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An Interactive Approach to Solving Correspondence Problems
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DOI：10.1007/s11263-013-0657-5.png)
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摘要
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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.
Keyword:
Human interaction
Active learning
Value of information
Matching
Correspondence problems
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