An Evaluation of Feature Matchers for Fundamental Matrix Estimation (BMVC 2019)
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Updated
Apr 6, 2020 - MATLAB
An Evaluation of Feature Matchers for Fundamental Matrix Estimation (BMVC 2019)
Contains notes and assignment solutions for the Robotics Perception MOOC offered by coursera
Calculation of Epipolar geometry using Fundamental Matrix, and the plotting the epipolar lines in the respective images.
The project involves projective geometry, geometric transformations, modelling of cameras, feature extraction, stereo vision, recognition and deep learning, 3d-modelling, geometry of surfaces and their silhouettes, tracking, and visualisation.
In this repository, 8-point algorithm is used to find the fundamental matrix based on SVD. Disparity map is generated from left and right images. In addition, RealSense depth camera 435i is used to estimate object center depth. Image thresholding and object detection are implemented. It is apart of Assignment3 in Sensing, Perception and Actuatio…
Used epipolar geometry fundamentals to perform an array of computer vision tasks on camera snapshots and motion capture sensor data.
ComputerVision Practical Session
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