Human Motion Dataset For Animation Design

This dataset is designed to support motion classification using data collected from wearable sensors in the context of Human-Computer Interaction (HCI) integrated with biomimetic vision systems for animation design. The dataset was collected as part of a study aimed at improving real-time human motion recognition to enhance immersive experiences in Virtual Reality (VR) and Augmented Reality (AR) environments.

Dataset Description:
Participants: Data was gathered from 30 participants (15 males and 15 females), performing a variety of activities designed to simulate dynamic human movements.
Activities: The dataset includes data for activities such as:
Walking
Jumping
Arm Waving
Sports Action
Sensors: Each participant wore sensors, including accelerometers and gyroscopes, which captured motion data in 3 dimensions (X, Y, Z) for both acceleration and rotation.

Features:
Accelerometer Data (X, Y, Z): Measures acceleration along the 3 spatial axes.
Gyroscope Data (X, Y, Z): Measures rotational velocity along the 3 spatial axes.
Timestamp: The time at which each data point was recorded.