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Digital video capturing is getting popular with the decreasing price of camcorders and the increasing availability of devices with embedded video cameras such as digital-still cameras, mobile phones and PDAs. While a raw home video is considered as visually non-appealing, having multiple recordings of the same event provides the opportunity to combine audio and video segments from different cameras for improving quality and aesthetics. Mixing content from different recordings requires precise synchronization among the recordings. In most present applications, synchronization is done manually and considered as a very tedious task. In this paper, we propose a novel automated synchronization approach based on detecting and matching audio and video features extracted from the recorded content. We assess experimentally three realizations of this approach on a common data set and make recommendations on the usability of the different realizations in practical use cases. The realizations have no limitations on the number and movement of the cameras. Moreover, they are robust against various ambient noises and audio-visual artifacts occurring during the recordings.