27. The apparatus according to claim 19 , wherein the update unit selects, every given number of selection times, a state parameter of a weak classifier at a current timing as a state parameter to be updated even when a performance of the weak classifier at the current timing is lower than a previous performance, upon updating the state parameter of the weak classifier.
19. 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: a model generation unit configured to generate a weak classifier model as a basis of a weak classifier based on a plurality of data for learning, in each of which whether or not the specific pattern is included is given; an update unit configured to update state parameters of a weak classifier generated based on the weak classifier model generated by the model generation unit until the weak classifier satisfies a predetermined performance; and a management unit configured to manage an update history of the state parameters of the weak classifier in each stage updated by the update unit, wherein the update unit selects and updates a state parameter of a stage to be updated of the weak classifier from the update history managed by the management unit based on a performance evaluation result of the weak classifier.