1. A system for multi-class classifier threshold-offset estimation for visual object recognition, the system comprising: one or more processors and a memory having instructions such that when the instructions are executed, the one or more processors perform operations of: receiving an input image comprising a set of input features; training a classifier for each pair of a plurality of object classes M; generating a set of classification responses r based on the set of input features; computing a multi-class receiver-operating-characteristics (ROC) curve for a set of threshold-offsets x; computing an objective function of classification performance f(x) from the ROC curve; optimizing the objective function of classification performance f(x) through particle swarm optimization to generate a set of optimized threshold-offsets x; applying the set of optimized threshold-offsets x to the set of classification responses r to generate a set of classification responses r′; and comparing each classification response in the set of classification responses r′ to a predetermined value to classify the set of input features as belonging to an object class.