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Body Pose Keypoint Tracking

Human pose estimation is a fundamental building block for modern computer vision systems. Labellerr introduces Body Pose Keypoint Tracking with support for up to 33 body keypoints, helping teams create richer skeletal annotations for full-body understanding tasks. This enables more structured human pose labeling and better representation of body movement, alignment, posture, and positional relationships.

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Key Features

  • 33-Point Pose Annotation: Maps all critical body joints, including shoulders, elbows, wrists, hips, knees, ankles, and facial landmarks (eyes, nose, ears).
  • Connected Skeleton Structure: Visualizes spatial and anatomical relationships directly on the labeling canvas.
  • Pose Presets: Quickly start labeling with pre-configured skeletal structures tailored for pose estimation workflows.
  • Enhanced Precision: Designed to handle complex human body movements, varied camera angles, and distance variations.

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Step-by-Step Guide: Using Body Pose Keypoint Tracking

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1. Set Up the Pose Template

  • Go to the Label Configuration settings of your project.
  • Click Add Object, name the label (e.g., person or pose), and select Keypoint as the tool type.
  • Choose the Body Pose Preset (33 Points) to instantly load the standardized skeleton layout.
  • Click Save to confirm.

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2. Placing the Pose Skeleton

  • Select the pose label from the annotation sidebar.
  • Click on the person in the image/frame to overlay the skeleton.
  • Drag and place individual keypoint nodes (such as the elbows, knees, or shoulders) onto their corresponding anatomical landmarks.

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3. Verification & Fine-Tuning

  • Toggle connecting lines to verify that limbs and joints are connected correctly.
  • Use Attribute Filtering to isolate and audit pose annotations across large datasets, ensuring metadata consistency.

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Use Cases

  • Pose Estimation Training: Building datasets to train deep learning models on human joint detection.
  • Fitness & Movement Analysis: Analyzing body alignment, squats, or yoga poses in fitness coaching apps.
  • Sports Performance Tracking: Tracking athlete movements, posture, and techniques for analytics.
  • Safety Monitoring: Detecting falls or unsafe postures in industrial and healthcare environments.
  • Human Behavior Analysis: Enhancing security and retail analytics through posture and movement interpretation.