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IEEE Transactions on Pattern Analysis and Machine Intelligence
Information Retrieval
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Vector Model Based Indexing and Retrieval of Handwritten Medical Forms
ICDAR '07 Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 01
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Personal and Ubiquitous Computing
Multimodal identity tracking in a smart room
Personal and Ubiquitous Computing
Handbook of Remote Biometrics: for Surveillance and Security
Handbook of Remote Biometrics: for Surveillance and Security
Audio, video and multimodal person identification in a smart room
CLEAR'06 Proceedings of the 1st international evaluation conference on Classification of events, activities and relationships
Multimodal identification and tracking in smart environments
Personal and Ubiquitous Computing
The Three Rs of Cyberphysical Spaces
Computer
ICCSA'05 Proceedings of the 2005 international conference on Computational Science and its Applications - Volume Part I
Context-based scene recognition from visual data in smart homes: an Information Fusion approach
Personal and Ubiquitous Computing
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We discuss smart environments that identify and track their occupants using unobtrusive recognition modalities such as face, gait, and voice. In order to alleviate the inherent limitations of recognition, we propose spatio-temporal reasoning techniques based upon an analysis of the occupant tracks. The key idea underlying our approach is to determine the identity of a person based upon information from a track of events rather than a single event. We abstract a smart environment by a probabilistic state transition system in which each state records a set of individuals who are present in various zones of the smart environment. An event abstracts a recognition step, and the transition function defines the mapping between states upon the occurrence of an event. We express two forms of spatio-temporal reasoning in the form of transition functions: a track-based transition function and an error-correcting transition function. We also define the concepts of `precision' and `recall' to quantify the performance of the smart environment and provide experimental results to clarify the performance improvements from spatio-temporal reasoning. Our conclusion is that the state transition system is an effective abstraction of a smart environment and the application of spatial-temporal reasoning enhances the overall performance of a biometric recognition system.