egohos-segmentation
EgoHOS - Egocentric Hand-Object Segmentation
Overview
Fine-grained hand-object segmentation system designed for egocentric (first-person) videos. EgoHOS provides pixel-level segmentation masks that precisely separate hands from objects and background, enabling detailed analysis of hand-object interactions. The system outputs colorful mask overlays that make hand regions visually distinct and easy to analyze.
Key advantage: Pixel-level accuracy for understanding hand-object boundaries and contact regions, surpassing bounding box or keypoint approaches for interaction understanding.
When to Use This Skill
This skill should be used when:
- Need pixel-accurate hand and object masks in egocentric videos
- Analyzing hand-object manipulation and interactions
- Studying contact regions between hands and objects
- Creating training data for segmentation models
- Applications requiring precise hand shape and outline
- Research in fine-grained activity recognition
- Building systems that need to understand hand-object contact
- Generating annotated videos with segmentation overlays
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