Federated Filter Algorithm with Positioning Technique Based on 3D Sensor

Somatosensory control based on 3D sensors has been widely used as a virtual reality and motion capture technology in large-screen human–computer interactive systems. However, many issues still exist in human–computer interactive systems, such as inaccuracies of target tracking and poor anti-jamming performance. A federated tracking filtering algorithm is proposed in this paper to address these problems. The algorithm first pretreats the original data with dynamic adaptive filtering and an unscented Kalman filter and then applies a mean shift clustering algorithm on the preprocessed data. Experiments show that the correct tracking rate can reach 95.3% when the measured points are 200, while the correct tracking rate of mean shift algorithm is 90.7%. Furthermore, the noise points are found to be almost completely filtered by comparing the depth image before and after filtering. The federated tracking filtering algorithm is shown to guarantee accurate target tracking and excellent anti-jamming performance, and can significantly improve the interactive experience.