EYEDIAP Overview
The EYEDIAP dataset was designed to train and evaluate gaze estimation algorithms from RGB and RGB-D data. It contains a diversity of participants, head poses, gaze targets and sensing conditions.
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The lack of a common benchmark for the evaluation of the gaze estimation task from RGB and RGB-D data is a serious limitation for distinguishing the advantages and disadvantages of the many proposed algorithms found in the literature. The EYEDIAP dataset intends to fill the need for a standard database for gaze estimation from remote RGB, and RGB-D (standard vision and depth), cameras. The recording methodology was designed such that we systematically include, and isolate, most of the variables which affect the remote gaze estimation algorithms:
Some pre-defined benchmarks are provided to evaluate each one of these aspects in an independent manner, and the data was preprocessed to extract and provide complementary observations (e.g. head pose).
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The recording setup is as shown in the image below: |
