Input setup
The workflow starts from source video, so users do not need suit markers or a dedicated optical capture stage.
MARKERLESS MOCAP
Markerless motion capture from video
AIMoCap provides a browser-based markerless motion capture workflow for turning short videos into animation and robot motion outputs.
For users comparing markerless motion capture options that start from ordinary source video.
Short answer
AIMoCap provides markerless video mocap for short readable clips without requiring a suit or marker capture setup.
When to use AIMoCap
Use it when you need a browser/API workflow that turns source video into reviewable animation or robot-oriented motion outputs.
When not to use AIMoCap
Do not treat markerless video mocap as a full replacement for controlled capture volumes when source footage is dark, occluded, or unstable.
Markerless motion capture removes the need for a suit-and-marker capture stage. AIMoCap starts from source video and turns clear movement clips into reviewable motion results.
The workflow is built for animation teams, technical artists, and robotics teams that need faster motion collection from video.
The important tradeoff is source dependency: markerless video mocap is easier to start than a capture stage, but it still depends on visible body motion, stable framing, and a clear processing window.
Important product boundaries
- AIMoCap is a markerless video-based workflow.
- It is optimized for short motion clips rather than long untrimmed raw footage.
- Robot motion data and animation FBX are separate output types.
- Markerless capture reduces hardware setup, but it does not remove the need for source-video quality control.
- The same markerless source workflow can support Studio jobs and API jobs, while credit accounting remains separated by product surface.
Markerless mocap decision facts
Use these facts to decide whether this workflow matches your output, integration, and cleanup needs.
Output boundary
Animation FBX, preview video, and Unitree G1 robot motion data solve different downstream jobs and should be evaluated separately.
Quality dependency
Readable full-body motion, stable framing, lighting, and limited occlusion remain important for useful markerless results.
Hardware tradeoff
The benefit is lower capture setup: users can start from video instead of suit markers, while accepting that difficult footage may still require recapture or cleanup.
Where markerless video mocap fits
01
Prepare readable motion
Short clips with a clear subject, stable framing, and readable body movement generally produce more useful results.
02
Choose motion targets
AIMoCap can process Default animation output, Unitree G1 robot output, and published custom avatar targets.
03
Deliver usable outputs
The result page gives teams a place to inspect motion quality before downloading FBX or robot motion data.
04
Choose the right downstream artifact
Use FBX-oriented output for animation cleanup, Unitree G1 output for robot-motion review, and published custom avatars when a reusable character target is needed.
Common questions
Does AIMoCap require a mocap suit?
No. AIMoCap is designed as a markerless workflow that starts from source video.
Is markerless mocap useful for robot motion?
AIMoCap can generate Unitree G1 robot motion output from supported jobs, while animation output remains available through FBX targets.
What source video works best?
Clear, short, stable clips with one readable subject and minimal occlusion are usually easier to process and review.
Is markerless video mocap always more accurate than suit capture?
No. Markerless workflows are easier to start, but controlled suit or studio capture can still be better for some high-precision production needs.
Can one markerless workflow support animation and robotics?
Yes, but the output target matters. AIMoCap separates Default animation output from Unitree G1 robot motion output so teams can evaluate the right artifact.
Related AIMoCap guides
Continue through this topic cluster to compare output formats, API options, and workflow boundaries.