> ## Documentation Index
> Fetch the complete documentation index at: https://docs.labellerr.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Hand Keypoint Tracking

> Learn how Labellerr's Hand Keypoint Tracking supports up to 21 points for precise hand and finger gesture annotation on images and videos.

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# Hand Keypoint Tracking

Precise hand annotation is a critical requirement for many computer vision applications, especially in scenarios involving gesture interpretation, hand-object interaction, and egocentric understanding.

Labellerr supports **Hand Keypoint Tracking** across both images and videos with up to **21 keypoints per hand**, enabling teams to create detailed and structured annotations for hand movement and articulation. This enhancement allows annotation teams to define fine-grained hand positions with greater consistency, making it easier to build high-quality datasets for motion-centric AI workflows.

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## Key Features

* **21-Point Skeletal Mapping:** Captures the complete skeletal structure of the hand, including the wrist and five fingers with all joint articulations.
* **Image & Video Compatibility:** Supports tracking across both static images and video timelines, maintaining temporal consistency.
* **Preset Support:** Redesigned template setups allow teams to use standard hand presets without manual layout configuration.
* **Egocentric Video Optimization:** Built specifically to support first-person views and handle complex rotations, occlusions, and hand-object interactions.

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## Step-by-Step Guide: Using Hand Keypoint Tracking

### 1. Configure the Hand Keypoint Template

* Navigate to the **Label Configuration** section in your project setup.
* Click on **Add Object**, enter a label name (e.g., `hand`), and select the **Keypoint** type.
* Choose the **Hand Preset (21 Points)** from the template presets. This automatically generates the skeletal structure with predefined wrist and finger joint landmarks.
* Click **Save** to apply the template to your project.

### 2. Positioning the Keypoints

* Open the labeling screen and select the `hand` label.
* Click on the canvas to place the hand keypoint skeleton.
* Adjust individual keypoints (e.g., finger tips, knuckles, wrist joint) to precisely align with the subject's hand structure.

### 3. Tracking Across Video Frames

* For video projects, select the hand annotation on the canvas.
* Right-click and choose **Hand Tracking** (or use the keypoint tracking controls) to automatically propagate the skeleton across subsequent frames.
* Review the tracked frames and manually adjust keypoints if there are minor drift issues caused by fast movements or severe occlusions.

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## Use Cases

* **Gesture Recognition:** Training models to interpret hand signs, gestures, and user interface controls.
* **Human-Computer Interaction (HCI):** Capturing interactions in AR/VR and smart devices.
* **Robotics:** Annotating hand movements for robotic manipulation and training.
* **Egocentric Workflows:** Annotating tasks filmed from a first-person perspective, such as assembly lines, medical surgeries, or cooking tutorials.
* **Sign Language Interpretation:** Capturing fine-grained finger spelling and movements for translation systems.