Kalman Filter Implementation for Object Tracking
VerifiedAdded on 2024/05/23
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AI Summary
This document details the implementation of a Kalman filter for object tracking in a video sequence. The algorithm is designed to estimate the position of a moving object, specifically a ball, by incorporating noisy measurements from a camera. The implementation involves several key steps: 1) Kalman filter prediction and update, 2) Object detection using image processing techniques, 3) Extraction of the ball's center and radius, and 4) Background subtraction to isolate the ball from the surrounding environment. The document includes detailed code snippets, flowcharts, and illustrative figures to explain the process. The results demonstrate the effectiveness of the Kalman filter in providing accurate and robust object tracking, even in the presence of noise and uncertainties.
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