Advanced Search
DSpace@MIT

Learning Three-Dimensional Shape Models for Sketch Recognition

Research and Teaching Output of the MIT Community

Show simple item record

dc.contributor.author Kaelbling, Leslie P.
dc.contributor.author Lozano-Pérez, Tomás
dc.date.accessioned 2004-12-13T06:56:19Z
dc.date.available 2004-12-13T06:56:19Z
dc.date.issued 2005-01
dc.identifier.uri http://hdl.handle.net/1721.1/7424
dc.description.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. en
dc.description.sponsorship Singapore-MIT Alliance (SMA) en
dc.format.extent 408469 bytes
dc.format.mimetype application/pdf
dc.language.iso en
dc.relation.ispartofseries Computer Science (CS);
dc.subject sketch recognition en
dc.subject object recognition en
dc.subject computer vision en
dc.title Learning Three-Dimensional Shape Models for Sketch Recognition en
dc.type Article en


Files in this item

Name Size Format Description
CS014.pdf 398.8Kb PDF

This item appears in the following Collection(s)

Show simple item record

MIT-Mirage