Video processing device, video processing method, and video processing program

Abstract

Accurate and rapid identification can be performed even when feature vectors of input pixels and background pixels are close. An image processing device includes: a feature extractor which extracts features of pixels from an input image and an input image of a different time; a quantization unit which reduces the number of gradations of features extracted by the feature extractor; a learning unitwhich learns combinations of the features of pixels through a machine learning algorithm that performs nonlinear identification and constructs a network according to machine learning; an LUT generatorwhich generates an LUT that replaces arithmetic operations of the network constructed by the learning unit; a foreground region estimatorwhich rapidly estimates similarity of each pixel of the input image to a foreground by referring to the LUT generated by the LUT generator; and a boundary correctorwhich classifies regions similar to the foreground estimated by the foreground region estimatorinto the foreground, a background, and an unclassified region including boundary pixels of the foreground and the background and performs boundary correction only on the unclassified region.