Robust Visual Recognition of Color Images Rozenn Dahyot, Pierre

Abstract

In this paper a robust pattern recognition system, using an appearance-based representation of colour images is described. Standard appearance-based approaches are not robust to outliers, occlusions or segmentation errors. The approach proposed here relies on robust M-estimators, involving non-quadratic and possibly non-convex energy functions. To deal with the minimisation of non-convex functions in a deterministic framework, we introduce an estimation scheme relying on M-estimators used in continuation, from convex functions to hard redescending nonconvex estimators. At each step of the robust estimation scheme, the non-quadratic criterion is minimized using the half-quadratic theory. This leads to a weighted least squares algorithm, which is easy to implement. The proposed robust estimation scheme does not require any user interaction because all necessary parameters are previously estimated. The method is illustrated on a road sign recognition application. Experiments show significant improvements with respect to standard estimation schemes.