Here you can find some commonly used algorithms in 3D image processing (3D Bildverarbeitung).
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Updated
Jan 26, 2024 - C++
Here you can find some commonly used algorithms in 3D image processing (3D Bildverarbeitung).
Tracking the preceding vehicle using Lidar and camera sensors to calculate the Time To Collision (TTC).
Testing various detector / descriptor combinations to see which ones perform best to be used in a collision detection system. Also 2 different approaches (FLANN vs. Brute-force with the descriptor distance ratio test) for keypoints matching are tested.
A package for registration of wide range astronomical images of stars, galaxies and clusters using SIFT, FLANN and RANSAC algorithms for extreme precision applications
Match a cropped image to the original image with an efficient algorithm using Python and OpenCV.
Python bindings for FLANN - Fast Library for Approximate Nearest Neighbors. (With Python 3 compatibility patches)
Image key points Extraction, Description, Feature Matching
A Julia wrapper for Fast Library for Approximate Nearest Neighbors (FLANN)
Utilized OpenCV, ORBDescriptors, FLANN, Homography/Affine Transformations, and a multi-layer convolutional architecture to do direct image matching via feature and key-point matching for scale-variant images
Processing videos of digital electricity meter to extract readings using OpenCV and Python
Panorama Image Stitching Using SIFT and SURF Keypoint Descriptors
Feature Tracking and testing of various keypoint detector/descriptor combinations, keypoint matching using Brute Force and FLANN approach.
📽️🖥️ Track objects on your camera or on a video.
Object 2D Pose Estimation trained by RGB Data - Using Intel® RealSense D435
Project: 2D Feature Tracking || Udacity: Sensor Fusion Engineer Nanodegree
6 DOF arm manipulation, utilizing knowledge-based reasoning, BDI and HTN planning
A vision-based nutrition management system (mobile + server) for users, where users can track the calorie and nutrient intake of the food products purchased, using the concepts of image processing, computer vision and machine learning to accurately predict names of cereal boxes, fruits, vegetables etc. The images are classified using the concept…
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