MCAP Episodes From a Photogrammetry Dataset With FiftyOne

PIVOT, a 56GB drone photogrammetry dataset designed for NeRF and 3D Gaussian splatting research, can also be treated as a robotics-log dataset because each trajectory records a moving camera, dual pose estimates, and a shared static sparse point cloud. The workflow described converts its 103 trajectories across five scenes into individual MCAP episodes for synchronized 3D playback in FiftyOne, while reducing the source download to roughly 27GB by excluding disposable COLMAP intermediate files. Each episode stores original JPEG images, repeated camera calibration, measured drone poses, available COLMAP-optimized poses, and a scene point cloud, using coordinate transformations to reconcile PIVOT’s NED/OpenGL conventions with the Z-up OpenCV/ROS conventions expected by Foxglove and FiftyOne. Since original image timestamps are unavailable, frames receive a synthetic 10 fps clock, and absent COLMAP poses are skipped rather than inferred. The resulting multimodal dataset supports inspection of flight paths and pose disagreement in a shared 3D environment, though users are advised to validate rendered episodes before batch conversion and account for wide-angle fisheye calibration issues when processing all trajectories.

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