Cavlectometry: Towards holistic reconstruction of large mirror objects

Jonathan Balzer; Daniel Acevedo-Feliz; Stefano Soatto; Sebastian G. Höfer; Markus Hadwiger; Jürgen Beyerer

doi:10.1109/3DV.2014.85

Cavlectometry: Towards holistic reconstruction of large mirror objects

Jonathan Balzer, Daniel Acevedo-Feliz, Stefano Soatto, Sebastian G. Höfer, Markus Hadwiger, Jürgen Beyerer

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

10 Scopus citations

Abstract

We introduce a method based on the deflectometry principle for the reconstruction of specular objects exhibiting significant size and geometric complexity. A key feature of our approach is the deployment of an Automatic Virtual Environment (CAVE) as pattern generator. To unfold the full power of this experimental setup, an optical encoding scheme is developed which accounts for the distinctive topology of the CAVE. Furthermore, we devise an algorithm for detecting the object of interest in raw deflectometric images. The segmented foreground is used for single-view reconstruction, the background for estimation of the camera pose, necessary for calibrating the sensor system. Experiments suggest a significant gain of coverage in single measurements compared to previous methods. © 2014 IEEE.

Original language	English (US)
Title of host publication	2014 2nd International Conference on 3D Vision
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	448-455
Number of pages	8
ISBN (Print)	9781479970018
DOIs	https://doi.org/10.1109/3DV.2014.85
State	Published - Dec 2014

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10.1109/3DV.2014.85

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@inproceedings{b4656b800456405e8aec9719b0b41049,

title = "Cavlectometry: Towards holistic reconstruction of large mirror objects",

abstract = "We introduce a method based on the deflectometry principle for the reconstruction of specular objects exhibiting significant size and geometric complexity. A key feature of our approach is the deployment of an Automatic Virtual Environment (CAVE) as pattern generator. To unfold the full power of this experimental setup, an optical encoding scheme is developed which accounts for the distinctive topology of the CAVE. Furthermore, we devise an algorithm for detecting the object of interest in raw deflectometric images. The segmented foreground is used for single-view reconstruction, the background for estimation of the camera pose, necessary for calibrating the sensor system. Experiments suggest a significant gain of coverage in single measurements compared to previous methods. {\textcopyright} 2014 IEEE.",

author = "Jonathan Balzer and Daniel Acevedo-Feliz and Stefano Soatto and H{\"o}fer, {Sebastian G.} and Markus Hadwiger and J{\"u}rgen Beyerer",

note = "KAUST Repository Item: Exported on 2020-10-01",

year = "2014",

month = dec,

doi = "10.1109/3DV.2014.85",

language = "English (US)",

isbn = "9781479970018",

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T1 - Cavlectometry: Towards holistic reconstruction of large mirror objects

AU - Balzer, Jonathan

AU - Acevedo-Feliz, Daniel

AU - Soatto, Stefano

AU - Höfer, Sebastian G.

AU - Hadwiger, Markus

AU - Beyerer, Jürgen

N1 - KAUST Repository Item: Exported on 2020-10-01

PY - 2014/12

Y1 - 2014/12

N2 - We introduce a method based on the deflectometry principle for the reconstruction of specular objects exhibiting significant size and geometric complexity. A key feature of our approach is the deployment of an Automatic Virtual Environment (CAVE) as pattern generator. To unfold the full power of this experimental setup, an optical encoding scheme is developed which accounts for the distinctive topology of the CAVE. Furthermore, we devise an algorithm for detecting the object of interest in raw deflectometric images. The segmented foreground is used for single-view reconstruction, the background for estimation of the camera pose, necessary for calibrating the sensor system. Experiments suggest a significant gain of coverage in single measurements compared to previous methods. © 2014 IEEE.

AB - We introduce a method based on the deflectometry principle for the reconstruction of specular objects exhibiting significant size and geometric complexity. A key feature of our approach is the deployment of an Automatic Virtual Environment (CAVE) as pattern generator. To unfold the full power of this experimental setup, an optical encoding scheme is developed which accounts for the distinctive topology of the CAVE. Furthermore, we devise an algorithm for detecting the object of interest in raw deflectometric images. The segmented foreground is used for single-view reconstruction, the background for estimation of the camera pose, necessary for calibrating the sensor system. Experiments suggest a significant gain of coverage in single measurements compared to previous methods. © 2014 IEEE.

UR - http://hdl.handle.net/10754/575828

UR - http://ieeexplore.ieee.org/document/7035857/

UR - http://www.scopus.com/inward/record.url?scp=84925310816&partnerID=8YFLogxK

U2 - 10.1109/3DV.2014.85

DO - 10.1109/3DV.2014.85

M3 - Conference contribution

SN - 9781479970018

SP - 448

EP - 455

BT - 2014 2nd International Conference on 3D Vision

PB - Institute of Electrical and Electronics Engineers (IEEE)

ER -

Cavlectometry: Towards holistic reconstruction of large mirror objects

Abstract

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