Public Datasets for SLAM

TUM RGB-D benchmark [38]
- an excellent dataset to evaluate the accuracy of camera location
- several sequences with accurate ground truth obtained with an external motion capture system

KITTI
- extracted 2000 corners
- 512x384
- 752x480
- 1241x376
- 5 corners per cell

Compute orientation & ORB descriptors
- novel, direct, semi-dense, LSD-SLAM [10]
- takes time to converge the depth values
- PTAM benchmarks [4]
- manually selected two keyframes for initialization

- align the keyframe trajectories using the similarity transformatione
- scale is unknown
- measure the absolute trajectory error (ATE) [38]

- RGB-D SLAM [43]
- trajectories

- use the similarity transform to check if the scale is well recovered.
- align the trajectories with a rigid body transformation

Comments

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Artificial Intelligence and Machine Vision

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