Clustering and Synchronizing Multi-camera Video via Landmark Cross-Correlation

IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

Publication date: March 25, 2012

Nicholas J. Bryan, Paris Smaragdis, Gautham Mysore

We propose a method to both identify and synchronize multi-camera video recordings within a large collection of video and/or audio files. Landmark-based audio fingerprinting is used to match multiple recordings of the same event together and time-synchronize each file within the groups. Compared to prior work, we offer improvements towards event identification and a new synchronization refinement method that resolves inconsistent estimates and allows non-overlapping content to be synchronized within larger groups of recordings. Furthermore, the audio fingerprinting-based synchronization is shown to be equivalent to an efficient and scalable time-difference-of-arrival method using cross-correlation performed on a non-linearly transformed signal.

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