The Community for Technology Leaders
RSS Icon
Subscribe
Issue No.07 - July (2000 vol.22)
pp: 649-662
ABSTRACT
<p><b>Abstract</b>—Object recognition requires robust and stable features that are unique in feature space. Lie group analysis provides a constructive procedure to determine such features, called invariants, when they exist. Absolute invariants are rare in general, so quasi-invariants relax the restrictions required for absolute invariants and, potentially, can be just as useful in real-world applications. This paper develops the concept of a dominant-subspace invariant, a particular type of quasi-invariant, using the theory of Lie groups. A constructive algorithm is provided that fundamentally seeks to determine an integral submanifold which, in practice, is a good approximation to the orbit of the Lie group action. This idea is applied to the long-wave infrared problem and experimental results are obtained supporting the approach. Other application areas are cited.</p>
INDEX TERMS
Dominant-subspace invariants, Lie group analysis, principal basis, quasi-invariants, thermophysical invariance, thermophysical model.
CITATION
D. Gregory Arnold, Kirk Sturtz, Vince Velten, N. Nandhakumar, "Dominant-Subspace Invariants", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol.22, no. 7, pp. 649-662, July 2000, doi:10.1109/34.865182
6 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool