### Abstract

We solve this typical SfS problem using belief propagation to marginalise a probabilistic model. The key novel step is in using a directional probability distribution, the Fisher-Bingham distribution. This produces a fast and relatively simple algorithm that does an effective job of both extracting details and being robust to noise. Quantitative comparisons with past algorithms are provided using both synthetic and real data.

Original language | English |
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Pages | 780-791 |

Number of pages | 12 |

Publication status | Published - 2008 |

Event | European Conference on Computer Vision - Marseille, France Duration: 12 Oct 2008 → 18 Oct 2008 Conference number: 10 |

### Conference

Conference | European Conference on Computer Vision |
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Abbreviated title | ECCV |

Country | France |

City | Marseille |

Period | 12/10/08 → 18/10/08 |

### Fingerprint

### Cite this

*Belief propagation with directional statistics for solving the shape-from-shading problem*. 780-791. Paper presented at European Conference on Computer Vision, Marseille, France.

**Belief propagation with directional statistics for solving the shape-from-shading problem.** / Fincham Haines, Tom; Wilson, Richard C.

Research output: Contribution to conference › Paper

}

TY - CONF

T1 - Belief propagation with directional statistics for solving the shape-from-shading problem

AU - Fincham Haines, Tom

AU - Wilson, Richard C

PY - 2008

Y1 - 2008

N2 - The Shape-from-Shading [SfS] problem infers shape from reflected light, collected using a camera at a single point in space only. Reflected light alone does not provide sufficient constraint and extra information is required; typically a smoothness assumption is made. A surface with Lambertian reflectance lit by a single infinitely distant light source is also typical.We solve this typical SfS problem using belief propagation to marginalise a probabilistic model. The key novel step is in using a directional probability distribution, the Fisher-Bingham distribution. This produces a fast and relatively simple algorithm that does an effective job of both extracting details and being robust to noise. Quantitative comparisons with past algorithms are provided using both synthetic and real data.

AB - The Shape-from-Shading [SfS] problem infers shape from reflected light, collected using a camera at a single point in space only. Reflected light alone does not provide sufficient constraint and extra information is required; typically a smoothness assumption is made. A surface with Lambertian reflectance lit by a single infinitely distant light source is also typical.We solve this typical SfS problem using belief propagation to marginalise a probabilistic model. The key novel step is in using a directional probability distribution, the Fisher-Bingham distribution. This produces a fast and relatively simple algorithm that does an effective job of both extracting details and being robust to noise. Quantitative comparisons with past algorithms are provided using both synthetic and real data.

M3 - Paper

SP - 780

EP - 791

ER -