We present a solution to the problem of discovering all periodic
segments of a video and of estimating their period in
a completely unsupervised manner. These segments may be
located anywhere in the video, may differ in duration, speed,
period and may represent unseen motion patterns of any type
of objects (e.g., humans, animals, machines, etc). The proposed
method capitalizes on earlier research on the problem
of detecting common actions in videos, also known as commonality
detection or video co-segmentation. The proposed
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