Reconstruction of Occluded region missing Gait values using various numerical methods

The occlusion of body parts during gait analysis poses significant challenges, particularly in biometric security, healthcare, and robotics applications. This paper addresses the problem of reconstructing missing gait data caused by occlusion using advanced numerical interpolation techniques. We introduce Adjusted Cubic Spline, Adjusted PCHIP, Radial Basis Function (RBF), and Kriging methods for reconstructing occluded gait data, improving upon traditional methods. A comparative analysis of these techniques shows that RBF and Kriging outperform others in terms of accuracy, with substantial improvements in Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Mean Absolute Percentage Error (MAPE). These methods significantly enhance gait analysis, offering better accuracy under occluded conditions, as demonstrated by experimental results using statistical metrics and visualizations.