1. An image processing method of simultaneously extracting a background image, at least two object images, a shape of each object image and motion of each object image, which are defined as hidden parameters, from among plural images, said image processing method comprising: an image input step of accepting input of plural images arranged in time series; a hidden parameter estimation step of estimating a hidden parameter based on the plural images and a constraint enforcement parameter, wherein the constraint enforcement parameter indicates a condition of at least one of the hidden parameters, using an iterative learning method; a constraint enforcement parameter learning step of learning a constraint enforcement parameter related to the hidden parameter using an estimation result from said hidden parameter estimation step as a training signal; a complementary learning step of causing the estimation of the hidden parameter and the learning of the constraint enforcement parameter to be iterated, the estimation of the hidden parameters being performed in said hidden parameter estimation step, which uses a learning result given in said constraint enforcement parameter learning step, and the learning of the constraint enforcement parameter being performed in said constraint enforcement parameter learning step, which uses the estimation result of the hidden parameter given in said hidden parameter estimation step; an output step of outputting the hidden parameter estimated in said hidden parameter estimation step after the iterative learning is performed in said complementary learning step; and an intermediate time image synthesis step of: receiving the background image, the object images, the shapes of the object images, and the motion of the object images, which are hidden parameters outputted in said output step, synthesizing, for each of at least two objects, an object image within an intermediate time between input images using the background image, the object images, the shapes of the object images and the motion of the object images, and synthesizing, for the object image synthesized for each of the at least two objects, an intermediate time image by superimposing the object image at the intermediate time onto the background image at the corresponding time.
1. An image processing method of simultaneously extracting a background image, at least two object images, a shape of each object image and motion of each object image, which are defined as hidden parameters, from among plural images, said image processing method comprising: an image input step of accepting input of plural images arranged in time series; a hidden parameter estimation step of estimating a hidden parameter based on the plural images and a constraint enforcement parameter, wherein the constraint enforcement parameter indicates a condition of at least one of the hidden parameters, using an iterative learning method; a constraint enforcement parameter learning step of learning a constraint enforcement parameter related to the hidden parameter using an estimation result from said hidden parameter estimation step as a training signal; a complementary learning step of causing the estimation of the hidden parameter and the learning of the constraint enforcement parameter to be iterated, the estimation of the hidden parameters being performed in said hidden parameter estimation step, which uses a learning result given in said constraint enforcement parameter learning step, and the learning of the constraint enforcement parameter being performed in said constraint enforcement parameter learning step, which uses the estimation result of the hidden parameter given in said hidden parameter estimation step; an output step of outputting the hidden parameter estimated in said hidden parameter estimation step after the iterative learning is performed in said complementary learning step; and an intermediate time image synthesis step of: receiving the background image, the object images, the shapes of the object images, and the motion of the object images, which are hidden parameters outputted in said output step, synthesizing, for each of at least two objects, an object image within an intermediate time between input images using the background image, the object images, the shapes of the object images and the motion of the object images, and synthesizing, for the object image synthesized for each of the at least two objects, an intermediate time image by superimposing the object image at the intermediate time onto the background image at the corresponding time. 2. The image processing method according to claim 1 , wherein the constraint enforcement parameter is a parameter related to at least one of the following conditions: an area size for each object image, a color of each object image, and a pixel motion that is included in each object image.