Estimating the pose of an object in a distributed camera network

A. Jorstad; P. Burlina; I. J. Wang; D. Lucarelli; D. DeMenthon; R. Tron; A. Terzis; R. Vidal

Estimating the pose of an object in a distributed camera network

A. Jorstad, P. Burlina, I. J. Wang, D. Lucarelli, D. DeMenthon, R. Tron, A. Terzis, R. Vidal

Research output: Contribution to journal › Article › peer-review

Abstract

A study was conducted to estimate the pose of an object in a distributed camera network. The cameras were assumed to be internally and externally calibrated. They potentially saw a subset of the object feature points in the middle of clutter points from the background. The cameras individually recovered the object's pose by using their knowledge of the model where pose was defined to be the rotation matrix and the translation vector from a known origin that placed and oriented the object in space. These pose estimates were exchanged between neighbors, performing all updates locally to obtain a single estimate consistent across all cameras.

Original language	English (US)
Pages (from-to)	274-275
Number of pages	2
Journal	Johns Hopkins APL Technical Digest (Applied Physics Laboratory)
Volume	28
Issue number	3
State	Published - 2010
Externally published	Yes

ASJC Scopus subject areas

General Engineering
General Physics and Astronomy

Cite this

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AU - Jorstad, A.

AU - Burlina, P.

AU - Wang, I. J.

AU - Lucarelli, D.

AU - DeMenthon, D.

AU - Tron, R.

AU - Terzis, A.

AU - Vidal, R.

PY - 2010

Y1 - 2010

N2 - A study was conducted to estimate the pose of an object in a distributed camera network. The cameras were assumed to be internally and externally calibrated. They potentially saw a subset of the object feature points in the middle of clutter points from the background. The cameras individually recovered the object's pose by using their knowledge of the model where pose was defined to be the rotation matrix and the translation vector from a known origin that placed and oriented the object in space. These pose estimates were exchanged between neighbors, performing all updates locally to obtain a single estimate consistent across all cameras.

AB - A study was conducted to estimate the pose of an object in a distributed camera network. The cameras were assumed to be internally and externally calibrated. They potentially saw a subset of the object feature points in the middle of clutter points from the background. The cameras individually recovered the object's pose by using their knowledge of the model where pose was defined to be the rotation matrix and the translation vector from a known origin that placed and oriented the object in space. These pose estimates were exchanged between neighbors, performing all updates locally to obtain a single estimate consistent across all cameras.

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JF - Johns Hopkins APL Technical Digest (Applied Physics Laboratory)

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Estimating the pose of an object in a distributed camera network

Abstract

ASJC Scopus subject areas

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