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: A new method to estimate piecewise affine motion fields directly without intermediate segmentation.

Keyphrases: piecewise-affine motion estimation video

Dataset description:
SynthHands: The SynthHands dataset is a dataset for hand pose estimation which consists of real captured hand motion retargeted to a virtual hand with natural backgrounds and interactions with different objects. The dataset contains data for male and female hands, both with and without interaction with objects.
KITTI: KITTI (Karlsruhe Institute of Technology and Toyota Technological Institute) is one of the most popular datasets for use in mobile robotics and autonomous driving. It consists of hours of traffic scenarios recorded with a variety of sensor modalities, including high-resolution RGB, grayscale stereo cameras, and a 3D laser scanner.
ProofWriter: The ProofWriter dataset contains many small rulebases of facts and rules, expressed in English. Each rulebase also has a set of questions (English statements) which can either be proven true or false using proofs of various depths, or the answer is “Unknown” (in open-world setting, OWA) or assumed negative (in closed-world setting, CWA).
Oxford-Affine: The Oxford-Affine dataset is a small dataset containing 8 scenes with sequence of 6 images per scene. The images in a sequence are related by homographies.

Options:- A: SynthHands  B: KITTI  C: ProofWriter  D: Oxford-Affine
KITTI