1. A learning apparatus for a pattern detector, which includes a plurality of weak classifiers and detects a specific pattern from input data by classifications of the plurality of weak classifiers, comprising: an acquisition unit configured to acquire a plurality of data for learning in each of which whether or not the specific pattern is included is given; a learning unit configured to make the plurality of weak classifiers learn by making the plurality of weak classifiers detect the specific pattern from the data for learning acquired by the acquisition unit; a selection unit configured to select a plurality of weak classifiers to be composited from the weak classifiers which have learned by the learning unit; a composition unit configured to composite the plurality of weak classifiers selected by the selection unit into one composite weak classifier based on comparison between a performance of the composite weak classifier and performances of the plurality of weak classifiers; and an initialization unit configured to initialize a filter structure of the composite weak classifier after composition by superimposing filter structures of the selected plurality of weak classifiers.
12. The apparatus according to claim 1 , wherein the initialization unit superimposes the filter structures of the plurality of weak classifiers in consideration of characteristic evaluation values of the weak classifiers selected by the selection unit, and a learning result based on weights of data for learning used in learning.