Annotation
Skeletal Keypoint Annotation

Precision pose estimation for human activity recognition

Professional skeletal keypoint labeling for pose estimation, human activity analysis, and motion tracking. Power sports analytics, fitness applications, and gesture recognition with accurate joint annotations.

  • 17+ keypoint models
  • Multi-person tracking
  • Occlusion handling
TRUSTED BY
Peloton
Nike
Strava
Under Armour
Fitbit
Garmin

Annotation Capabilities

Comprehensive skeletal keypoint annotation

Advanced pose estimation annotation for human activity recognition and motion analysis

Sports Analytics

Track athlete movements and analyze form for performance optimization and injury prevention.

  • Movement analysis
  • Form correction
  • Performance metrics
Fitness & Wellness

Power fitness apps with real-time pose tracking for exercise guidance and rep counting.

  • Exercise tracking
  • Rep counting
  • Form validation
Gesture Recognition

Enable touchless interfaces and sign language recognition with precise hand and body tracking.

  • Hand gesture detection
  • Sign language
  • Touchless control
Healthcare & Rehabilitation

Monitor patient movement for physical therapy, gait analysis, and mobility assessment.

  • Gait analysis
  • Rehabilitation tracking
  • Mobility assessment
Gaming & Entertainment

Create immersive gaming experiences and motion-capture for animation and virtual characters.

  • Motion capture
  • Character animation
  • Full-body tracking
Activity Recognition

Classify human activities and behaviors for security, surveillance, and behavioral analysis.

  • Action classification
  • Behavior analysis
  • Crowd monitoring

Our Process

How skeletal keypoint annotation works

A meticulous workflow for precise joint localization and pose tracking

STEP 1

Upload Media

Upload images or video frames containing human figures for annotation

STEP 2

Define Skeleton

Specify keypoint schema (COCO 17, MPII, custom) and annotation standards

STEP 3

Mark Keypoints

Expert annotators precisely mark joint locations and handle occlusions

STEP 4

Quality Review

Multi-layer QA verifies keypoint accuracy and pose consistency

Pose estimation at scale

Powering human activity recognition systems worldwide

30M+

Poses annotated

17+

Keypoint schemas

99.5%

Joint accuracy

Multi

Person tracking

Use Cases

Skeletal annotation across industries

Enabling human pose estimation for diverse applications

Sports Analytics

Performance & form analysis

Fitness Apps

Exercise tracking & guidance

Healthcare

Rehabilitation & gait analysis

Gesture Control

Touchless interfaces

Gaming

Motion capture & animation

Activity Recognition

Behavior classification

Video Analysis

Temporal pose tracking

Security

Surveillance & monitoring

Ready to enable pose estimation?

Get professional skeletal keypoint annotations for your sports analytics, fitness, and human activity recognition projects.

Skeletal Keypoint FAQs

Common questions about our pose estimation annotation services

We support all major keypoint schemas including COCO 17-point, MPII 16-point, OpenPose 18/25-point, MediaPipe 33-point, and custom schemas. Each includes anatomical landmarks like shoulders, elbows, wrists, hips, knees, and ankles. We can also annotate facial keypoints (68-point) and hand keypoints (21-point) for detailed gesture recognition.

Our expert annotators are trained to estimate occluded joint positions based on visible body parts and anatomical constraints. We mark occluded keypoints with visibility flags (visible, occluded, or not visible) so your models can learn to handle partial visibility. For video sequences, we use temporal context from adjacent frames to improve occlusion estimates.

Yes, we specialize in multi-person pose estimation annotation. Each person receives a separate skeleton with unique ID tracking, essential for crowd scenes, sports team analysis, and social interaction studies. We handle challenging scenarios like overlapping people, group activities, and dense crowds while maintaining individual identity tracking.

We achieve 99.5% accuracy for keypoint localization, measured as pixel-level precision within acceptable anatomical constraints. Our multi-layer QA process includes cross-validation between annotators, anatomical consistency checks, and symmetry verification for bilateral joints. We provide confidence scores for each keypoint to indicate annotation certainty.

Yes, we offer temporal pose tracking for video sequences where keypoints are tracked frame-by-frame with consistent IDs. This enables motion analysis, activity recognition, and gesture tracking over time. We can annotate at various frame rates and handle motion blur, rapid movements, and camera motion common in sports and activity videos.

We provide skeletal keypoint annotations in COCO JSON format, OpenPose JSON, MPII format, MediaPipe format, and custom JSON with pixel coordinates, visibility flags, and confidence scores. For video data, we support temporal tracking formats with frame-by-frame keypoint sequences and unique person IDs across frames.