Sensorless reconstruction of freehand 3D ultrasound data.

Freehand 3D ultrasound can be acquired without a position sensor by finding the separations of pairs of frames using information in the images themselves. Previous work has not considered how to reconstruct entirely freehand data, which can exhibit irregularly spaced frames, non-monotonic out-of-plane probe motion and significant inplane motion. This paper presents reconstruction methods that overcome these limitations and are able to robustly reconstruct freehand data. The methods are assessed on freehand data sets and compared to reconstructions obtained using a position sensor.

Reconstruction of Outdoor Sculptures from Silhouettes under Approximate Circular Motion of an Uncalibrated Hand-Held Camera

This paper presents a novel technique for reconstructing an outdoor sculpture from an uncalibrated image sequence acquired around it using a hand-held camera. The technique introduced here uses only the silhouettes of the sculpture for both motion estimation and model reconstruction, and no corner detection nor matching is necessary. This is very important as most sculptures are composed of smooth textureless surfaces, and hence their silhouettes are very often the only information available from their images. Besides, as opposed to previous works, the proposed technique does not require the camera motion to be perfectly circular (e.g., turntable sequence). It employs an image rectification step before the motion estimation step to obtain a rough estimate of the camera motion which is only approximately circular. A refinement process is then applied to obtain the true general motion of the camera. This allows the technique to handle large outdoor sculptures which cannot be rotated on a turntable, making it much more practical and flexible.

Towards a complete dense geometric and photometric reconstruction under varying pose and illumination

This paper proposes a novel framework to construct a geometric and photometric model of a viewed object that can be used for visualisation in arbitrary pose and illumination. The method is solely based on images and does not require any specialised equipment. We assume that the object has a piece-wise smooth surface and that its reflectance can be modelled using a parametric bidirectional reflectance distribution function. Without assuming any prior knowledge on the object, geometry and reflectance have to be estimated simultaneously and occlusion and shadows have to be treated consistently. We exploit the geometric and photometric consistency using the fact that surface orientation and reflectance are local invariants. In a first implementation, we demonstrate the method using a Lambertian object placed on a turn-table and illuminated by a number of unknown point light-sources. A discrete voxel model is initialised to the visual hull and voxels identified as inconsistent with the invariants are removed iteratively. The resulting model is used to render images in novel pose and illumination. © 2004 Elsevier B.V. All rights reserved.