1. An action estimating apparatus comprising: an image acquisition unit configured to repeatedly obtain a photographic image of an occupant of a movable object; a feature point detection unit configured to obtain feature point data indicating a position of a feature point of the occupant in the photographic image in response to obtaining of the photographic image by the image acquisition unit, the feature point being at least one predetermined point of a person's body; a model storage unit configured to store action estimation models each defining a position or a locus of the feature point in each specific action, which an occupant may perform; an action estimating unit configured to compare the feature point data obtained by the feature point detection unit with each of the action estimation models stored in the model storage unit to detect an estimated action, which is the specific action associated with the action estimation model, which is highest in a coincident degree; a manipulation signal acquisition unit configured to obtain manipulation signals each indicating that a predetermined manipulation device equipped in the movable object is manipulated; a definite action detecting unit configured to implement at least one of: detection of a specific action for manipulating the manipulation device corresponding to each of the manipulation signals from the manipulation signals, which are obtained by the manipulation signal acquisition unit, as the definite action performed by the occupant and detection of a start time when input of the manipulation signal, which corresponds to the detected definite action, starts and an end time when the input of the manipulation signal ends; and detection of a specific action, in which a hand moves from the manipulation device, which corresponds to a first manipulation signal, to the manipulation device, which corresponds to a second manipulation signal, as the definite action based on the manipulation signals, which are obtained by the manipulation signal acquisition unit, and detection of the start time when the input of the first manipulation signal ends and the end time when the input of the second manipulation signal starts; a definite action model generating unit configured to generate a new definite action estimation model by modifying a position or a locus of the feature point, which constitutes a definite action estimation model, according to an in-action feature point corresponding to each of the definite actions detected by the definite action detection unit, the in-action feature point being each of the feature point data detected by the feature point detection unit in each period from the start time to the end time detected by the definite action detection unit, the action estimation model corresponding to each of the definite actions detected by the definite action detection unit; a non-definite action model generating unit configured to generate a new non-definite action estimation model with respect to each non-definite action model stored in the model storage unit using the in-action feature point according to a predetermined correspondence between a position or a locus of the feature point when the occupant performs the definite action and a position or a locus of the feature point, which constitutes the non-definite action estimation model, which is the action estimation model corresponding to a non-definite action, wherein the definite action model corresponds to the definite action being a continuous manipulation of the manipulation device by the occupant, wherein the non-definite action model corresponds to the non-definite action being a specific action, which cannot be detected as the definite action, and is other than the definition action; and a model update unit configured to update the definite action estimation model and the non-definite action estimation model stored in the model storage unit and corresponding to the definite action estimation model generated by the definite action model generating unit and the non-definite action estimation model generated by the non-definite action model generating unit, respectively to the newly generated definite action estimation model and the newly generated non-definite action estimation model, wherein the model update unit includes an old model comparison unit configured to: compare a subsequent in-action feature point, which is the in-action feature point of the definite action, with an old definite action model of the definite action, which is the definite action estimation model stored in the model storage unit, when the definite action detecting unit subsequently detects the definite action; and determine a coincidence degree as an old model coincidence degree, wherein the model update unit further includes a new model comparison unit configured to: compare the subsequent in-action feature point with the new definite action estimation model generated by the definite action model generating unit; and determine the coincidence degree as a new model coincidence degree, wherein the model update unit is configured to perform the model update when the new model coincidence degree determined by the new model comparison unit is higher than the old model coincidence degree determined by the old model comparison unit.