A periodicity detection dataset
We present a solution to the problem of discovering all temporally periodic segments of a given video and of estimating their period in a completely unsupervised manner. These periodic segments may be located anywhere in the original sequence, 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 [1-2].