Just wrapped a 4-day motion capture dataset shoot at our studio in India. Wanted to share some behind-the-scenes since motion data is becoming increasingly critical for humanoid robot training and imitation learning.<\/p>\n
What we did:<\/p>\n
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- 12 actors<\/li>\n
- Continuous day + night shooting<\/li>\n
- Structured locomotion and action datasets<\/li>\n
- High-volume capture (1800+ sequences)<\/li>\n
- 24-hour production cycles to meet deadline<\/li>\n<\/ul>\n
What’s interesting about this:<\/p>\n
Most AI\/ML teams working on humanoid control or embodied AI are stuck with either:<\/p>\n
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- Low-quality synthetic data<\/li>\n
- Academic datasets that don’t scale<\/li>\n
- Building their own infrastructure (expensive)<\/li>\n<\/ol>\n
We realized professional motion capture studios have the infrastructure already built. So we’re now offering this as a service specifically for ML teams.<\/p>\n
The dataset we captured is structured for imitation learning \u2014 actions, locomotion, complex movements. Not cinematic. Not game-ready. Built specifically for training.<\/p>\n
If you’re working on humanoid robotics, gesture recognition, or motion-based ML models and need real human movement data, this is now available as a service.<\/p>\n
More details: www.appleartsstudios.com<\/a><\/p>\n
Happy to answer questions about dataset format, motion capture quality, or scaling.<\/p>\n<\/div>\n
submitted by \/u\/PossiblePotato961 <\/a>
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