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Multimodal Identification and Tracking in Smart Environments

Publication Type : Journal Article

Publisher : Elsevier

Source : Journal of Personal and Ubiquitous Computing 14(8), pp. 685-694, 2010, Elsevier. DOI:

Url :

Campus : Amritapuri, Coimbatore, Kochi

School : Department of Computer Science and Engineering, School of Business, School of Engineering

Department : Computer Science

Year : 2010

Abstract : We present a model for unconstrained and unobtrusive identification and tracking of people in smart environments and answering queries about their whereabouts. Our model supports biometric recognition based upon multiple modalities such as face, gait, and voice in a uniform manner. The key technical idea underlying our approach is to abstract a smart environment by a state transition system in which each state records a set of individuals who are present in various zones of the environment. Since biometric recognition is inexact, state information is inherently 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 integrate different biometric modalities uniformly and also different criteria for state transitions. Fusion of biometric modalities is also supported by our model. We define performance metrics for a smart environment in terms of the concepts of ‘precision’ and ‘recall’. We have developed a prototype implementation of 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 good basis for developing practical systems.

Cite this Research Publication : V. Menon, B. Jayaraman, V. Govindaraju, “Multimodal Identification and Tracking in Smart Environments”, Journal of Personal and Ubiquitous Computing 14(8), pp. 685-694, 2010, Elsevier. DOI:

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