This paper addresses a still original issue and a solution that, while emerging from the pattern recognition point of view, certainly shares common goals with mobile HCI research goals. The contribution is at the crossroads of multimedia data analysis for content-based retrieval, and wearable computing. As users are acquiring multimedia content personal mobile devices, they are getting also undergoing information overflow. The problem of structuring the content into time-oriented meaningful episodes is addressed, and we argue that geographical location processing is crucial, as a complement to processing audiovisual material. A technique for model-based temporal structuring of one's trajectory during a day is presented, based on a Bayesian/MAP approach, that generates one or several summaries. Experimental results illustrate the applicative interest of the problem addressed and validates the proposed solution.
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