Computer Vision-Runtime Remote Video Quality Assessment

Abstract

This project presents a Runtime Remote Video Quality Assessment system based on Computer Vision techniques. The system evaluates the visual quality of uploaded videos by analyzing important quality parameters such as brightness, contrast, and blur. It provides a simple web-based platform that enables users to register, log in, upload videos, and receive instant quality assessment results. The proposed system ensures efficient and automated video quality evaluation, reducing the need for manual inspection. Traditional video quality assessment methods often rely on reference videos, specialized software, or human evaluation, making the rmtime-consuming, for realtime applications. These methods also lack a simple and accessible platform for remote video quality monitoring. There is a need for a lightweight, cost-effective, and automated video quality assessment system that can accurately evaluate video quality and provide immediate feedback to users. The proposed system addresses these challenges by integrating Computer Vision and Image Processing techniques to deliver fast, reliable, and user-friendly video quality analysis.