Numerical evaluation of differential and semi-differential invariants

Abstract: "Soon after the appearance of Weiss's influential paper [7], I undertook a straightforward implementation of differential projective invariants. I made some experiments as a feasibility study to see qualitatively how well it seemed differential invariants could be matched. The ex...

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1. Verfasser: Brown, Christopher M. (VerfasserIn)
Format: Buch
Sprache:English
Veröffentlicht: Rochester, NY 1991
Schriftenreihe:University of Rochester <Rochester, NY> / Department of Computer Science: Technical report 393
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490 1 |a University of Rochester <Rochester, NY> / Department of Computer Science: Technical report  |v 393 
520 3 |a Abstract: "Soon after the appearance of Weiss's influential paper [7], I undertook a straightforward implementation of differential projective invariants. I made some experiments as a feasibility study to see qualitatively how well it seemed differential invariants could be matched. The experiments tried to get at the effects of limited precision in positional measurements and the effect of curve sampling needed to compute local derivatives. The conclusions are not at all surprising. More recent work has the object of making the computations robust by using measurements from different points instead of trying to compute many derivatives at a point 
520 3 |a Similar experiments were performed to compute the absolute invariants [tau] b1 s(t) and [tau] b2 s(t) of [6], which indeed are much more resistent [sic] to the effects of different sampling densities and numerical precision. 
650 4 |a Computer vision 
650 4 |a Invariants 
810 2 |a Department of Computer Science: Technical report  |t University of Rochester <Rochester, NY>  |v 393  |w (DE-604)BV008902697  |9 393 
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spelling Brown, Christopher M. Verfasser aut
Numerical evaluation of differential and semi-differential invariants Christopher M. Brown
Rochester, NY 1991
17 S.
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University of Rochester <Rochester, NY> / Department of Computer Science: Technical report 393
Abstract: "Soon after the appearance of Weiss's influential paper [7], I undertook a straightforward implementation of differential projective invariants. I made some experiments as a feasibility study to see qualitatively how well it seemed differential invariants could be matched. The experiments tried to get at the effects of limited precision in positional measurements and the effect of curve sampling needed to compute local derivatives. The conclusions are not at all surprising. More recent work has the object of making the computations robust by using measurements from different points instead of trying to compute many derivatives at a point
Similar experiments were performed to compute the absolute invariants [tau] b1 s(t) and [tau] b2 s(t) of [6], which indeed are much more resistent [sic] to the effects of different sampling densities and numerical precision.
Computer vision
Invariants
Department of Computer Science: Technical report University of Rochester <Rochester, NY> 393 (DE-604)BV008902697 393
spellingShingle Brown, Christopher M.
Numerical evaluation of differential and semi-differential invariants
Computer vision
Invariants
title Numerical evaluation of differential and semi-differential invariants
title_auth Numerical evaluation of differential and semi-differential invariants
title_exact_search Numerical evaluation of differential and semi-differential invariants
title_full Numerical evaluation of differential and semi-differential invariants Christopher M. Brown
title_fullStr Numerical evaluation of differential and semi-differential invariants Christopher M. Brown
title_full_unstemmed Numerical evaluation of differential and semi-differential invariants Christopher M. Brown
title_short Numerical evaluation of differential and semi-differential invariants
title_sort numerical evaluation of differential and semi differential invariants
topic Computer vision
Invariants
topic_facet Computer vision
Invariants
volume_link (DE-604)BV008902697
work_keys_str_mv AT brownchristopherm numericalevaluationofdifferentialandsemidifferentialinvariants