Matteo Zanotto

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We present a novel probabilistic framework that jointly models individuals and groups for tracking. Managing groups is challenging, primarily because of their nonlinear dynamics and complex layout which lead to repeated splitting and merging events. The proposed approach assumes a tight relation of mutual support between the modeling of individuals and(More)
Figure 1: The first 54 images of a lifelog. Notice the high blur (red boxed images) and the dramatic changes in illumination (yellow box) It is a common belief that in the near future, wearable technology will be the next computing revolution. Such wearable systems are intended to be used in a seamless way like a piece of clothing and they are at the basis(More)
This paper presents a generative framework aimed at the analysis of a " visual lifelog " captured by wearing a camera for long periods of time. Here, we focused on location recognition and we propose the use of an ensemble of heterogeneous generative models able to capture the different aspects that characterize each location. We defined the likelihood of(More)
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