1. A method for performing image based regression using boosting to infer a value of an entity that is associated with an object in an image, the method comprising: learning a regression function using boosting for a plurality of images in which for each image the associated entity is known, wherein the regression function is configured to predict a value of the entity associated with the object from a continuous range of values; and using the learned regression function to predict the value of the entity associated with the object in an image in which the entity is not known, wherein learning the regression function using boosting further comprises: approximating the regression function as an additive function; at each iteration of the boosting, adding at least one weak function having a plurality of features corresponding in number to the number of dimensions of the object into the regression function; and retaining the added weak functions that improve the predictability of the entity by the iterated regression function, wherein the method is performed by a processor.