About this document
Kalman Filters in Motion Tracking by ah patel is a document available to read on EtoBox.
Kalman filters are used for motion tracking to predict and update the state of a moving object by combining noisy measurements with a prediction model. The process involves a prediction step to estimate the next state and an update step to correct this estimate based on new measurements. Applications of motion tracking include video surveillance, autonomous vehicles, gesture recognition, and sports performance analysis.
- Author
- ah patel
- Language
- EN