SRA
SRA is a real-time digital human workforce solution designed to support businesses and customers anytime, anywhere. We iterated through multiple concepts before we achieved our launched product.
- Reported directly to Sr. VP of Research who lead the Generative AI Digital Human Platform
- Building Design Team from ground up as Hiring Manager to include Directors, CG Artists,
Product Designers, Concept Artists, Technical Artist, SWE, and Digital Asset Manager
- Building Design Team from ground up as Hiring Manager to include Directors, CG Artists,
- Building the automated Quality Control and Media Asset Management pipeline using
Python and FFMPEG for training realtime digital humans via generative AI, to assess
crops, transcodes, sound, frame anomalies, rig, key points, sync, color, proxies
- System runnable by a digtial asset manager with CLI experience
- editable Json, Yaml file
- FFMPEG, MediaArena QCtools, Mediapipe, SoX (sound),
- code that determines Loudness Units (Lufs) and correct codecs
- System runnable by a digtial asset manager with CLI experience
- Converting greenscreen stage from 12k resolution video capture to multicam broadcast
capture and mocap, as well as building the end-to-end hardware/software solution for
audio capture and DSLR facial photogrammetry within a reasonable budget.
- Problem: Too much future proofing by capturing too much data with unclear requirements.
- Solution: work with r and d on narrowing down requirements and building a capture system for production.
- Maintain flexibility for r and d, but keep the rigid requirements of software team.
- Increase speed of capture tenfold
- Problem: How to capture with a midsize budget
- Understand project requirements
- Ensure studio is color correct, but when deploying to various devices, its lesser priority
- Problem: How to sync cameras
- Dont trust hardware specs, always verify
- Our recorder claims to be able to shoot synced cameras, but found out via timecode it is off a few frames heads and tails
- wrote code to take videos with timecode and cuts heads and tails to insure sync
- Experimented with AI solutions first to see if there results are good
- Experimented with 3d Cameras but frames drop for long recording sessions
- Need timecode and genlock because will triangulate data later for inhouse mocap solution
- Our recorder claims to be able to shoot synced cameras, but found out via timecode it is off a few frames heads and tails
- Dont trust hardware specs, always verify
- On-set Technical Director for Talent data capture, and Pipeline Lead for the Design Team
- Previous experience as a filmmaker/improv and onset director helped with coaching actresses to perform better
- Actors strike affected getting good quality data because we couldnt hire SAG
- Solved all Technical issues onset
- Collaborating with Business Strategy and Product Designers on pitch and video decks in
order to prototype Minimal Viable Products using Maya, Blender, Resolve, Unreal, Unity - Working with R&D scientists on 2D and 3D digital human methods found in latest papers
- Focused on dataops and capture related portion
- determine how to emulate public datasets or buy them, since for product licensing prevents open use