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What's so good about quadrature filters?
被引:0
|作者:
Knutsson, H
[1
]
Andersson, M
[1
]
机构:
[1] Linkoping Univ, Dept Biomed Engn, Linkoping, Sweden
关键词:
D O I:
暂无
中图分类号:
TP18 [人工智能理论];
学科分类号:
081104 ;
0812 ;
0835 ;
1405 ;
摘要:
The paper argues for the use of quadrature filters for local structure tensor and motion estimation. The question of which properties of a local motion estimator are important is discussed. Answers are provided via the introduction of a number of fundamental invariances that are required in object motion estimation. A combination of statistical and deterministic modeling leads to mathematical formulations corresponding to the required invariances. The discussion leads up to the introduction of a new class of filter sets loglets. A number of experiments support the claim that loglets are preferable to other designs. In particular it is demonstrated that the loglet approach outperforms a Gaussian derivative approach in resolution and robustness to variations in object illumination.
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页码:61 / 64
页数:4
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