This paper addresses the issue of automated organization of a personal image collection, in particular to respond to the emerging needs from a mobile camera phones. The issues related to browsing through large image collections acquired from such devices are first discussed. In contrast with metadata-less collections, which necessarily rely on image content, we propose a collection organization technique based on picture geolocation and timestamps. These are indeed available and generally reliable in the proposed context. The objective is formulated as an unsupervised classification problem, in both space and time. The statistical ntegrated completed likelihood criterion is chosen, providing effective solutions both to model complexity determination and the cluster separability objective, in a setting which avoids arbitrary algorithm parametrization. Reliability of space and time partitions obtained are then assessed, to select an effective segmentation, which may then provide a calendar-type structured view for navigating in the picture collection.