An Interactive Approach to Solving Correspondence Problems

被引:0
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作者
Stefanie Jegelka
Ashish Kapoor
Eric Horvitz
机构
[1] UC Berkeley,
[2] Microsoft Research Redmond,undefined
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关键词
Human interaction; Active learning; Value of information; Matching; Correspondence problems;
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摘要
Finding correspondences among objects in different images is a critical problem in computer vision. Even good correspondence procedures can fail, however, when faced with deformations, occlusions, and differences in lighting and zoom levels across images. We present a methodology for augmenting correspondence matching algorithms with a means for triaging the focus of attention and effort in assisting the automated matching. For guiding the mix of human and automated initiatives, we introduce a measure of the expected value of resolving correspondence uncertainties. We explore the value of the approach with experiments on benchmark data.
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页码:49 / 58
页数:9
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