twitchslam is a small educational implementation of monocular simultaneous localization and mapping created during a livestream. It processes ordinary video while estimating camera motion and building a map of observed 3D points. Frames contain extracted visual features, while map points retain their 2D correspondences across frames. OpenCV handles feature extraction, SDL2 provides a 2D view, and Pangolin renders the reconstructed map in 3D. The project includes pose optimization, projection-based point recovery, a kinematic model, and map loading and saving. It can run against sample Freiburg and KITTI-style videos and supports optional ground-truth data for comparison.
Features
- Monocular video-based SLAM processing
- Camera pose estimation
- 3D point-map reconstruction
- OpenCV visual feature extraction
- 2D and 3D visualization
- Map loading, saving, and pose optimization
Categories
SystemLicense
MIT LicenseFollow twitchslam
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