An Alternative 3-D Shape Descriptor for Database Mining

Format:

Conference/Event

Author/Creator:

Robinette, Kathleen M., author.

Conference Name:

Digital Human Modeling for Design and Engineering Symposium (2004-06-15 : Rochester, Michigan, United States)

Language:

English

Physical Description:

1 online resource

Place of Publication:

Warrendale, PA SAE International 2004

Summary:

This research examines and compares methods for mathematically coding 3-D human shapes for shape searching in large databases. The mathematical coding is called shape description and the codes themselves are called shape descriptors. The measure of effectiveness of the shape descriptors is the ability to locate a different copy of the same person from amongst a database of thousands. The hypothesis for this study is that the automated method for deriving a compact shape descriptor developed by Paquet and Rioux (6), referred to henceforth as the Paquet Shape Descriptor (PSD), is an objective shape descriptor that can distinguish between some groups of shapes as well or better than distance type body measurement methods. The present research suggests that PSD excels in searches when body contours are the most important criterion, and offers a viable alternative when key measurement or landmark data are not available. When underlying skeletal structure is more important than surface contours, other search methods may still be preferable when available

Notes:

Vendor supplied data

Publisher Number:

2004-01-2185

Access Restriction:

Restricted for use by site license