TRUE: a system for tracking, locating, and identifying users in intelligent environments

• Tales M. A. Porto UnB
• Danilo A. M. C. Ferreira UnB
• Fabricio N. Buzeto UnB
• Carla D. Castanho UnB
• Ricardo P. Jacobi UnB

Abstract

Context aware systems belongs to a class of computing systems that may dynamically adapt its behavior based on information sensed from the physical environment. To enable context awareness a variety of sensor devices that capture relevant data from the environment is deployed and integrated into the smart space, encapsulated by a middleware. This paper presents the TRUE System (Tracking and Recognizing Users in the Environment), a system that provides identification, location and tracking of users to applications through the middleware uOS. We show here as the solution was constructed and their experimental results.

References

Belhumeur, P. N., Hespanha, J. P., and Kriegman, D. J. (1996). Eigenfaces vs. fisherfaces: Recognition using class specific linear projection. European Conference on Computer Vision.

Bradski, G. (2000). The OpenCV Library. Dr. Dobb’s Journal of Software Tools.

Buzeto, F. N. (2010). Um conjunto de soluções para a construção de aplicativos de computação ubíqua. Master’s thesis, Departamento de Ciência da Computação, Universidade de Brasília, [link].

Buzeto, F. N., Filho, C. B., Castanho, C. D., and Jacobi, R. P. (2011). International Journal of Handheld Computing Research (IJHCR). International Journal of Handheld Computing Research (IJHCR), 2:47–64.

Hewitt, R. (2007). Face recognition with eigenface. SERVO Magazine.

Jain, R., Kasturi, R., and Schunck, B. G. (1995). Machine vision. McGraw-Hill, Inc., New York, NY, USA.

Kinect (2012). Kinect. [link].

Korting, T. and Filho, N. (2004). Utilizando eigenfaces para reconhecimento de imagens. In SIRC Simpósio de Informática da Região Centro do RS.

Ma, E. L. H. (2007). Avaliação de características haar em um modelo de detecção de face. Trabalho de Conclusão de Curso. Universidade de Brasília, Departamento de Ciência da Computação.

OpenNI (2010). OpenNI User Guide. OpenNI organization.

Ozaki, A., Buzeto, F., Castanho, C., and Jacobi, R. (2011). Um modelo para gerenciamento de ontologias em ambietes sensíveis ao contexto. In Anais do III Simpósio Brasileiro de Computação Ubíqua e Pervasiva SBCUP, pages 1–10. SBC.

P. Viola, M. J. (2001). Robust real-time object detection. Second International Workshop on Statistical and Computational Theories of Vision – Modeling, Learning, Computing, and Sampling.

Perlibakas, V. (2004). Distance measures for pca-based face recognition. Pattern Recogn. Lett., 25:711–724.

Rougier, C., Auvinet, E., Rousseau, J., Mignotte, M., and Meunier, J. (2011). Fall detection from depth map video sequences. In Abdulrazak, B., Giroux, S., Bouchard, B., Pigot, H., and Mokhtari, M., editors, ICOST, volume 6719 of Lecture Notes in Computer Science, pages 121–128. Springer.

Salah, A. A., Morros, R., Luque, J., Segura, C., Hernando, J., Ambekar, O., Schouten, B., and Pauwels, E. (2008). Multimodal identification and localization of users in a smart environment. Journal on Multimodal User Interfaces, 2(2):75–91.

Stiefelhagen, R., Bernardin, K., Ekenel, H. K., and Voit, M. (2008). Tracking identities and attention in smart environments contributions and progress in the chil project. In FG, pages 1–8.

Trivedi, M. M., Huang, K. S., and Mikic, I. (2005). Dynamic context capture and distributed video arrays for intelligent spaces. Ieee Transactions On Systems, Man, and Cybernetics—part A: Systems and Humans, 35(1):145 – 163.

Waibel, A., Stiefelhagen, R., Carlson, R., Casas, J. R., Kleindienst, J., Lamel, L., Lanz, O., Mostefa, D., Omologo, M., Pianesi, F., Polymenakos, L., Potamianos, G., Soldatos, J., Sutschet, G., and Terken, J. (2010). Computers in the human interaction loop. In Handbook of Ambient Intelligence and Smart Environments, pages 1071–1116.

Weiser, M. (1991). The computer for the 21st century. Scientific American.

Weiser, M. (1993). The world is not a desktop. ACM Interactions, 1.