Input-augmented Taylor expansion (IATE) Kalman filter for robust visual object tracking

Key Points

• Robust visual object tracking is achieved with the input-augmented Kalman filter, enhancing tracking accuracy.
• The input-augmented model utilizes Taylor expansion techniques to improve performance in dynamic environments.
• An observational analysis was conducted, demonstrating the benefits of the method in various tracking scenarios.
• The findings may enable better object tracking strategies, suggesting further exploration of this approach.