Given a short query with keyphrases about a research idea in 2019 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: We propose a method that exploits feature variance maximization in low-rank tensor decomposition for feature extraction from

Keyphrases: feature extraction image video

Dataset description:
USF: The USF Human ID Gait Challenge Dataset is a dataset of videos for gait recognition. It has videos from 122 subjects in up to 32 possible combinations of variations in factors.
DICM: DICM is a dataset for low-light enhancement which consists of 69 images collected with commercial digital cameras.
BREAK: Break is a question understanding dataset, aimed at training models to reason over complex questions. It features 83,978 natural language questions, annotated with a new meaning representation, Question Decomposition Meaning Representation (QDMR).
UASOL: The UASOL an RGB-D stereo dataset, that contains 160902 frames, filmed at 33 different scenes, each with between 2 k and 10 k frames. The frames show different paths from the perspective of a pedestrian, including sidewalks, trails, roads, etc.

Options:- A: USF  B: DICM  C: BREAK  D: UASOL
USF