Blog

Robust estimation is essential in computer vision, robotics, and navigation, aiming to minimize the impact of outlier measurements for improved accuracy. We present two Geman-McClure robust estimation solvers, FracGM and QGM, leveraging fractional programming and quadratic programming techniques. We demonstrate both solvers on spatial perception benchmark problems, outperforming existing state-of-the-art methods in both accuracy and robustness.