✨Cross-platform set of tools for building native UIs with Reason/OCaml

Feature Detection and Matching with SIFT, SURF, KAZE, BRIEF, ORB, BRISK, AKAZE and FREAK through the Brute Force and FLANN algorithms using Python and OpenCV

React.js-like reconciler implemented in OCaml

Brisk is a complete Continuous Integration tool for executing your test suites. It is designed around speed and only rebuilds the test env when necessary. It can be run either from your developer machine (running your entire test suite in seconds on every save) or as part of your CI/CD pipeline.

Feature Detection and Description with SIFT, SURF, KAZE, BRIEF, ORB, BRISK, AKAZE and FREAK using Python and OpenCV

Stereo matching and sparse disparity map implementation using OpenCV (BRISK, ORB algorithms)

Mobile/PC Markerless AR detector&tracker core app

A General Purpose Wasm Linker Built For The Brisk Programming Language

Project: 2D Feature Tracking || Udacity: Sensor Fusion Engineer Nanodegree

A tiny toy “language” developed as an excuse to learn more about x86-x64 and code generation

A robust vision-based localization system for UAVs operating in GPS-denied environments. The system utilizes advanced computer vision techniques to achieve accurate position estimation by matching real-time drone camera feeds with satellite imagery.

Touch Bar App to launch set of applications and URLs based on different profiles.

2-D to 3-D Image Reconstruction of a telecommunication tower

Comparative Evaluation of Feature Descriptors Through Bag of Visual Features with Multilayer Perceptron on Embedded GPU System, published in 17th IEEE Latin American Robotics Symposium/8th Brazilian Symposium of Robotics (LARS/SBR 2020)

The idea of the camera course is to build a collision detection system. You will now build the feature tracking part and test various detector / descriptor combinations to see which ones perform best.

Code repository for Tactode tiles recognition using: (i) machine learning with HOG&SVM, (ii) deep learning with some neural networks like VGG16/19, ResNet152, MobileNetV2, YOLOv4 and SSD, (iii) matching of handcrafted features with SIFT, SURF, ORB and BRISK, and (iv) template matching.

Tracking the preceding vehicle using Lidar and camera sensors to calculate the Time To Collision (TTC).

Testing BRISK with OpenCV and Android

BriskDotNet is a .net library for interact with the Brisk API