1. A learning apparatus comprising: a processor: feature extracting means for extracting a feature at a feature point in a plurality of training images including a training image that contains a target object to be recognized and a training image that does not contain the target object; tentative learner generating means for generating a tentative learner for detecting the target object in an image, the tentative learner being formed from a plurality of weak learners through statistical learning using the training images and the feature obtained from the training images; and learner generating means for generating a final learner that is formed from a plurality of weak learners and that detects the target object in an image by substituting the feature into a feature function formed from at least one of the weak learners that form the tentative learner so as to obtain a new feature and performing an AdaBoost type statistical learning using the new feature and the training images, wherein the feature extracting means comprises outline feature computing means for computing an outline feature based on the training image, the outline feature computing means comprising: a first-order filter processing unit performing a filtering process on an outline feature point extracted using a first-order differential Gauss function; a second-order filter processing unit performing a filtering process on the outline feature point using a second-order differential Gauss function: and a third-order filter processing unit performing a filtering process on the outline feature point using a third-order differential Gauss function.