21-Keypoint Hand Pose Tracking

Skeletal finger joint 3D coordinate tracking for bimanual manipulation modeling.

TYPE SPECIFIC TELEMETRY INSPECTOR • 50Hz PASS: GROUND TRUTH VERIFIED

Quality & Precision Benchmarks

3D JOINT ERROR

< 2.4 mm

OCCLUSION RECOVERY

98.7%

Dataset Taxonomy & Output Structure

wrist_0

thumb_1..4

index_5..8

Specific Type Tasks & Applications

• Fine Motor Skill Learning
• Gesture Recognition

4-Stage Capture & Validation Process

1. Hardware Rig Setup
Calibration & zero-drift test

2. Field Execution
50Hz operator task capture

3. 3-Tier QA Audit
Sub-millisecond verification

4. Secure Delivery
HDF5/Parquet cloud export

What Is Right vs What Is Wrong

COMMON COMPETITOR ERRORS (WRONG)	BLUE PROJECTS GROUND TRUTH (RIGHT)
FAIL: 2D hand box without joint coordinates	PASS: 3D 21-keypoint skeletal finger joint tracking
FAIL: Self-occluded finger keypoints ignored	PASS: Temporal skeletal tracking resolving hand self-occlusions

Files & Telemetry Data Example (Python `h5py`)

import h5py
import numpy as np

# Load Blue Projects Type Dataset
with h5py.File('21-keypoint-hand-pose-tracking_episode_001.h5', 'r') as f:
    joint_data = np.array(f['observations/qpos'])
    print("Loaded joint data shape:", joint_data.shape)

Network Footprint of Blue Projects

Blue Projects operates a dedicated 1,200 sq ft capture studio in Davanagere, Karnataka, India, paired with pan-India field operations. All datasets are captured in-house under strict MSME, GeM, and GDPR/DPDP compliant protocols.

Why Blue Projects for 21-Keypoint Hand Pose Tracking?

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