### Abstract

We present an algorithm for fusing monocular and stereo cues to get robust estimates of both motion and structure. Our algorithm assumes the motion to be along a smooth trajectory and the sequence of images to be dense. The algorithm starts by calculating the instantaneous FOE (focus of expansion). Knowing the FOE we calculate a MAP estimate of the displacement at each pixel and an associated confidence measure. Using the displacement estimates we calculate a relative depth map from one of the two frame sequences. By calculating the disparities at some feature points and using information about their relative depths we compute the instantaneous component of velocity in the direction perpendicular to the image plane (the Z direction). Using this information a depth map is calculated, this depth map is then used to derive a prior probability distribution for disparity that is used in matching the two frames of the stereo pairs. We use this method to estimate the disparity at each pixel independently; no assumption about smoothness are used. Experimental results on a real image sequence are given.

Original language | English |
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Title of host publication | IEEE Computer Vision and Pattern Recognition |

Editors | Anon |

Place of Publication | Piscataway, NJ, United States |

Publisher | Publ by IEEE |

Pages | 321-327 |

Number of pages | 7 |

ISBN (Print) | 0818638826 |

State | Published - Dec 1 1993 |

Externally published | Yes |

Event | Proceedings of the 1993 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - New York, NY, USA Duration: Jun 15 1993 → Jun 18 1993 |

### Other

Other | Proceedings of the 1993 IEEE Computer Society Conference on Computer Vision and Pattern Recognition |
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City | New York, NY, USA |

Period | 6/15/93 → 6/18/93 |

### Fingerprint

### ASJC Scopus subject areas

- Engineering(all)

### Cite this

*IEEE Computer Vision and Pattern Recognition*(pp. 321-327). Piscataway, NJ, United States: Publ by IEEE.

**Binocular motion stereo using MAP estimation.** / Abdel-Mottaleb, Mohamed; Chellappa, Rama; Rosenfeld, Azriel.

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

*IEEE Computer Vision and Pattern Recognition.*Publ by IEEE, Piscataway, NJ, United States, pp. 321-327, Proceedings of the 1993 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, New York, NY, USA, 6/15/93.

}

TY - GEN

T1 - Binocular motion stereo using MAP estimation

AU - Abdel-Mottaleb, Mohamed

AU - Chellappa, Rama

AU - Rosenfeld, Azriel

PY - 1993/12/1

Y1 - 1993/12/1

N2 - We present an algorithm for fusing monocular and stereo cues to get robust estimates of both motion and structure. Our algorithm assumes the motion to be along a smooth trajectory and the sequence of images to be dense. The algorithm starts by calculating the instantaneous FOE (focus of expansion). Knowing the FOE we calculate a MAP estimate of the displacement at each pixel and an associated confidence measure. Using the displacement estimates we calculate a relative depth map from one of the two frame sequences. By calculating the disparities at some feature points and using information about their relative depths we compute the instantaneous component of velocity in the direction perpendicular to the image plane (the Z direction). Using this information a depth map is calculated, this depth map is then used to derive a prior probability distribution for disparity that is used in matching the two frames of the stereo pairs. We use this method to estimate the disparity at each pixel independently; no assumption about smoothness are used. Experimental results on a real image sequence are given.

AB - We present an algorithm for fusing monocular and stereo cues to get robust estimates of both motion and structure. Our algorithm assumes the motion to be along a smooth trajectory and the sequence of images to be dense. The algorithm starts by calculating the instantaneous FOE (focus of expansion). Knowing the FOE we calculate a MAP estimate of the displacement at each pixel and an associated confidence measure. Using the displacement estimates we calculate a relative depth map from one of the two frame sequences. By calculating the disparities at some feature points and using information about their relative depths we compute the instantaneous component of velocity in the direction perpendicular to the image plane (the Z direction). Using this information a depth map is calculated, this depth map is then used to derive a prior probability distribution for disparity that is used in matching the two frames of the stereo pairs. We use this method to estimate the disparity at each pixel independently; no assumption about smoothness are used. Experimental results on a real image sequence are given.

UR - http://www.scopus.com/inward/record.url?scp=0027795286&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0027795286&partnerID=8YFLogxK

M3 - Conference contribution

SN - 0818638826

SP - 321

EP - 327

BT - IEEE Computer Vision and Pattern Recognition

A2 - Anon, null

PB - Publ by IEEE

CY - Piscataway, NJ, United States

ER -