Convex Optimization Based Low-Rank Matrix Completion and Recovery for Photometric Stereo and Factor Classification

@inproceedings{Wu2011ConvexOB,
  title={Convex Optimization Based Low-Rank Matrix Completion and Recovery for Photometric Stereo and Factor Classification},
  author={Lun Wu and Arvind Ganesh and Boxin Shi and Yasuyuki Matsushita and Yongtian Wang and Yi Fei Ma},
  year={2011}
}
We present a new approach to robustly solve the photometric stereo problem. We cast the problem of recovering surface normals from images taken under multiple lighting conditions as a one of recovering a low-rank matrix from missing and corrupted observations, which model many different non-Lambertian effects such as shadows and specularities. Unlike previous approaches that use least-squares or heuristic robust techniques, our method uses an advanced convex optimization technique that is… CONTINUE READING

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