DeepMotion

Converts standard video footage into realistic 3D skeletal body animations by analyzing human movement patterns frame-by-frame. Uses AI-driven pose estimation to extract motion data without requiring specialized mocap hardware or studio infrastructure.

Exports captured motion data in industry-standard formats (FBX, BVH) that are natively compatible with major 3D engines and animation software. Enables seamless integration of AI-generated animations into existing game development and animation pipelines.

Analyzes video frames to detect and estimate the 3D position and orientation of major body joints and segments in real-time. Provides frame-by-frame skeletal tracking that forms the foundation for animation generation.

Attempts to capture hand position and finger movements from video footage. Provides basic hand animation data, though with lower fidelity compared to full-body capture.

Processes video containing multiple people and attempts to extract separate motion data for each performer. Enables group animation and multi-character scene capture from single video.

Provides a free tier that allows creators to test motion capture quality and functionality before committing to paid plans. Enables evaluation of whether the tool meets specific animation needs.

Provides immediate visual feedback of captured motion applied to a 3D character model. Allows creators to review animation quality and accuracy before final export.

Analyzes input video and provides feedback on factors affecting capture quality such as lighting, body visibility, clothing, and camera angle. Helps users optimize footage before processing.

Applies captured motion data to custom character rigs and skeletal structures. Enables reuse of motion capture data across different character models and proportions.

Processes multiple video files sequentially or in parallel to generate animations from a collection of footage. Streamlines workflow for creators with large amounts of video content.