Given a short query with keyphrases about a research idea in 2018 in the domain of artificial intelligence, recommend the relevant datasets to validate the research idea from options provided. A short description of the datasets is also provided to help you.

Query: I want to segment human activities from videos and predict which action category is being performed.

Keyphrases: action segmentation video

Dataset description:
AVA: AVA is a project that provides audiovisual annotations of video for improving our understanding of human activity. Each of the video clips has been exhaustively annotated by human annotators, and together they represent a rich variety of scenes, recording conditions, and expressions of human activity.
MECCANO: The MECCANO dataset is the first dataset of egocentric videos to study human-object interactions in industrial-like settings. The MECCANO dataset has been acquired in an industrial-like scenario in which subjects built a toy model of a motorbike.
BABEL: BABEL is a large dataset with language labels describing the actions being performed in mocap sequences. BABEL consists of action labels for about 43 hours of mocap sequences from AMASS.
Charades: The Charades dataset is composed of 9,848 videos of daily indoors activities with an average length of 30 seconds, involving interactions with 46 objects classes in 15 types of indoor scenes and containing a vocabulary of 30 verbs leading to 157 action classes. Each video in this dataset is annotated by multiple free-text descriptions, action labels, action intervals and classes of interacting objects.

Options:- A: AVA  B: MECCANO  C: BABEL  D: Charades
Charades