An Improved Rotation-based Self-calibration

Purely rotation-based self-calibration receives the most attention among various self-calibration methods owing to its algorithmic simplicity. However, it is actually impossible to ensure that the camera motion for this kind of self-calibration is a pure rotation. Thus, significant errors of calibrating results could be inevitably introduced because of ignoring nonzero translation. In this paper, we propose a practical and effective approach to improve the purely rotation-based self-calibration approach. According to the fact that the rotational angles between images have a very strong impact on the calibrating errors from the translations, we compute the rotational angles between images prior to calibrating, and then use different and very appropriate strategies for self-calibration in different angle circumstances. Real data has been used to validate the proposed approach.