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Gradient descent approach for minimizing dissimilarity measure in log-polarimagery

Gradient descent approach for minimizing dissimilarity measure in log-polarimagery
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摘要 Log-polar mapping has been proposed as a very appropriate space-variant imaging model in active vision applications.There is no doubt about the importance of translation estimation in active visual tracking.In this paper an approach is presented,and its performances are evaluated.The approach uses a gradient descent for minimizing a dissimilarity measure.The experimental results reveal that this method is efficient for approaching active image translations. Log-polar mapping has been proposed as a very appropriate space-variant imaging model in active vision applications. There is no doubt about the importance of translation estimation in active visual tracking. In this paper an approach is presented,and its performances are evaluated. The approach uses a gradient descent for minimizing a dissimilarity measure. The experimental results reveal that this method is efficient for approaching active image translations.
出处 《Optoelectronics Letters》 EI 2006年第4期302-304,共3页 光电子快报(英文版)
基金 SupportedbyNationalNaturalScienceFoundationofChina(GrantNo.60575013).
关键词 图象处理 空间变量 图象模型 视频跟踪 CLC number TP751
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