epipolar-geometry
There are 1 repository under epipolar-geometry topic.
- Low-Cost-Mocap
jyjblrd / Low-Cost-Mocap
Low cost motion capture system for room scale tracking
Language:TypeScript 1307 JiawangBian / FM-Bench
An Evaluation of Feature Matchers for Fundamental Matrix Estimation (BMVC 2019)
Language:MATLAB 107- Language:Python 92
anubhavparas / visual-odometry
Implementing different steps to estimate the 3D motion of the camera. Provides as output a plot of the trajectory of the camera.
Language:Python 59HowieMa / TransFusion-Pose
[BMVC2021] "TransFusion: Cross-view Fusion with Transformer for 3D Human Pose Estimation"
Language:Python 38prclibo / relative_pose
A Collection of Algorithms for Relative Pose Estimation of a Calibrated Camera
Language:C++ 34dani-amirtharaj / KeyPointDetection-Homography-EpipolarGeometry
Programs to detect keyPoints in Images using SIFT, compute Homography and stitch images to create a Panorama and compute epilines and depth map between stereo images.
Language:Python 30sakshamjindal / Monocular-MiniSLAM
Real-Time Monocular Visual SLAM with Pose-graph optimization
Language:Python 30Real-time Stereo Visual SLAM Pipeline with Bundle Adjustment
Language:Python 29siddharthtelang / SfM
3D scene reconstruction and camera pose estimation given images from different views (Structure from Motion)
Language:Python 18ygaostu / Shearlet-Transform-TensorFlow
This is an implementation of Shearlet Transform (ST) for light field reconstruction using TensorFlow 1.x.
Language:Python 17xmba15 / uncalibrated_stereo_rectification
simple library for uncalibrated stereo rectification using feature points
Language:Python 12sakshikakde / Depth-Using-Stereo
Python code to estimate depth using stereo vision.
Language:Jupyter Notebook 11gkouros / coursera-robotics-perception-mooc
Contains notes and assignment solutions for the Robotics Perception MOOC offered by coursera
Language:MATLAB 8AlexisDrch / Computer-Vision
Computer Vision @GTech MSCS
Language:Jupyter Notebook 7Prasannanatu / sfm_and_nerf
Structure from Motion and NeRF
Language:Python 7sdeepaknarayanan / Computer-Vision
Assignments for 3D Computer Vision, IIT Gandhinagar
Language:Jupyter Notebook 7mfaisal59 / EpipolarScore
[WACV-2020] Exploiting Geometric Constraints on Dense Trajectories for Motion Saliency
Language:C++ 6Bazs / structure_from_motion
Simple Structure From Motion pipeline from scratch
Language:Python 4hiteshhedwig / visual_odo_max
wanna make the best visual odo knowledge out there
Language:Jupyter Notebook 4Luisrosario2604 / 3D-Vision
Manual calibration chessboard / Stereo vision reconstruction
Language:Jupyter Notebook 4twwang97 / 3D-Computer-Vision-Homework
Some projects are modified from Chu-Song Chen's class of 3D Computer Vision with Deep Learning Applications at National Taiwan University.
Language:Python 4karan9nov / epipolar-geometry
Calculation of Epipolar geometry using Fundamental Matrix, and the plotting the epipolar lines in the respective images.
Language:MATLAB 33D scene reconstruction (stereo)
Language:Python 3bharadwaj-chukkala / Stereo-Vision-to-estimate-depth-in-an-image
ENPM673: Project 3. Implementing a stereo vision pipeline to find the depth of an image. This project will generate a heat map indicating depth which has been calculated using disparity between correspondences
Language:Python 2prat1kbhujbal / Stereo_Depth_Estimation
Depth Estimation Using Stereo Cameras
Language:Python 2- Language:Jupyter Notebook 2
adamelkholyy / Computer-Vision-CW
Selection of notebooks from a masters computer vision course undertaken at University of Helsinki. Includes 3 notebooks tackling Hough Line Detection, Manhattan Frames, Epipolar Lines, Camera and Fundamental Matrix calculation along with other essential Computer Vision approaches..
Language:Jupyter Notebook 1antonItachi / visual-odometry
Study of Visual Odometry and Structure from Motion (SFM) problem
Language:Python 1bmisra03 / cmpen454-project2
Used epipolar geometry fundamentals to perform an array of computer vision tasks on camera snapshots and motion capture sensor data.
Language:MATLAB 1GraceSevillano / Computer-Vision-Course-Assignments
Detailed solutions to three programming assignments from the Computer Vision course taught by Prof. Renato Martins, covering corner detection, object recognition, and epipolar geometry.
Language:Jupyter Notebook 1Saharsh1005 / visual_odometry
Exploring Various Methods for Stereo Vision and their Impact on Visual Odometry using the KITTI Dataset
Language:Python 1Sri-Sai-Charan / Epipolar-Lines
A program to identify epipoles. The epipolar line is the straight line of intersection of the epipolar plane with the image plane. It is the image in one camera of a ray through the optical center and image point in the other camera. All epipolar lines intersect at the epipole.
Language:Jupyter Notebook 1vibhorag101 / TwoView_DepthEstimation
Developed a Two View Depth Estimation system utilizing Epipolar Geometry, OpenCV, SIFT Detectors, RANSAC, Frame Rectification, and StereoSGBM algorithm. Benchmarked depth maps using a pretrained PyTorch MiDaS monocular depth estimation model.
Language:Jupyter Notebook 1yufanana / ComputerVision02504
DTU course 02504 Computer Vision, Spring 2024
Language:Jupyter Notebook 1
