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Python implementation of the Stereo PTAM (parallel tracking and mapping), See the paper: "[S-PTAM: Stereo Parallel Tracking and Mapping](docs/S-PTAM: Stereo Parallel Tracking and Mapping.pdf) Taihu Pire et al. RAS17"

Example of S-PTAM on KITTI dataset

Requirements

  • Python 3.6+
  • cv2
  • numpy
  • g2o (python binding of C++ library g2o) for BA and pose graph optimization
  • pangolin (python binding of C++ library Pangolin) for visualization

Features

  • Multithreads Tracking, Mapping, and Loop Closing;
  • Covisibility Graph (representing the relation between keyframes, mappoints and measurements);
  • Local Bundle Adjustment and Pose Graph Optimization;
  • Motion Model (used for pose prediction, then for reliable feature matching);
  • Point Clouds and Graph visualization;

Usage

python3 main.py

System overview :

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S-PTAM: Stereo Parallel Tracking and Mapping, python implementation

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