1. An image processing apparatus comprising: an image feature outputting unit that outputs each of image features, which are formed as features of a plurality of feature points of images of each frame in data of an input moving image, in correspondence with a time of the frame; a foreground estimating unit that estimates a foreground image at a time s by executing a view transform as a geometric transform on a foreground view model having the image feature of a foreground image in the image as a parameter in regard to the image feature at the time s, and then outputs an estimated foreground view; a background estimating unit that estimates a background image at the time s by executing a view transform as a geometric transform on a background view model having the image feature of a background image in the image as a parameter in regard to the image feature at the time s, and then outputs an estimated background view; a synthesized view generating unit that generates a synthesized view by synthesizing the estimated foreground view and the estimated background view; a foreground learning unit that learns the foreground view model based on an evaluation value obtained by comparison between the synthesized view and the image feature at the time s by updating the parameter of the foreground view model based on a stochastic generation model; and a background learning unit that learns the background view model based on the evaluation value by updating the parameter of the background view model based on a stochastic generation model.
1. An image processing apparatus comprising: an image feature outputting unit that outputs each of image features, which are formed as features of a plurality of feature points of images of each frame in data of an input moving image, in correspondence with a time of the frame; a foreground estimating unit that estimates a foreground image at a time s by executing a view transform as a geometric transform on a foreground view model having the image feature of a foreground image in the image as a parameter in regard to the image feature at the time s, and then outputs an estimated foreground view; a background estimating unit that estimates a background image at the time s by executing a view transform as a geometric transform on a background view model having the image feature of a background image in the image as a parameter in regard to the image feature at the time s, and then outputs an estimated background view; a synthesized view generating unit that generates a synthesized view by synthesizing the estimated foreground view and the estimated background view; a foreground learning unit that learns the foreground view model based on an evaluation value obtained by comparison between the synthesized view and the image feature at the time s by updating the parameter of the foreground view model based on a stochastic generation model; and a background learning unit that learns the background view model based on the evaluation value by updating the parameter of the background view model based on a stochastic generation model. 2. The image processing apparatus according to claim 1 , wherein the foreground estimating unit and the background estimating unit each: calculate a posterior probability of each of a plurality of the view transforms based on the evaluation value, estimate the view transform based on the image feature and the posterior probability, and output the estimated foreground view and the estimated background view, respectively, by executing the view transforms on the view model.