Video Processing – Subtracting Background with SVD
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Learn how to use Python to subtract background on a video easily. Understand singular-value decomposition and implement techniques to edit frames in a video. Also, learn how to reduce data dimensions with scikit-learn as a professional data scientist.
At a Glance
Want to know how to use Python to subtract background on a video easily? After doing this guided project, you will understand the foundation of singular-value decomposition and how to implement these techniques 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.
As the popularity of short-form videos booms, more and more people are using the technique of video inpainting to edit their videos. The goal of Video Inpainting is to fill in missing regions of a given video sequence with contents that are both spatially and temporally coherent. 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.
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