VPA2VOG Gesture Convert: Migrating Virtual Places Animations to Voodoo VOG
Migrating gesture animations from the legacy Virtual Places Animation (VPA) format to the Voodoo VOG format can revive older assets and make them compatible with modern engines. This guide walks through the conversion goals, prerequisites, an actionable step‑by‑step workflow, common issues and fixes, and tips for batch processing and validation.
Goal
Convert VPA gesture files into VOG format while preserving timing, keyframes, and blending behavior so gestures play correctly in the Voodoo runtime.
Prerequisites
- Source VPA gesture files (back up originals).
- VPA2VOG converter tool (command‑line or GUI) — ensure latest version.
- Voodoo VOG specification or SDK (for reference).
- A text editor for metadata tweaks and a tool to inspect VOG output (viewer/debugger).
- Optional: scripting environment (Python/Node) for batch tasks.
Workflow — Single File (recommended order)
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Inspect the VPA file
- Open the VPA in a text or binary viewer to identify structure: header, keyframe blocks, timeline, and metadata.
- Note frame rate, loop flags, and any custom easing curves.
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Prepare mapping rules
- Map VPA channels to VOG channels (e.g., VPA.HeadYaw → VOG.headyaw).
- Decide unit conversions (degrees ↔ radians, normalized values).
- Map blend modes (additive, override) to VOG equivalents.
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Run the converter
- Use the VPA2VOG tool with flags for framerate and mapping file:
Code
vpa2vog –input gesture.vpa –output gesture.vog –fps 30 –map mappings.json - If GUI, load input, select mapping preset, set export options, and convert.
- Use the VPA2VOG tool with flags for framerate and mapping file:
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Review converted VOG
- Open VOG in viewer. Check playback speed, keyframe alignment, and looping.
- Compare important poses at specific timestamps with original VPA (frame-by-frame).
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Adjust metadata
- Edit VOG metadata: name, author, tags, priority, blending masks.
- Fix any channel name mismatches or inverted axes.
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Validate in target runtime
- Import into Voodoo runtime/engine and trigger the gesture.
- Observe interactions with other animations and transitions.
Batch Conversion
- Create a mappings.json that covers common channel mappings and unit rules.
- Write a small script (example in pseudocode):
Code
for file in directory/*.vpa: run vpa2vog –input file –output out_dir/file.vog –fps 30 –map mappings.json - After batch run, auto-validate by sampling N frames from each output and comparing keyframe timestamps to source.
Common Issues & Fixes
- Timing drift (fps mismatch): Convert using the original VPA frame rate or resample keyframes to target fps.
- Axis inversion (mirrored motion): Apply sign inversion in mapping rules for affected channels.
- Missing channels: If VOG lacks an equivalent, create a synthetic channel or map to a closest available channel, then tweak weights.
- Easing curve loss: Export easing as cubic bezier or approximate with extra keyframes.
- Blending artifacts: Ensure blend masks and priorities are set; use additive where appropriate.
Testing Checklist
- Play gesture solo and with other layered animations.
- Verify start/end poses match expectations.
- Check loop continuity if gesture is looped.
- Confirm no sudden pops at blend boundaries.
- Validate performance (memory/CPU) for batch imports.
Tips
- Keep a library of mapping presets per content type (facial, hands, body).
- Use versioned outputs so you can revert if migration introduces regressions.
- Automate visual diffs by rendering short clips of source and converted gestures and comparing frames.
- Document any manual tweaks in metadata to simplify future conversions.
If you want, I can:
- Generate a sample mappings.json for common VPA→VOG channel translations.
- Provide a ready-to-run Python batch script tailored to your file layout and converter CLI.
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