7. An information processing method, executed by at least one processor of a computing device, the method comprising: performing learning of a separation learning model using an action performed by an object and an observation value of an image as learning data, the separation learning model including: a background model that is a model of the background of the image; and one or more foreground models that are models of a foreground of the image, which can move on the background, wherein the background model includes a background appearance model indicating the appearance of the background, wherein at least one among the one or more foreground models includes: a transition probability, with which a state corresponding to the position of the foreground on the background is transitioned by an action performed by the object corresponding to the foreground, for each action; and a foreground appearance model indicating the appearance of the foreground, and wherein the learning comprises: obtaining a value corresponding to the difference between the observation value of the image and an observation value observed in the separation learning model as an observation likelihood with which the observation value of the image is observed in the separation learning model; obtaining a forward probability and a backward probability using the observation likelihood and the transition probability; updating the transition probability using the forward probability, the backward probability, and the observation likelihood according to a Baum-Welch algorithm, and updating the foreground appearance model and the background appearance model using the observation value of the image; using an observation value of an area in a foreground size determined in advance at a position corresponding to the state among observation values of the image in updating the foreground appearance model; and using the observation value of the image obtained by setting the observation value of the area in the foreground size to 0 at the position corresponding to the state in updating the background appearance model.
9. The information processing method according to claim 7 , wherein the separation learning model includes a plurality of foreground models, and wherein the learning further comprises: sequentially selecting the plurality of foreground models in a target model to be learned and updating the transition probability and the foreground appearance model of the target model; and then updating the background appearance model.