HoloSet - A Dataset for Visual-Inertial Pose Estimation in Extended Reality

HoloSet was published at DATA'22 workshop at ACM SenSys'22. 

Overview: There is a lack of datasets for visual-inertial odometry applications in Mixed Reality (MR). To the best of our knowledge, there is no dataset available that is captured from an MR headset with a human as a carrier. To bridge this gap, we present a novel pose estimation dataset — called HoloSet — collected using Microsoft Hololens 2, which is a state-of-the-art head mounted device for XR. Potential applications for HoloSet include visual-inertial odometry, simultaneous localization and mapping (SLAM), and additional applications in XR that leverage visual-inertial data.

HoloSet captures both macro and micro movements. For macro movements, the dataset consists of more than 66,000 samples of visual, inertial, and depth camera data in a variety of environments
(indoor, outdoor) and scene setups (trails, suburbs, downtown) under multiple user action scenarios (walk, jog). For micro movements, the dataset consists of more than 12,000 samples of additional articulated hand depth camera images while a user plays games that exercise fine motor skills and hand-eye coordination. We present basic visualizations and high-level statistics of the data and outline the potential research use cases for HoloSet.

Please find the relevant publication at https://dl.acm.org/doi/abs/10.1145/3560905.3567763.