TUM Kitchen
Introduced by Moritz Tenorth et al. in The TUM Kitchen Data Set of everyday manipulation activities for motion tracking and action recognition
The TUM Kitchen dataset is an action recognition dataset that contains 20 video sequences captured by 4 cameras with overlapping views. The camera network captures the scene from four viewpoints with 25 fps, and every RGB frame is of the resolution 384×288 by pixels. The action labels are frame-wise, and provided for the left arm, the right arm and the torso separately.
Source: Temporal Human Action Segmentation via Dynamic ClusteringPapers
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