FIMS QC 8 th March 2013 WebEx

FIMS - Intellectual Property Rights Rules "This meeting is being held under the Intellectual Property Rights Policy of the Advanced Media Workflow Association. By signing in and attending this meeting, you have agreed to be bound, and your employer, if a member of the AMWA, is already bound, by that policy. If you are unfamiliar with that policy, please ask the Chair of this meeting, and s/he will provide you with a copy of that Policy. At this time, I would ask that anyone in attendance inform me if they are personally aware of any claims under any patent applications or issued patents that would be likely to be infringed by an implementation of the specification or other work product which is the subject of this meeting. You need not be the inventor of such patent or patent application in order to inform us of its existence, nor will you be held responsible for expressing a belief that turns out to be inaccurate."

FIMS QC : GOAL Develop a framework that according to FIMS’goals: –Allows adoption of new business models –Allows strategic technology changes –Provides flexibility and cost leveraging. –Supports faster deployment and effective, efficient usage Scope –Correction is out of scope. –File retrieval –Watch folder

Content Recognition Example Define -Identify -Recognize objects and label them, -Matching/Related Items together Out of Scope In studio workflows, we often encounter the use case of matching textless and texted sections. A bit of background: Often, one encounters text in video. For example, a marquis or chyron displaying information in the lower third of a sequence of a "reporter on the scene," or the name of a trucking company emblazoned on the side of a dump truck. For film and video targeted for eventual distribution to international markets, the creators of the content purposefully record such content with no text on it at all. The text is added later, in post. An example: TC Content 1:00:01:03 Dump Truck in murder scene (Textless) 2:55:41:01 End Credits 3:01:04:06 Dump Truck in murder scene (French) 3:01:05:09 Dump Truck in murder scene (English) 3:01:06:12 Dump Truck in murder scene (German) 3:01:07:15 Dump Truck in murder scene (Mandarin) In this situation, some tools will match the textless scene with texted scenes automatically. They will automatically find the matching content using sophisticated content-matching (CONTENT RECOGNITION) algorithms, and will report/persist the information as part of the report. This is extremely valuable for automated fulfillment workflows, as such workflows can automatically create the appropriate make for the market in question simply by having the editor/transcoder read this information from the report associated with the given media and stitch together the right version of the texted content for the target language. In studio workflows, we often encounter the use case of matching textless and texted sections. A bit of background: Often, one encounters text in video. For example, a marquis or chyron displaying information in the lower third of a sequence of a "reporter on the scene," or the name of a trucking company emblazoned on the side of a dump truck. For film and video targeted for eventual distribution to international markets, the creators of the content purposefully record such content with no text on it at all. The text is added later, in post. An example: TC Content 1:00:01:03 Dump Truck in murder scene (Textless) 2:55:41:01 End Credits 3:01:04:06 Dump Truck in murder scene (French) 3:01:05:09 Dump Truck in murder scene (English) 3:01:06:12 Dump Truck in murder scene (German) 3:01:07:15 Dump Truck in murder scene (Mandarin) In this situation, some tools will match the textless scene with texted scenes automatically. They will automatically find the matching content using sophisticated content-matching (CONTENT RECOGNITION) algorithms, and will report/persist the information as part of the report. This is extremely valuable for automated fulfillment workflows, as such workflows can automatically create the appropriate make for the market in question simply by having the editor/transcoder read this information from the report associated with the given media and stitch together the right version of the texted content for the target language.

Check/Tests -- interpretation Value, Scale -- interpretation Severity (Seriousness) Formats etc... Check/Tests -- interpretation Value, Scale -- interpretation Severity (Seriousness) Formats etc... Profile Use Case / Examples Definition –List of allowed checks & formats against which user wants to validate its audio/video content. What it can contain ? –We will define that… Every QC job would need to profile to validate content against. VOD (SD/HD) -- On DemandiTunes Delivery Spec NetflixApple HLS / Smooth Streaming MezzanineCustomer specific deliverable spec: e.g. NBC Spec, DG spec etc XDCAMInternal formats Can allow more than 1 format also. E.g. Quicktime & Program Stream -- SD/HD