Proceedings of the 27th annual conference on Computer graphics and interactive techniques
Multiple view geometry in computer vision
Multiple view geometry in computer vision
Epipolar Geometry from Profiles under Circular Motion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Circular Motion Geometry Using Minimal Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
Self-calibration from turn-table sequences in presence of zoom and focus
Computer Vision and Image Understanding
Geometry of single axis motions using conic fitting
IEEE Transactions on Pattern Analysis and Machine Intelligence
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In this paper, we propose an algorithm for camera calibration from silhouettes under circular motion with an unknown constant interval angle. Unlike previous silhouette-based methods based on surface of revolution, the proposed algorithm can be applied to sparse and incomplete image sequences. Under the assumption of circular motion with a constant interval angle, epipoles of successive image pairs remain constant and can be determined from silhouettes. A pair of epipoles formed by a certain interval angle can provide a constraint on the angle and focal length. With more pairs of epipoles recovered, the focal length can be determined from the one that most satisfies the constraints and determine the interval angle concurrently. The rest of camera parameters can be recovered from image invariants. Finally, the estimated parameters are optimized by minimizing the epipolar tangency constraints. Experimental results on both synthetic and real images are shown to demonstrate its performance.