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ECCV
2004
Springer

Estimating Intrinsic Images from Image Sequences with Biased Illumination

9 years 9 months ago
Estimating Intrinsic Images from Image Sequences with Biased Illumination
We present a method for estimating intrinsic images from a fixed-viewpoint image sequence captured under changing illumination directions. Previous work on this problem reduces the influence of shadows on reflectance images, but does not address shading effects which can significantly degrade reflectance image estimation under the typically biased sampling of illumination directions. In this paper, we describe how biased illumination sampling leads to biased estimates of reflectance image derivatives. To avoid the effects of illumination bias, we propose a solution that explicitly models spatial and temporal constraints over the image sequence. With this constraint network, our technique minimizes a regularization function that takes advantage of the biased image derivatives to yield reflectance images less influenced by shading.
Yasuyuki Matsushita, Stephen Lin, Sing Bing Kang,
Added 15 Oct 2009
Updated 15 Oct 2009
Type Conference
Year 2004
Where ECCV
Authors Yasuyuki Matsushita, Stephen Lin, Sing Bing Kang, Heung-Yeung Shum
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