Abstract
We present an abstract framework for ‘smart indoor environments’ that are monitored unobtrusively by biometrics capture devices, such as video cameras, microphones, etc. Our interest is in developing smart environments that keep track of their occupants and are capable of answering questions about the whereabouts of the occupants. We abstract the smart environment by a state transition system: Each state records a set of individuals who are present in various zones of the environment. Since biometric recognition is inexact, state information is probabilistic in nature. An event abstracts a biometric recognition step, and the transition function abstracts the reasoning necessary to effect state transitions. In this manner, we are able to accommodate different types of biometric sensors and also different criteria for state transitions. We define the notions of ‘precision’ and ‘recall’ of a smart environment in terms of how well it is capable of identifying occupants. We have developed a prototype smart environment based upon our proposed concepts, and provide experimental results in this paper. Our conclusion is that the state transition model is an effective abstraction of a smart environment and serves as a basis for integrating various recognition and reasoning capabilities.
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
Weiser, M.: The Computer for the 21st Century. Scientific American 265(3), 66–75 (1991)
Satyanarayanan, M.: Pervasive Computing: Vision and Challenges. IEEE Personal Communications 8(4), 10–17 (2001)
Pentland, A., Choudhury, T.: Face Recognition for Smart Environments. IEEE Computer 33(2), 50–55 (2000)
Cao, H., Govindaraju, V.: Vector Model Based Indexing and Retrieval of Handwritten Medical Forms. In: Proc. of the Ninth International Conference on Document Analysis and Recognition (ICDAR 2007), pp. 88–92. IEEE Computer Society, Washington (2007)
Bouchaffra, D., Govindaraju, V., Srihari, S.: A Methodology for Mapping Scores to Probabilities. IEEE Transactions on Pattern Analysis and Machine Intelligence 21(9), 923–927 (1999)
van Rijsbergen, C.J.: Information Retrieval. Butterworths, Boston (1979)
Cook, D., Das, S.: How smart are our environments? An updated look at the state of the art. Pervasive and Mobile Computing 3(2), 53–73 (2007)
Youngblood, M., Cook, D.J., Holder, L.B.: Managing adaptive versatile environments. In: Proc. of the Third IEEE Intl. Conf. on Pervasive Computing and Communications, pp. 351–360. IEEE Computer Society, Washington (2005)
Lesser, V., et al.: The Intelligent Home Testbed. In: Proc. of the Autonomous Agents 1999 Workshop on Autonomy Control Software. ACM, New York (1999)
House n Living Laboratory Introduction (2006)
Hightower, J., Borriello, G.: Location Systems for Ubiquitous Computing. IEEE Computer 34(8), 57–66 (2001)
Manesis, T., Avouris, N.: Survey of position location techniques in mobile systems. In: Proc. of the Seventh Intl. Conf. on Human Computer interaction with Mobile Devices and Services. MobileHCI 2005, pp. 291–294. ACM, New York (2005)
Fox, D., Hightower, J., Liao, L., Schulz, D., Borriello, G.: Bayesian filtering for location estimation. IEEE Pervasive Computing 2(3), 24–33 (2003)
Bar-Shalom, Y., Li, X.-R.: Multitarget-Multisensor Tracking: Principles and Techniques, Yaakov Bar-Shalom (1995)
Bui, H.H., Venkatesh, S., West, G.: Tracking and surveillance in wide-area spatial environments using the Abstract Hidden Markov Model. Intl. Journal of Pattern Recognition and Artificial Intelligence 15(1), 177–195 (2002)
Roy, A., Bhaumik, S., Bhattacharya, A., Basu, K., Cook, D.J., Das, S.K.: Location aware resource management in smart homes. In: Proc. of the First IEEE Intl. Conf. on Pervasive Computing and Communications, pp. 481–488. IEEE Computer Society, Washington (2003)
Das, S.K., Roy, N., Roy, A.: Context-aware resource management in multi-inhabitant smart homes: A framework based on Nash H-learning. Pervasive and Mobile Computing 2(4), 372–404 (2006)
Schulz, D., Fox, D., Hightower, J.: People tracking with anonymous and id-sensors using Rao-Blackwellised particle filters. In: Proc. of the 18th Intl. Joint Conference on Artificial Intelligence (IJCAI), pp. 921–926 (2003)
Krumm, J., Harris, S., Meyers, B., Brumitt, B., Hale, M., Shafer, S.: Multi-Camera Multi-Person Tracking for EasyLiving. In: Proc. of the 3rd IEEE Intl. Workshop on Visual Surveillance (VS 2000). IEEE Computer Society, Washington (2000)
Brumitt, B., Meyers, B., Krumm, J., Kern, A., Shafer, S.A.: EasyLiving: Technologies for Intelligent Environments. In: Thomas, P., Gellersen, H.-W. (eds.) HUC 2000. LNCS, vol. 1927, pp. 12–29. Springer, Heidelberg (2000)
Chen, D., Gellersen, H.: Recognition and reasoning in an awareness support system for generation of storyboard-like views of recent activity. In: Proc. of the Intl. ACM SIGGROUP Conference on Supporting Group Work. GROUP 1999. ACM Press, New York (1999)
Aghajan, H., et al.: Distributed Vision-Based Accident Management for Assisted Living. In: Okadome, T., Yamazaki, T., Makhtari, M. (eds.) ICOST. LNCS, vol. 4541, pp. 196–205. Springer, Heidelberg (2007)
Gao, Y., Hui, S.C., Fong, A.C.: A Multi-View Facial Analysis Technique for Identity Authentication. IEEE Pervasive Computing 2(1), 38–45 (2003)
Hong, K., et al.: Real Time Face Detection and Recognition System Using Haar-Like Feature/HMM in Ubiquitous Network Environments. In: Gervasi, O., Gavrilova, M.L., Kumar, V., Laganá, A., Lee, H.P., Mun, Y., Taniar, D., Tan, C.J.K. (eds.) ICCSA 2005. LNCS, vol. 3480, pp. 1154–1161. Springer, Heidelberg (2005)
Zhang, S., et al.: Continuous Verification Using Multimodal Biometrics. In: Zhang, D., Jain, A.K. (eds.) ICB 2005. LNCS, vol. 3832, pp. 562–570. Springer, Heidelberg (2005)
Hazen, T., Weinstein, E., Heisele, B., Park, A., Ming, J.: Multi-Modal Face and Speaker Identification for Mobile Devices. In: Hammoud, R.I., Abidi, B.R., Abidi, M.A. (eds.) Face Biometrics for Personal Identification: Multi-Sensory Multi-Modal Systems, pp. 123–138. Springer, Heidelberg (2006)
Bohn, J., Coroama, V., Langheinrich, M., Mattern, F., Rohs, M.: Social, Economic, and Ethical Implications of Ambient Intelligence and Ubiquitous Computing. In: Weber, W., Rabaey, J., Aarts, E. (eds.) Ambient Intelligence, pp. 5–29. Springer, Heidelberg (2005)
Vildjiounaite, E., et al.: Unobtrusive Multimodal Biometrics for Ensuring Privacy and Information security with Personal Devices. In: Fishkin, K.P., Schiele, B., Nixon, P., Quigley, A. (eds.) PERVASIVE 2006. LNCS, vol. 3968, pp. 186–201. Springer, Heidelberg (2006)
Bernardin, K., Stiefelhagen, R.: Audio-visual multi-person tracking and identification for smart environments. In: Proc. of the 15th International Conference on Multimedia, pp. 661–670. ACM, New York (2007)
Hewitt, R., Belongie, S.: Active Learning in Face Recognition: Using Tracking to Build a Face Model. In: Proc. of the 2006 Computer Vision and Pattern Recognition Workshop, pp. 157–157. IEEE Computer Society, Washington (2006)
OpenCV, http://www.intel.com/technology/computing/opencv/index.htm
Turk, M., Pentland, A.: Eigenfaces for Recognition. J. Cognitive Neuroscience 3(1), 71–86 (1991)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Menon, V., Jayaraman, B., Govindaraju, V. (2008). Biometrics Driven Smart Environments: Abstract Framework and Evaluation. In: Sandnes, F.E., Zhang, Y., Rong, C., Yang, L.T., Ma, J. (eds) Ubiquitous Intelligence and Computing. UIC 2008. Lecture Notes in Computer Science, vol 5061. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69293-5_8
Download citation
DOI: https://doi.org/10.1007/978-3-540-69293-5_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-69292-8
Online ISBN: 978-3-540-69293-5
eBook Packages: Computer ScienceComputer Science (R0)