkos, G., et al.: Social Event Detection at MediaEval 2013: Challenges, Datasets, and Evaluation. In: MediaEval Workshop (2013)

    Google Scholar 

  15. Lu, Z., Grauman, K.: Story-Driven Summarization for Egocentric Video. In: CVPR, Portland, OR, USA, pp. 2714–2721 (2013)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Wang, P., Smeaton, A., Mileo, A. (2014). Semantically Enhancing Multimedia Lifelog Events. In: Ooi, W.T., Snoek, C.G.M., Tan, H.K., Ho, CK., Huet, B., Ngo, CW. (eds) Advances in Multimedia Information Processing – PCM 2014. PCM 2014. Lecture Notes in Computer Science, vol 8879. Springer, Cham. https://doi.org/10.1007/978-3-319-13168-9_17

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-13168-9_17

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-13167-2

  • Online ISBN: 978-3-319-13168-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics