New York, New York, May 9, 2018 – At this year’s east coast gathering of streaming media experts, Professor Zhou Wang, Chief Science Officer at SSIMWAVE™ had the opportunity to sit on a panel with Anne Aaron, Director of Video Algorithms at Netflix, and Scott Labrozzi, Senior Principal Engineer/VP Video Processing at BAMTECH Media. The group’s panel, “Best Practices for Advanced Software Encoder Evaluations” was moderated by Tom Vaughan, VP Strategy at Beamr.

Best Practices for Advanced Software Encoder Evaluations

Tom Vaughan – Beamr, Professor Zhou Wang – SSIMWAVE, Scott Labrozzi – BAMTECH Media, and Anne Aaron – Netflix.

Tom began the discussion on evaluating encoders by stating, “if you want to know if a video looks good, you have to look at the video, but having a human subject watch every video gets expensive.”

This is where automated video quality assessments like SSIMPLUS™ and VMAF come into play – to save time and resources.

“SSIMPLUS can help with encoder optimization because it has the ability to go into such a fine granularity that you can do per-title, per-channel, per-scene, per-frame, per-block, and even per-pixel quality evaluations. Depending on which scale you want to base your encoder optimization on, you can choose the right scale to work with to make informed decisions.”

– Professor Zhou Wang, CSO, SSIMWAVE

Per-Title Optimization 2.0

Professor Wang followed the panel discussion with a more in-depth presentation entitled “Per-Title Optimization 2.0” — the most attended Discovery Track talk of the show. During this talk, Wang explained to the audience the details of Per-Title Optimization 1.0. He then continued on to explain the improvements Per-Title Optimization 2.0 provides to the industry and how SSIMWAVE is implementing this with SSIMPLUS.

Professor Zhou Wang leading Discovery Track Talk DT104 – Per-Title Optimization 2.0

Watch the full session.
View the slide deck.

Per-title optimization 2.0 allows users to go from an interactive, inaccurate and expensive solution (per-title optimization 1.0) to an automatic, accurate, low-cost solution.

When discussing cross-resolution quality assessment and creating per-title encoding ladders, Wang stated, “now you no longer have to take a shot in the dark. If you use what we call the quality-first principle of Per-Title Optimization 2.0, with one shot you can get exactly what you want.”

Are you in the business of streaming live and VOD content? We’d love to hear from you and understand your specific use cases. Do not hesitate to reach out. You’ll be glad you did.