We present a generative model based method for recovering both the shape and the reflectance of the surface(s) of a scene from multiple images, assuming that illumination conditions are known in advance. Based on a variational framework and via gradient descents, the algorithm minimizes simultaneously and consistently a global cost functional with respect to both shape and reflectance. Contrary to previous works which consider specific individual scenarios, our method applies to a number of scenarios - mutiview stereovision, multiview photometric stereo, and multiview shape from shading. In addition, our approach naturally combines stereo, silhouette and shading cues in a single framework and, unlike most previous methods dealing with only Lambertian surfaces, the proposed method considers general dichromatic surfaces. © 2009 Springer Berlin Heidelberg.
CITATION STYLE
Yoon, K. J., Prados, E., & Sturm, P. (2009). Generic scene recovery using multiple images. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5567 LNCS, pp. 745–757). https://doi.org/10.1007/978-3-642-02256-2_62
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