Optimization design of cascaded classifiers

We present two optimization algorithms for the design of a cascade of classifiers, which is becoming a popular choice for many classification problems. Both algorithms represent each node classifier of a cascade using a high-level abstraction model and attempt to jointly optimize the setting of the thresholding parameters of all the node classifiers within the cascade. We applied both algorithms to optimize the famous Viola and Jones face detector and one of them in particular greatly improved the performance. We believe both algorithms can serve as a useful post-processing process for general cascaded classifier design.