Compute Parallax for difference between two images

OpenCV based Image Stitching applied various method (using RealSense Camera) !!

This is a project for socks card label validation where the socks card is validated comparing with the correct socks card whose coordinates are stored in the database. When the test socks card is compared with the correct socks card(master socks card) the software checks whether both test and master socks card matches or not.

Computer vision and cognitive systems: concepts, methods, and technologies

image stitching using superglue

Using OpenCV to match features and identify an object.

Projects Implemented for the Udacity Sensor Fusion Engineer Nanodegree Program

Make Rendered Database using Rendered Image Obtained by Trained Gaussian Splatting

Todo o conteúdo produzido para a unidade curricular VC (Visão por Computador), para o curso em Engenharia Informática e Computação na FEUP

3D scene reconstruction (stereo)

Map images to representation vectors.

Panoramic image stitching using traditional and deep learning approach

Computer vision small projects. Algorithms from scratch.

Calculate time-to-collision by using Lidar and camera

A Where's Waldo puzzle solver made using OpenCV and Python.

Image Feature Matching with Julia using freak descriptor

Stabilo is a Python package for stabilizing video frames or object trajectories using advanced transformation techniques. It supports user-defined masks to exclude specific areas, making it ideal for dynamic scenes with moving objects. Unlike traditional stabilization, it stabilizes content relative to a chosen reference frame.

When given different views of an object as input, it can tell us if that specific object is present in a larger picture or not.

This repo consist of my project based on Udacity Sensor Fusion Nanodegree on 2D Image Feature tracking

Implementing the concept of Stereo Vision. We are given 3 different datasets, each of them containing 2 images of the same scenario but taken from two different camera angles. By comparing the information about a scene from 2 vantage points, we can obtain the 3D information by examining the relative positions of objects.