1. An information processing device comprising: a learning unit that performs, using an action performed by an object and an observation value of an image as learning data, learning of a separation learning model, the separation leaning 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, wherein the learning unit: obtains 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; obtains a forward probability and a backward probability using the observation likelihood and the transition probability; updates the transition probability using the forward probability, the backward probability, and the observation likelihood according to a Baum-Welch algorithm, and updates the foreground appearance model and the background appearance model using the observation value of the image; uses 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 uses 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, and wherein the learning unit is implemented via at least one processor.
1. An information processing device comprising: a learning unit that performs, using an action performed by an object and an observation value of an image as learning data, learning of a separation learning model, the separation leaning 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, wherein the learning unit: obtains 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; obtains a forward probability and a backward probability using the observation likelihood and the transition probability; updates the transition probability using the forward probability, the backward probability, and the observation likelihood according to a Baum-Welch algorithm, and updates the foreground appearance model and the background appearance model using the observation value of the image; uses 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 uses 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, and wherein the learning unit is implemented via at least one processor. 2. The information processing device according to claim 1 , wherein the separation learning model includes a plurality of foreground models, and wherein the learning unit: sequentially selects the plurality of foreground models in a target model to be learned and updates the transition probability and the foreground appearance model of the target model; and then updates the background appearance model.