Subpixel corner detection for camera calibration

Many different interest point detectors have been proposed with a wide range of definitions for what points in an image are interesting. Corner points are interesting as they are formed from two or more edges and usually define the boundary between two different objects or parts of the same object. Interest points are generally more abundant in real images than straight edges and are considered to be the most important features, they are attractive due to their high information content and hence they are ideal features for tasks such as camera calibration, object tracking or fast interpretation of a robot´s environment. Therefore, we present a comparative study of different subpixel interest point detectors combined with the use of finding interest points using the different corner measures proposed by Harris and Stephens and Interest operator by Haralick.