Given a short query with keyphrases about a research idea in 2009 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: A performance comparison between visible, thermal infra-red and range

Keyphrases: human identification visible, thermal infra-red, range images

Dataset description:
FRGC: The data for FRGC consists of 50,000 recordings divided into training and validation partitions. The training partition is designed for training algorithms and the validation partition is for assessing performance of an approach in a laboratory setting.
WMCA: The Wide Multi Channel Presentation Attack (WMCA) database consists of 1941 short video recordings of both bonafide and presentation attacks from 72 different identities. The data is recorded from several channels including color, depth, infra-red, and thermal.
KAIST Multispectral Pedestrian Detection Benchmark: KAIST Multispectral Pedestrian Dataset  The KAIST Multispectral Pedestrian Dataset is imaging hardware consisting of a color camera, a thermal camera and a beam splitter to capture the aligned multispectral (RGB color + Thermal) images. With this hardware, we captured various regular traffic scenes at day and night time to consider changes in light conditions.
HotpotQA: HotpotQA is a question answering dataset collected on the English Wikipedia, containing about 113K crowd-sourced questions that are constructed to require the introduction paragraphs of two Wikipedia articles to answer. Each question in the dataset comes with the two gold paragraphs, as well as a list of sentences in these paragraphs that crowdworkers identify as supporting facts necessary to answer the question.

Options:- A: FRGC  B: WMCA  C: KAIST Multispectral Pedestrian Detection Benchmark  D: HotpotQA
FRGC