Tian-Tsong Ng, Shih-Fu Chang, Mao-Pei Tsui. Using Geometry Invariants for Camera Response Function Estimation. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), June 2007.
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In this paper, we present a new single-image camera response function (CRF) estimation method using geometry invariants (GI). We derive mathematical properties and geometric interpretation for GI, which lend insight to addressing various algorithm implementation issues in a principled way. In contrast to the previous single-image CRF estimation methods, our method provides a constraint equation for selecting the potential target data points. While the performance of our method is comparable to those in the prior work, our experiment is conducted over more extensive data and our method is flexible in that its estimation accuracy and stability can be improved whenever more than one image is available. The geometry invariance theory is novel and may be of wide interest.
@InProceedings{ng:geometryinvarint,
Author = {Ng, Tian-Tsong and Chang, Shih-Fu and Tsui, Mao-Pei},
Title = {Using Geometry Invariants for Camera Response Function Estimation},
BookTitle = {IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR)},
Month = {June},
Year = {2007}
}
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