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Analysis of 3D pose data to extract volumetric and depth information from motion sequences.
Distinct from 3D Pose Estimation: Distinct from 3D Pose Estimation as it focuses on the subsequent analysis of motion and depth rather than the initial coordinate estimation.
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DeepLabCut is a deep learning toolkit for markerless 2D and 3D animal pose estimation. It functions as a motion tracking system that identifies anatomical keypoints on animals in video sequences without the need for physical markers. The framework utilizes transfer learning and a library of pre-trained weights to accelerate the training of networks for different species. It supports multi-individual identity tracking to maintain unique identities across video sequences and offers real-time pose detection for live video feeds. The system covers a broad range of computer vision capabilities, i
Provides 3D spatial motion analysis to add depth and volumetric data to markerless tracking.