Abstract: The first step in camera calibration is to make a right choice of the camera model. Traditional ways of the model selection share an obvious limitation by mainly relying on a single evaluation measure, i.e. the reconstruction precision, to estimate a model's soundness. In this paper, aiming at the comparison and selection of different cameral models, we define and analyze three evaluation measures. The first one is the 3D reconstruction precision and generalization capability, measuring not only the reconstruction error for calibrated points but also the adaptability on points deviated from the calibrated ones; the second one is the stability, describing the extent to which the calibration result depends on the spatial distribution of the points; the third one is the uncertainty which reflects the randomness of one trial of calibration. These three measures are mutually complementary, and the stability and uncertainty can be directly estimated through the calibration result without reconstruction. Finally, intensive experiments on three cameras with eight distortion models are conducted to verify the validity and feasibility of three proposed evaluation measures, which offers a helpful guidance for the selection of camera models.