Headcam: Cylindrical Panoramic Video Dataset for Unsupervised Learning of Depth and Ego-Motion
This dataset contains panoramic video captured from a helmet-mounted camera while riding a bike through suburban Northern Virginia. We used the videos to evaluate an unsupervised learning method for depth and ego-motion estimation, as described in our paper:
Alisha Sharma and Jonathan Ventura. "Unsupervised Learning of Depth and Ego-Motion from Cylindrical Panoramic Video." Proceedings of the 2019 IEEE Artificial Intelligence & Virtual Reality Conference, San Diego, CA, 2019.
If you make use of this dataset, please cite this paper.
The videos are stored as .mkv video files encoded using lossless H.264. To extract the images, we recommend using ffmpeg:
mkdir 2018-10-03 ;
ffmpeg -i 2018-10-03.mkv -q:v 1 2018-10-03/%05d.png ;
Associated code can be found in our GitHub repository.
- CRII: RI: High-Speed Vision-Based Motion Estimation 1464420
- National Science Foundation