### Abstract

This paper proposes a new scheme for multi-image projective reconstruction based on a projective grid space. The projective grid space is defined by two basis views and the fundamental matrix relating these views. Given fundamental matrices relating other views to each of the two basis views, this projective grid space can be related to any view. In the projective grid space as a general space that is related to all images, a projective shape can be reconstructed from all the images of weakly calibrated cameras. The projective reconstruction is one way to reduce the effort of the calibration because it does not need Euclid metric information, but rather only correspondences of several points between the images. For demonstrating the effectiveness of the proposed projective grid definition, we modify the voxel coloring algorithm for the projective voxel scheme. The quality of the virtual view images re-synthesized from the projective shape demonstrates the effectiveness of our proposed scheme for projective reconstruction from a large number of images.

Original language | English |
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Title of host publication | Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition |

Publisher | IEEE |

Pages | 49-54 |

Number of pages | 6 |

Volume | 2 |

Publication status | Published - 1999 |

Externally published | Yes |

Event | Proceedings of the 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'99) - Fort Collins, CO, USA Duration: 1999 Jun 23 → 1999 Jun 25 |

### Other

Other | Proceedings of the 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'99) |
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City | Fort Collins, CO, USA |

Period | 99/6/23 → 99/6/25 |

### Fingerprint

### ASJC Scopus subject areas

- Computer Vision and Pattern Recognition
- Software
- Control and Systems Engineering
- Electrical and Electronic Engineering

### Cite this

*Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition*(Vol. 2, pp. 49-54). IEEE.

**Shape reconstruction in projective grid space from large number of images.** / Saito, Hideo; Kanade, Takeo.

Research output: Chapter in Book/Report/Conference proceeding › Chapter

*Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition.*vol. 2, IEEE, pp. 49-54, Proceedings of the 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'99), Fort Collins, CO, USA, 99/6/23.

}

TY - CHAP

T1 - Shape reconstruction in projective grid space from large number of images

AU - Saito, Hideo

AU - Kanade, Takeo

PY - 1999

Y1 - 1999

N2 - This paper proposes a new scheme for multi-image projective reconstruction based on a projective grid space. The projective grid space is defined by two basis views and the fundamental matrix relating these views. Given fundamental matrices relating other views to each of the two basis views, this projective grid space can be related to any view. In the projective grid space as a general space that is related to all images, a projective shape can be reconstructed from all the images of weakly calibrated cameras. The projective reconstruction is one way to reduce the effort of the calibration because it does not need Euclid metric information, but rather only correspondences of several points between the images. For demonstrating the effectiveness of the proposed projective grid definition, we modify the voxel coloring algorithm for the projective voxel scheme. The quality of the virtual view images re-synthesized from the projective shape demonstrates the effectiveness of our proposed scheme for projective reconstruction from a large number of images.

AB - This paper proposes a new scheme for multi-image projective reconstruction based on a projective grid space. The projective grid space is defined by two basis views and the fundamental matrix relating these views. Given fundamental matrices relating other views to each of the two basis views, this projective grid space can be related to any view. In the projective grid space as a general space that is related to all images, a projective shape can be reconstructed from all the images of weakly calibrated cameras. The projective reconstruction is one way to reduce the effort of the calibration because it does not need Euclid metric information, but rather only correspondences of several points between the images. For demonstrating the effectiveness of the proposed projective grid definition, we modify the voxel coloring algorithm for the projective voxel scheme. The quality of the virtual view images re-synthesized from the projective shape demonstrates the effectiveness of our proposed scheme for projective reconstruction from a large number of images.

UR - http://www.scopus.com/inward/record.url?scp=0032629709&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0032629709&partnerID=8YFLogxK

M3 - Chapter

VL - 2

SP - 49

EP - 54

BT - Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

PB - IEEE

ER -