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. 5. The information processing device according to claim 1 , wherein the observation value of the image is an observation value of a visual field area of a known visual field in the image, and wherein the learning unit: performs updating of the transition probability of the foreground model only for the transition probability from the state in which the entire area in the foreground size is included in the visual field area; and performs updating of the foreground appearance model of the foreground model and the background appearance model of the background model using the forward probability and the backward probability for the state in which the entire area in the foreground size is included in the visual field area.