1. A representative feature extraction system which selects a representative feature from an input data group, the system comprising: input means that receives the input data group comprising an input image; occurrence distribution memory means that stores an occurrence distribution which is estimated with respect to feature quantities assumed to be input; evaluation value calculation means that calculates, with respect to each of data items in the data group, a sum of distances to other data items included in the data group based on the occurrence distribution, to determine an evaluation value for each of the data items, the distance being a value representing a degree of similarity; data selecting means that selects the data item having a smallest evaluation value as a representative feature of the data group; and a detecting means that detects a partial portion of the input image based on comparison with the representative feature, wherein said evaluation value calculation means determines, with respect to a pattern calculated according to the occurrence distribution, the distance between two data items as a value according to a product of a probability of a plurality of data value of a plurality of components of the feature quantities on the pattern existing between the values of the two data items.