1. A computer implemented method for learning part-based object models from a set of digital representations of images, the method comprising: receiving a set of digital representations of images, each image having at least one object; for each image: extracting one or more shape features from the image; extracting one or more appearance features from the image; generating one or more shape models of the object based on the shape features, a shape model corresponding to a part of the object, generating a shape model of the object comprising: generating one or more histogram of oriented gradient (HOG) cells for a number of pixel of the image; and grouping two or more HOG cells into a HOG bundle based on similarity of orientations of the HOG cells with respect to the maximum magnitude of orientations of the HOG cells; computing an appearance model for each shape model of the object based on the appearance features; selecting one or more shape models as reference shape models of the object; selecting one or more appearance models as reference appearance models of the object; and storing the reference shape models of the images; and storing the reference appearance models of the images.