Abstract
In this paper, we introduce and evaluate a novel approach, namely the use of the cross correlation matrix and Maximum Overlap Discrete Wavelet Transform (MODWT) to analyse SenseCam lifelog data streams. SenseCam is a device that can automatically record images and other data from the wearer’s whole day. It is a significant challenge to deconstruct a sizeable collection of images into meaningful events for users. The cross-correlation matrix was used, to characterise dynamical changes in non-stationary multivariate SenseCam images. MODWT was then applied to equal-time Correlation Matrices over different time scales and used to explore the granularity of the largest Eigenvalue and changes, in the ratio of the sub-dominant Eigenvalue spectrum dynamics, over sliding time windows. By examination of the eigenspectrum, we show that these approaches can identify “Distinct Significant Events” for the wearers. The dynamics of the Eigenvalue spectrum across multiple scales provide useful insight on details of major events in SenseCam logged images.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Hodges, S., Williams, L., Berry, E., Izadi, S., Srinivasan, J., Butler, A., Smyth, G., Kapur, N., Wood, K.: SenseCam: A Retrospective Memory Aid. In: Dourish, P., Friday, A. (eds.) UbiComp 2006. LNCS, vol. 4206, pp. 177–193. Springer, Heidelberg (2006)
Harper, R., Randall, D., Smyth, N., Evans, C., Heledd, L., Moore, R.: Thanks for the Memory. In: Proceedings of the 21st BCS HCI Group Conference, HCI 2007, Lancaster, U.K. (2007)
Harper, R., Randall, D., Smyth, N., Evans, C., Heledd, L., Moore, R.: The Past is a Different Place: They Do Things Differently There. In: Designing Interactive Systems, Cape Town, South Africa, pp. 271–280 (2008)
Ashbrook, D., Lyons, K., Clawson, J.: Capturing Experiences Anytime, Anywhere. IEEE Pervasive Computing (2006)
Bell, G., Gemmell, J.: A Digital Life. Scientific American (2007)
Lee, M.L., Dey, A.K.: Providing good memory cues for people with episodic memory impairment. In: Assets 2007: Proceedings of the 9th International ACM SIGACCESS Conference on Computers and Accessibility, Tempe, Arizona, USA, pp. 131–138 (2007)
Lin, W.H., Hauptmann, A.: Structuring Continuous Video Recordings of Everyday Life Using Time-Constrained Clustering. In: Multimedia Content Analysis, Management and Retieval SPIE-IST Electronic Imaging, vol. 6073, San Jose, California, USA, pp. 111–119 (2006)
Doherty, A.R., Smeaton, A.F.: Automatically Segmenting Lifelog Data into Events. In: Proc. WIAMIS 2008, pp. 20–23 (2008)
Laloux, L., Cizeau, P., Bouchaud, J.-P., Potters, M.: Noise dressing of financial correlation matrices. Phys. Rev. Lett. 83(7), 1467–1470 (1999)
Plerou, V., Gopikrishnan, P., Rosenow, B., Nunes Amaral, L.A., Stanley, H.E.: Universal and non-uiversal properties of cross-correlations in financial time series. Phys. Rev. Lett. 83(7), 1471–1474 (1999)
Laloux, L., Cizeau, P., Bouchaud, J.-P., Potters, M.: Random matrix theory and financial correlations. Int. J. Theoret. Appl. Finance 3(3), 391–397 (2000)
Plerou, V., Gopikrishnan, P., Rosenow, B., Nunes Amaral, L.A., Guhr, T., Stanley, H.E.: A random matrix approach to cross-correlations in financial data. Phys. Rev. E 65, 066126/1–066126/18 (2000)
Gopikrishnan, P., Rosenow, B., Plerou, V., Eugene Stanley, H.: Indentifying business sectors from stock price fluctuations. Phys. Rev. E 64, 035106R/1–035106R/4 (2001)
Utsugi, A., Ino, K., Oshikawa, M.: Random matrix theory analysis of cross-correlations in financial markets. Phys. Rev. E 70, 026110/1–026110/17 (2004)
Bouchaud, J.P., Oshikawa, M.: Theory of Financial Risk and Derivative Pricing. Cambridge University Press (2003)
Wilcox, D., Gebbie, T.: On the analysis of cross-correlations in South African market data. Physica A 344(1-2), 294–298 (2004)
Sharifi, S., Crane, M., Shamie, A., Ruskin, H.J.: Random matrix theory for portfolio optimization: A stability approach. Physica A 335(3-4), 629–643 (2004)
Conlon, T., Ruskin, H.J., Crane, M.: Random matrix theory and fund of funds portfolio optimisation. Physica A 382(2), 565–576 (2007)
Conlon, T., Ruskin, H.J., Crane, M.: Wavelet multiscale analysis for Hedge Funds: Scaling and Strategies. Physica A, 5197–5204 (2008)
Podobnik, B., Stanley, H.E.: Detrended cross-correlation analysis: A new method for analysing two non-stationary time series. Phys. Rev. Lett. 100(8), 084102/1–084102/11 (2008)
Schindler, K., Leung, H., Elger, C.E., Lehnertz, K.: Assessing seizure dynamics by analysing the correlation structure of multichannel intracranial EEG. Brain 130, 65–77 (2007)
Schindler, K., Elger, C.E., Lehnertz, K.: Increasing synchronization promote seizure termination: Evidence from status epilepticus. Clin. Neurophysiol. 118(9), 1955–1968 (2007)
Kwapien, J., Drozda, S., Ionannides, A.A.: Temporal correlations versus noise in the correlation matrix formalism: An example of the brain auditory response. Phys. Rev. E 62, 5557–5564 (2000)
Li, N., Crane, M., Ruskin, H.J.: Automatically detecting significant events on sensecam. ERCIM News (87) (2011)
Peng, C.-K., Buldyrev, S.V., Havlin, S., Simons, M., Stanley, H.E., Golderberger, A.L.: On the mosaic organization of DNA sequences. Phys. Rev. E 49, 1685–1689 (1994)
Matos, J.A.O., Gama, S.M.A., Ruskin, H.J., Sharkasi, A.A., Crane, M.: An econophysics approach to the Portuguese Stock Index-PSI-20. Physica A 342, 665–676 (2004)
Buldyrev, S.V., Goldberger, A.L., Havlin, S., Mantegna, R.N., Matsa, M.E., Peng, C.-K., Simons, M., Stanley, H.E.: Long-range correlation properties of coding and noncoding DNA sequences: GenBank analysis. Phys. Rev. E 51, 5084–5091 (1995)
Heneghan, C., McDarby, G.: Establishing the relation between detrended fluctuation analysis and power spectral density analysis for stochastic processes. Phys. Rev. E 62, 6103–6110 (2000)
Percival, D.B., Walden, A.T.: Wavelet methods for time series analysis. Cambridge University Press (2000)
Sharkasi, A., Crane, M., Ruskin, H.J., Matos, J.A.: The reaction of stock markets to crashes and events: A comparison study between emerging and mature markets using wavelet transforms. Physica A 368, 511–521 (2006)
Burrus, C.S., Gopinath, R.A., Gao, H.: Introduction to wavelets and wavelets transforms. Prentice Hall (1997)
Misra, H., Hopfgartner, F., Goyal, A., Punitha, P., Jose, J.M.: TV News Story Segmentation Based on Semantic Coherence and Content Similarity. In: Boll, S., Tian, Q., Zhang, L., Zhang, Z., Chen, Y.-P.P. (eds.) MMM 2010. LNCS, vol. 5916, pp. 347–357. Springer, Heidelberg (2010)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Li, N., Crane, M., Ruskin, H.J., Gurrin, C. (2013). Multiscaled Cross-Correlation Dynamics on SenseCam Lifelogged Images. In: Li, S., et al. Advances in Multimedia Modeling. MMM 2013. Lecture Notes in Computer Science, vol 7732. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35725-1_45
Download citation
DOI: https://doi.org/10.1007/978-3-642-35725-1_45
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-35724-4
Online ISBN: 978-3-642-35725-1
eBook Packages: Computer ScienceComputer Science (R0)