Personal media capturing devices, such as smartphones or personal image and video cameras, are rarely synchronized. As a result, common tasks, like event detection and summarization across different multi-user media galleries, are considerably impeded and error-prone. In this paper, we investigate different approaches for the synchronization of image collections using visual information only. We perform a thorough evaluation of the performance of several global features on three datasets. Additionally, we explore the feasibility of common clustering algorithms for the detection of sub-events in the presence of synchronization misalignment.

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