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A system for retrieving video captured in a ubiquitous environment is presented. Data from pressure-based floor sensors are obtained as a supplementary input together with video from multiple stationary cameras. Unsupervised data mining techniques are used to reduce noise present in floor sensor data. An algorithm based on agglomerative hierarchical clustering is used to segment footpaths of individual persons. Video handover is proposed and two methods are implemented to retrieve video and key frame sequences showing a person moving in the house. Users can query the system based on time and retrieve video or key frames using either of the handover techniques. We compare the results of retrieval using different techniques subjectively. We conclude with suggestions for improvements, and future directions.