Offered By: IBM

Video Processing - Subtracting Background with SVD

Want to know how to use Python to subtract background on a video easily? After reading this guided project, you will understand the foundation of singular-value decomposition and how to implement these technics to edit frames in a video. As a bonus, you will also learn how to use SVD to reduce data dimensions with the scikit-learn as a professional data scientist.

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Guided Project

Machine Learning

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At a Glance

Want to know how to use Python to subtract background on a video easily? After reading this guided project, you will understand the foundation of singular-value decomposition and how to implement these technics to edit frames in a video. As a bonus, you will also learn how to use SVD to reduce data dimensions with the scikit-learn as a professional data scientist.

About

As the popularity of short-form videos booms, more and more people are using the technic of video inpainting to edit their videos. Yet, before we learn how to code video inpainting algorithms, we need to know how to extract the background in a frame. The Singular-Value Decomposition (SVD) is one of the most efficient ways to remove pedestrians in a frame and return a clean background frame as a result. Moreover, SVD can also support data scientists in lessening the dataset’s complexity before starting any training by reducing the dimension of the dataset to handle complex data analysis efficiently.

A Look at the Project Ahead

After completing this guided project you will be able to:
  • Understand what SVD is in terms of Matrix Decomposition
  • Understand Truncated SVD
  • Implemented Truncated SVD with Numpy and Sklearn
  • Applied Truncated SVD to actual data
  • Recognized the relationship between SVD and PCA (optional)

What You'll Need

This project mainly uses Python and JupyterLabs to process the matrixes, and we recommend that you review the concepts of matrix and PCA before starting. Yet, if you are still getting familiar with those concepts, we still welcome everyone with no prior experience to enjoy this Guided Project.

Frequently Asked Questions

  • Do I need to install any software to participate in this project?
    Everything you need to complete this project will be provided to you via the Skills Network Labs and it will all be available via a standard web browser.

  • What web browser should I use?
    The Skills Network Labs platform works best with current versions of Chrome, Edge, Firefox, Internet Explorer, or Safari.

Certificate

No Certificate Offered

Estimated Effort

45 Minutes

Level

Intermediate

Industries

Skills You Will Learn

Computer Vision, Image Processing, Machine Learning, Python, Video

Language

English

Course Code

GPXX0IT0EN

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