Kevin W. Bowyer

The Space Envelope

This work introduces the space envelope, a shape model based upon a boundary description. Instead of modeling a single object (or solid), a space envelope encloses a volume of empty space. The advantage is that in any given view, there may be any number of objects, this number being difficult to determine from pixel-data alone. However, there is always one, and only one, volume of visible empty space. Once a model has been constructed defining the space envelope, higher-order operations may be applied to reason about the scenes content. For instance, surface geometries and topology could yield insight into the number of visible objects. The enclosed empty volume may also be used for vision-based navigation (known free-space), while the surfaces are used for view correspondences.Algorithms to automatically construct a planar boundary representation (b-rep) space envelope from a range image are presented. Results for testing the algorithms on over 400 images from four different range cameras are presented.

Range image segmentation: the user's dilemma

A methodology for evaluating range image segmentation algorithms is proposed. This methodology involves (a) a common set of images that have manually specified ground truth and (b) a set of defined performance metrics for instances of correctly segmented, missed and noise regions, over- and under-segmentation, and accuracy of the recovered geometry. A tool is used to objectively compare a machine generated segmentation against the specified ground truth. Three research groups have contributed to evaluate their own algorithm for segmenting a range image into planar patches.