Structure from motion (SfM) is the process of estimating the 3-D structure of a scene from a set of 2-D images. SfM is used in many applications, such as 3-D scanning , augmented reality, and visual simultaneous localization and mapping (vSLAM). SfM can be computed in many different ways.
This project presents our pipeline for recreating a 3-D scene using Structure from Motion. Reconstructed a 3 dimensional scene with 2D stereo images from a monocular camera captured from different views while estimating camera poses along the way. The pipeline consists of Feature Matching, RANSAC Based Outlier feature rejection and Estimation of Fundamental Matrix, Estimation of Essential matrix from F matrix, Camera Pose Estimation and Refinement, Check for Cheirality Condition using Triangulation, Linear and Nonlinear Perspective-n-point estimation, Bundle Adjustment to achieve the results.
- Ubuntu 20.04 LTS
- Python Programming Language
- OpenCV Library
- SciPy Library
- Pylint
- Doxygen
MIT License
Copyright (c) 2023 Aditya Jadhav
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- ./Results
- GoPro Hero 3 camera used with fisheye lens distortion corrected
- 6 stereo images of Levine Hall at UPenn
- SIFT keypoints and descriptors used
- High Triangulation errors
- High BA errors
- cv2 4 or higher
- scipy latest version
- numpy
To Run tests
python test_load_dataset.py
Final Output and Overview --> ./Results