1. A posture state estimation apparatus that estimates a posture state of a person on a basis of image data obtained by capturing the person, the person being an object including a plurality of parts articulated by joints, the posture state estimation apparatus comprising: a part region estimation section that detects positions of a head and shoulders of the person from the image data, and estimates a range of motion of each of at least two of the plurality of parts in the image data as a part region of each part on a basis of the detected positions; a likelihood map generation section that calculates, for each pixel or each group of pixels in the part region corresponding to each of at least the two parts, a likelihood value indicating likelihood that the part is located thereat by determining an image feature of the pixel or the group of pixels from the image data, and generates, for each of at least the two parts, a likelihood map indicating a distribution of the calculated likelihood values; and a posture state estimation section that estimates, if a level of match between a learned likelihood map and an estimated likelihood map is high, the posture state associated with the learned likelihood map as the posture state of the person, the learned likelihood map being the likelihood map associated in advance with the posture state, the estimated likelihood map being the likelihood map generated on the basis of the image data, wherein the likelihood map generation section generates the likelihood map on a basis of parallel lines in the image data, and the posture state estimation section computes the level of match using a main edge direction of the estimated likelihood map acquired from the parallel lines and a main edge direction of the learned likelihood map.