12. The method for multi-class classifier threshold-offset estimation as set forth in claim 11 , further comprising an act of: generating a vote designating the set of input features as belonging to one object class of each pair of the plurality of object classes M or the other to generate a set of votes; collecting the set of votes to determine which object class of the plurality of object classes M received a majority of the set of votes; classifying the set of input features as belonging to the object class receiving the majority of the set of votes.
12. The method for multi-class classifier threshold-offset estimation as set forth in claim 11 , further comprising an act of: generating a vote designating the set of input features as belonging to one object class of each pair of the plurality of object classes M or the other to generate a set of votes; collecting the set of votes to determine which object class of the plurality of object classes M received a majority of the set of votes; classifying the set of input features as belonging to the object class receiving the majority of the set of votes. 14. The method for multi-class classifier threshold-offset estimation as set forth in claim 12 , further comprising acts of: extracting an area under the ROC curve (AUC) to determine a true-positive (TP) rate for a given false-positive rate; and defining the objective function as: 
 f 2 ( x )= AUC 1 ( r ′( x ))* AUC 2 ( r ′( x ))* AUC 3 ( r ′( x ))* . . . , wherein each subscript denotes an object class and * denotes multiplication.