Abstract for wong_phd_thesis

PhD Thesis, University of Cambridge


Kwan-Yee Kenneth Wong

Silhouettes (or outlines) are often a dominant image feature, and can be extracted relatively easily and reliably. They provide rich information about both the shape and motion of an object, and are indeed the only information available in the case of smooth textureless surfaces. Nonetheless, due to the viewpoint dependence of silhouettes, they do not readily provide point correspondences, and hence structure and motion from silhouettes has been a challenging problem.

This dissertation first studies the static properties of silhouettes. By relating the idea of camera calibration from vanishing points to the symmetry property exhibited in the silhouettes of surfaces of revolution (SOR), a novel technique for estimating the intrinsic parameters of a camera from 2 or more silhouettes of SOR has been developed. Besides, a simple algorithm for recovering the 3D shape of a SOR using its silhouette from a single view is presented, followed by an analysis of the ambiguity in the reconstruction.

This dissertation then studies the dynamic properties of silhouettes, and introduces a complete and practical system for generating high quality 3D models from a sequence of 2D silhouettes. The input to the system is an image sequence of an object under both unknown circular motion and unknown general motion. By exploiting a simple parameterization of the fundamental matrix, circular motion can be estimated easily and accurately from the silhouettes. The registration of arbitrary general views, using silhouettes from the estimated circular motion, reveals information which is concealed under circular motion, and greatly improves both the shape and textures of the 3D models. In contrast to previous techniques, only the 2 outer epipolar tangents to the silhouettes are required in estimating both the circular and general motion, making the system practical in virtually all situations.

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