Abstract
Assisted living has a particular social importance in most developed societies, due to the increased life expectancy of the general population and the ensuing ageing problems. It has also importance for the provision of improved home care in cases of disabled persons or persons suffering from certain diseases that have high social impact. This paper is primarily focused on the description of the human centered interface specifications, research and implementations for systems geared towards the well-being of aged people. Two tasks will be investigated in more detail: a) nutrition support to prevent undernourishment/malnutrition and dehydration, and b) affective interfaces that can help assessing the emotional status of the elderly. Such interfaces can be supported by ambient intelligence and robotic technologies.
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
Belhumeur, P.N., Hespanha, J.P., Kriegman, D.J.: Eigenfaces vs. fisherfaces: Recognition using class specific linear projection. IEEE Transactions on Pattern Analysis and Machine Intelligence 19(7), 711–720 (1997)
Chen, X.W., Huang, T.S.: Facial expression recognition: A clustering-based approach. Pattern Recognition Letters 24(9-10), 1295–1302 (2003)
Gkalelis, N., Tefas, A., Pitas, I.: Combining fuzzy vector quantization with linear discriminant analysis for continuous human movement recognition. IEEE Transactions on Circuits and Systems for Video Technology 18(11), 1511–1521 (2008)
Jolliffe, I.: Principal Component Analysis. Springer, New York (1986)
Kotsia, I., Zafeiriou, S., Pitas, I.: A novel discriminant non-negative matrix factorization algorithm with applications to facial image characterization problems. IEEE Transactions on Information Forensics and Security 2(3-2), 588–595 (2007)
Kyperountas, M., Tefas, A., Pitas, I.: Salient feature and reliable classifier selection for facial expression classification. Pattern Recognition 43(3), 972–986 (2010)
Lee, D.D., Seung, H.S.: Learning the parts of objects by non-negative matrix factorization. Nature 401, 788–791 (1999)
Maronidis, A., Bolis, D., Tefas, A., Pitas, I.: Improving Subspace Learning for Facial Expression Recognition Using Person Dependent and Geometrically Enriched Training Sets. Neural Networks (2011) (accepted for publication)
Maronidis, A., Tefas, A., Pitas, I.: Frontal view recognition using spectral clustering and subspace learning methods. In: Diamantaras, K., Duch, W., Iliadis, L.S. (eds.) ICANN 2010. LNCS, vol. 6352, pp. 460–469. Springer, Heidelberg (2010)
Mehrabian, A.: Communication without words. Psychology Today 2(4), 53–56 (1968)
Pantic, M., Rothkrantz, L.J.M.: Automatic analysis of facial expressions: The state of the art. IEEE Transactions on Pattern Analysis and Machine Intelligence 22(12), 1424–1445 (2000)
Pantic, M., Rothkrantz, L.J.M.: Toward an affect-sensitive multimodal human-computer interaction. Proceedings of the IEEE 91(9), 1370–1390 (2003)
Viola, P., Jones, M.: Rapid object detection using a boosted cascade of simple features. In: Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 1, pp. 511–518 (2001)
Zafeiriou, S., Tefas, A., Buciu, I., Pitas, I.: Exploiting discriminant information in non negative matrix factorization with application to frontal face verification. IEEE Transactions on Neural Networks 17(3), 683–695 (2006)
Zeng, Z., Pantic, M., Roisman, G.I., Huang, T.S.: A survey of affect recognition methods: Audio, visual, and spontaneous expressions. IEEE Transactions on Pattern Analysis and Machine Intelligence 31(1), 39–58 (2009)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Tefas, A., Pitas, I. (2011). Human Centered Interfaces for Assisted Living. In: Czachórski, T., Kozielski, S., Stańczyk, U. (eds) Man-Machine Interactions 2. Advances in Intelligent and Soft Computing, vol 103. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23169-8_1
Download citation
DOI: https://doi.org/10.1007/978-3-642-23169-8_1
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23168-1
Online ISBN: 978-3-642-23169-8
eBook Packages: EngineeringEngineering (R0)