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Building In-Video Search

The Netflix TechBlog

We have built an internal system that allows someone to perform in-video search across the entire Netflix video catalog, and we’d like to share our experience in building this system. Building in-video search To build such a visual search engine, we needed a machine learning system that can understand visual elements.

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All of Netflix’s HDR video streaming is now dynamically optimized

The Netflix TechBlog

by Aditya Mavlankar , Zhi Li , Lukáš Krasula and Christos Bampis High dynamic range ( HDR ) video brings a wider range of luminance and a wider gamut of colors, paving the way for a stunning viewing experience. HDR was launched at Netflix in 2016 and the number of titles available in HDR has been growing ever since.

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How To Implement Video Information and Editing APIs in Java

DZone

In the past 15+ years, online video traffic has experienced a dramatic boom utterly unmatched by any other form of content. It must be said that this video traffic phenomenon primarily owes itself to modernizations in the scalability of streaming infrastructure, which simply weren’t present fifteen years ago.

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Performing Sentiment Analysis Video

DZone

This video talks about an end-to-end flow, wherein an email content having a specific subject line will be read, the email body would be analyzed using Azure Cognitive Services (Sentiment analysis), analysis results would be saved in Azure Table Storage and finally, the chart would be drawn in Excel.

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Netflix Video Quality at Scale with Cosmos Microservices

The Netflix TechBlog

Moorthy and Zhi Li Introduction Measuring video quality at scale is an essential component of the Netflix streaming pipeline. Perceptual quality measurements are used to drive video encoding optimizations , perform video codec comparisons , carry out A/B testing and optimize streaming QoE decisions to mention a few.

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MezzFS?—?Mounting object storage in Netflix’s media processing platform

The Netflix TechBlog

Mounting object storage in Netflix’s media processing platform By Barak Alon (on behalf of Netflix’s Media Cloud Engineering team) MezzFS (short for “Mezzanine File System”) is a tool we’ve developed at Netflix that mounts cloud objects as local files via FUSE. What problem are we solving? Encoding is not a one-time process?—?large

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Scaling Media Machine Learning at Netflix

The Netflix TechBlog

In addition, we provide a unified library that enables ML practitioners to seamlessly access video, audio, image, and various text-based assets. Media Feature Storage: Amber Storage Media feature computation tends to be expensive and time-consuming. Background Match Cutting is a video editing technique.

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