Sign Language MediaPipe Keypoints for 29 Gesture Classes

Pre-extracted MediaPipe coordinates for 29 sign language and gesture classes. The dataset is hosted on Kaggle. The author, organization, and last update date are unknown.

Use Cases

• Train a sign language classifier based on pre-extracted MediaPipe keypoints.
• Benchmark gesture recognition models using a dataset of 29 classes.
• Develop real-time sign language translation systems based on skeletal keypoint data.
• Analyze human pose and hand movement patterns for specific sign language gestures.

Strengths

• Data is pre-processed into MediaPipe keypoint coordinates, which can reduce computational load for model training.
• Focuses on a specific domain of 29 sign language and gesture classes.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.

Provenance

Source

Kaggle

Collection Method

Coordinates were likely extracted using the MediaPipe framework.