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video2panorama is a Python-based tool designed to transform video sequences into panoramic images. It automates the stitching process by analyzing frames from input video files and producing panoramic outputs.
Photo_Stitching_with_OpenCv is a professional-grade Python project utilizing OpenCV to stitch two images into a seamless panoramic photo. It demonstrates advanced feature detection and matching techniques, providing the original images, the matching features, and the final panoramic result.
Design and development of a 360 Degree Field of View Camera, using multiple cameras. The current prototype consists of two cheap webcams mounted on a stand, rotated by a servo motor. The interfacing of the camera is done by a Raspberry Pi 3. The project also consists of developing an efficient stitching algorithm for producing best results.
This project implements a robust image stitching pipeline using feature-based matching techniques. It includes key steps such as SIFT feature detection, KNN matching with Lowe’s ratio test, RANSAC-based homography estimation, and multi-method blending (linear blending and single blending) to produce seamless panoramic images.