Real-time Image-based RGB-D Camera Motion Tracking and Environment Mapping
Tykkälä, Tommi M. (2013-11-22)
Väitöskirja
Tykkälä, Tommi M.
22.11.2013
Lappeenranta University of Technology
Acta Universitatis Lappeenrantaensis
Julkaisun pysyvä osoite on
https://urn.fi/URN:ISBN:978-952-265-474-8
https://urn.fi/URN:ISBN:978-952-265-474-8
Tiivistelmä
In this work, image based estimation methods, also known as direct methods, are studied
which avoid feature extraction and matching completely. Cost functions use raw
pixels as measurements and the goal is to produce precise 3D pose and structure estimates.
The cost functions presented minimize the sensor error, because measurements
are not transformed or modified. In photometric camera pose estimation, 3D rotation
and translation parameters are estimated by minimizing a sequence of image based
cost functions, which are non-linear due to perspective projection and lens distortion.
In image based structure refinement, on the other hand, 3D structure is refined using a
number of additional views and an image based cost metric. Image based estimation
methods are particularly useful in conditions where the Lambertian assumption holds,
and the 3D points have constant color despite viewing angle. The goal is to improve
image based estimation methods, and to produce computationally efficient methods
which can be accomodated into real-time applications. The developed image-based 3D
pose and structure estimation methods are finally demonstrated in practise in indoor
3D reconstruction use, and in a live augmented reality application.
which avoid feature extraction and matching completely. Cost functions use raw
pixels as measurements and the goal is to produce precise 3D pose and structure estimates.
The cost functions presented minimize the sensor error, because measurements
are not transformed or modified. In photometric camera pose estimation, 3D rotation
and translation parameters are estimated by minimizing a sequence of image based
cost functions, which are non-linear due to perspective projection and lens distortion.
In image based structure refinement, on the other hand, 3D structure is refined using a
number of additional views and an image based cost metric. Image based estimation
methods are particularly useful in conditions where the Lambertian assumption holds,
and the 3D points have constant color despite viewing angle. The goal is to improve
image based estimation methods, and to produce computationally efficient methods
which can be accomodated into real-time applications. The developed image-based 3D
pose and structure estimation methods are finally demonstrated in practise in indoor
3D reconstruction use, and in a live augmented reality application.
Kokoelmat
- Väitöskirjat [1037]