There are 11 repositories under disparity-map topic.
single and stereo calibration, disparity calculation.
A heterogeneous and fully parallel stereo matching algorithm for depth estimation, implementing a local adaptive support weight (ADSW) Guided Image Filter (GIF) cost aggregation stage. Developed in both C++ and OpenCL.
Code for 'Segment-based Disparity Refinement with Occlusion Handling for Stereo Matching'
Three-Filters-to-Normal: An Accurate and Ultrafast Surface Normal Estimator (RAL+ICRA'21)
Code for "Unsupervised Adaptation for Deep Stereo" - ICCV17
Disparity maps using various algorithms
Implementation of simple block matching, block matching with dynamic programming and Stereo Matching using Belief Propagation algorithm for stereo disparity estimation
C++ example codes for camera calibration, rectification and to build disparity maps
Compute disparity map from stereo image with semi global matching algorithm.
ROS package for local obstacle avoidance using stereo RGB cameras on the Jackal
Learning from scratch a confidence measure
Stereo 3D Reconstruction for two views
Object tracking with OpenCV based on stereo camera images
Pothole Detection Based on Disparity Transformation and Road Surface Modeling (T-IP)
A system which includes a pair of stereo-cameras for 3D reconstruction, object detection and depth analysis with the help of disparity maps.
Python code to estimate depth using stereo vision.
Disparity Maps and Image Segmentation Implementation
Calculating Disparity Maps using openCVs implemented algorithms.
Stereo matching and sparse disparity map implementation using OpenCV (BRISK, ORB algorithms)
Stereo matching algorithms implemented in MATLAB
Finds the stereo disparity between a pair of stereo images using SIFT and ORB algorithms
[AI6121] Computer Vision is an elective course of MSAI, SCSE, NTU, Singapore. The repository corresponds to the AI6121 of Semester 1, AY2021-2022, starting from 08/2021. The instructor of this course is Prof. Lu Shijian.
Computer Vision @GTech MSCS
Simple program in python for distance calculation using stereo cameras. Made for a university project.
A stereo vision system project (with calibration) using the MATLAB toolboxes.
A python implementation of computing depth from stereo pair of images.
Camera model and stereo depth sensing using OpenCV
Estimating pedestrian and vehicle distances using sparse and dense stereo
Probabilistic Graphical Models for Stereo Disparity Map Reconstruction by Factor Graph and Belief Propagation Maximum A Posteriori
A straightforward Siamese network designed for block matching to generate a disparity map
With Stereo Vision, 3D reconstruction based on two methods. First, correlation based algorithm which extracts disparity map then estimate depth value. The other is Feature-based algorithm which extracts features with SIFT, then use triangulation to get depth value.
Example of disparity map created by stereo correspondence through two images and a point cloud map created by LIDAR data values (distances measures).