Chapter 1 CAMERA CALIBRATION

Camera calibration is a necessary step in 3D computer vision in order to extract metric information from 2D images. It has been studied extensively in computer vision and photogrammetry, and even recently new techniques have been proposed. In this chapter, we review the techniques proposed in the literature include those using 3D apparatus (two or three planes orthogonal to each other, or a plane undergoing a pure translation, etc.), 2D objects (planar patterns undergoing unknown motions), 1D objects (wand with dots) and unknown scene points in the environment (self-calibration). The focus is on presenting these techniques within a consistent framework. Camera calibration is a necessary step in 3D computer vision in order to extract metric information from 2D images. Much work has been done, starting in the photogrammetry community (see [3, 6] to cite a few), and more recently in computer to cite a few). According to the dimension of the calibration objects, we can classify those techniques roughly into three categories. 3D reference object based calibration. Camera calibration is performed by observing a calibration object whose geometry in 3-D space is known with very good precision. Calibration can be done very efficiently [8]. The calibration object usually consists of two or three planes orthogonal to each other. Sometimes, a plane undergoing a precisely known translation is also used [33], which equivalently provides 3D reference points. This approach requires an expensive calibration apparatus and an elaborate setup. 2D plane based calibration. Techniques in this category requires to observe a planar pattern shown at a few different orientations [42, 31]. Different from Tsai's technique [33], the knowledge of the plane motion is not necessary. Because almost anyone can make such a calibration pattern by him/her-self, the setup is easier for camera calibration. 1D line based calibration. Calibration objects used in this category are composed of a set of collinear points [44]. As will be shown, a camera can be