10. The information processing device according to claim 9 , wherein the learning further comprises: performing a reduction process for reducing an observation value from the observation value of the image by an amount used in updating of the foreground appearance model of the target model; and performing updating of the next target model using the observation value of the image that has undergone the reduction process.
11. The information processing device according to claim 10 , wherein, as the plurality of foreground models, a foreground model with an action condition having a transition probability for each action and the foreground appearance model; and a foreground model without an action condition having a transition probability irrelevant to the action and the foreground appearance model are mixed, and wherein the learning further comprises: preferentially selecting the foreground model with an action condition to the foreground model without an action condition in the target model; updating, using the observation value of the image, an assumption model assuming that the foreground appearance model of the plurality of foreground models is respectively employed as the foreground appearance model of the foreground model with an action condition selected in the target model; obtaining the observation likelihood using an assumption model of which an entropy of the transition probability is the minimum in the assumption model after updating; and updating the transition probability and the foreground appearance model of the target model using the observation likelihood.