Learning Three-Dimensional Shape Models for Sketch Recognition
Author(s)
Kaelbling, Leslie P.
Lozano-Pérez, Tomás
Date Issued
January 2005
Series/Report no.
Computer Science (CS);
Abstract
Artifacts made by humans, such as items of furniture and houses, exhibit an enormous amount of variability in shape. In this paper, we concentrate on models of the shapes of objects that are made up of fixed collections of sub-parts whose dimensions and spatial arrangement exhibit variation. Our goals are: to learn these models from data and to use them for recognition. Our emphasis is on learning and recognition from three-dimensional data, to test the basic shape-modeling methodology. In this paper we also demonstrate how to use models learned in three dimensions for recognition of two-dimensional sketches of objects.
Subjects
sketch recognition
object recognition
computer vision
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