Show simple item record

Linear Object Classes and Image Synthesis from a Single Example Image

dc.date.accessioned2004-10-08T20:35:58Z
dc.date.accessioned2018-11-24T10:17:41Z
dc.date.available2004-10-08T20:35:58Z
dc.date.available2018-11-24T10:17:41Z
dc.date.issued1995-03-01en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/6635
dc.identifier.urihttp://repository.aust.edu.ng/xmlui/handle/1721.1/6635
dc.description.abstractThe need to generate new views of a 3D object from a single real image arises in several fields, including graphics and object recognition. While the traditional approach relies on the use of 3D models, we have recently introduced techniques that are applicable under restricted conditions but simpler. The approach exploits image transformations that are specific to the relevant object class and learnable from example views of other "prototypical" objects of the same class. In this paper, we introduce such a new technique by extending the notion of linear class first proposed by Poggio and Vetter. For linear object classes it is shown that linear transformations can be learned exactly from a basis set of 2D prototypical views. We demonstrate the approach on artificial objects and then show preliminary evidence that the technique can effectively "rotate" high- resolution face images from a single 2D view.en_US
dc.format.extent13231252 bytes
dc.format.extent887715 bytes
dc.language.isoen_US
dc.titleLinear Object Classes and Image Synthesis from a Single Example Imageen_US


Files in this item

FilesSizeFormatView
AIM-1531.pdf887.7Kbapplication/pdfView/Open
AIM-1531.ps13.23Mbapplication/postscriptView/Open

This item appears in the following Collection(s)

Show simple item record