Extract body part regions from pose landmarks

Use This When

• Building PPE detection systems that need isolated head, hand, or torso regions for gear classification
• Analyzing specific body parts separately like checking hand safety equipment or facial features
• Creating body part datasets for training specialized classifiers
• Implementing multi-stage analysis where full-body pose feeds part-specific detectors

What It Does

• Uses pose landmarks to locate and crop specific body parts like head, hands, arms, legs, torso
• Supports configurable part selection from 17 body regions including laterality
• Offers three merge strategies: overlay masks, vertical stacking, or horizontal stacking
• Filters low-confidence parts but always keeps highest confidence detection per target

Works Best With

• Pose landmark detector → this component → PPE classifiers or part-specific analyzers
• Safety monitoring pipelines checking helmets, gloves, vests on isolated body regions
• Workflows needing consistent body part framing regardless of person position in frame

Caveats

• Depends entirely on pose landmark quality; poor pose detection yields bad crops
• Stacking methods assume parts are same scale; mixed scales produce uneven grids
• Confidence threshold filtering may discard valid parts if all detections are low confidence
• Part definitions assume standard human proportions; unusual poses may crop incorrectly