Abstract
This paper presents a human tracking agent that recognizes the location and motion of the human in the home. We describe the architecture of the human tracking agent, and present an image recognition algorithm to track location and motion of the human. The human tracking agent decides the human’s location, which changes in real-time, through the reletive distance of home furniture (or appliance) and human. Unlike the human’s location, because a person’s appearance (height, weight) is different for each person, a human’s motion should be recognized to be different from each other person. We converted the image (that is acquired from the network camera) into a standard image (that is defined in the human tracking agent) for recognition of multi-user’s motion. We used a LSVM(linear support vector machine) to recognize the feature patterns for human motion. In our experiment, results of motion recognition showed excellent performance accuracy of over 80%.
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
Schulzrinne, H., Wu, X., Sidiroglou, S., Berger, S.: Ubiquitous computing in home networks. Communication Magazine. IEEE 41(11), 128–135 (2003)
Sherif, M.H.: Intelligent homes: a new challenge in telecommunications standardization. Communication Magazine. IEEE 40(1), 8–8 (2002)
Want, R., Hopper, A.: Active badges and personal interactive computing objects. Consumer Electronics. IEEE Transactions 38(1), 10–20 (1992)
Hazas, M., Hopper, A.: Broadband Ultrasonic Location Systems for Improved Indoor Positioning. Mobile Computing. IEEE Transactions 5(5), 536–547 (2006)
Smith, A., Balakrishnan, H., Goraczko, M., Priyantha, N.B.: Tracking Moving Devices with the Cricket Location System. In: 2nd International Conference on Mobile Systems. Applications and Services (Mobisys 2004) (2004)
Bahl, P., Padmanabhan, V.: RADAR: An In-Building RF-based User Location and tracking system. In: Proc, IEEE infocom, pp. 775–784. IEEE CS Press, Los Alamitos (2000)
Orr, J.R., Gregory, A.D.: The smart floor: A Mechanism for natural user identification and tracking. In: The proceedings of the 2000 Conference on Human Factors in Computing systems (CHI 2000), The Hague, Netherlands (to appear, 2000)
MavHome, http://cygnus.uta.edu/mavhome/
Das, S.K., Cook, D.J., Battacharya, A., Heierman III, E.O., Lin, T.-Y.: The role of prediction algorithms in the MavHome smart home architecture. Wireless Communications. IEEE 9(6), 77–84 (2002)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Lee, J., Choi, J., Shin, D., Shin, D. (2006). Multi-user Human Tracking Agent for the Smart Home. In: Shi, ZZ., Sadananda, R. (eds) Agent Computing and Multi-Agent Systems. PRIMA 2006. Lecture Notes in Computer Science(), vol 4088. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11802372_50
Download citation
DOI: https://doi.org/10.1007/11802372_50
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-36707-9
Online ISBN: 978-3-540-36860-1
eBook Packages: Computer ScienceComputer Science (R0)