745 research outputs found
Exploiting Structural Regularities and Beyond: Vision-based Localization and Mapping in Man-Made Environments
Image-based estimation of camera motion, known as visual odometry
(VO), plays a very important role in many robotic applications
such as control and navigation of unmanned mobile robots,
especially when no external navigation reference signal is
available. The core problem of VO is the estimation of the
camera’s ego-motion (i.e. tracking) either between successive
frames, namely relative pose estimation, or with respect to a
global map, namely absolute pose estimation. This thesis aims to
develop efficient, accurate and robust VO solutions by taking
advantage of structural regularities in man-made environments,
such as piece-wise planar structures, Manhattan World and more
generally, contours and edges. Furthermore, to handle challenging
scenarios that are beyond the limits of classical sensor based VO
solutions, we investigate a recently emerging sensor — the
event camera and study on event-based mapping — one of the key
problems in the event-based VO/SLAM. The main achievements are
summarized as follows.
First, we revisit an old topic on relative pose estimation:
accurately and robustly estimating the fundamental matrix given a
collection of independently estimated homograhies. Three
classical methods are reviewed and then we show a simple but
nontrivial two-step normalization
within the direct linear method that achieves similar performance
to the less attractive and more computationally intensive
hallucinated points based method.
Second, an efficient 3D rotation estimation algorithm for depth
cameras in piece-wise planar environments is presented. It shows
that by using surface normal vectors as an input, planar modes in
the corresponding density distribution function can be discovered
and continuously
tracked using efficient non-parametric estimation techniques. The
relative rotation can be estimated by registering entire bundles
of planar modes by using robust L1-norm minimization.
Third, an efficient alternative to the iterative closest point
algorithm for real-time tracking of modern depth cameras in
ManhattanWorlds is developed. We exploit the common orthogonal
structure of man-made environments in order to decouple the
estimation of the rotation and the three degrees of freedom of
the translation. The derived camera orientation is absolute and
thus free of long-term drift, which in turn benefits the accuracy
of the translation estimation as well.
Fourth, we look into a more general structural
regularity—edges. A real-time VO system that uses Canny edges
is proposed for RGB-D cameras. Two novel alternatives to
classical distance transforms are developed with great properties
that significantly improve the classical Euclidean distance field
based methods in terms of efficiency, accuracy and robustness.
Finally, to deal with challenging scenarios that go beyond what
standard RGB/RGB-D cameras can handle, we investigate the
recently emerging event camera and focus on the problem of 3D
reconstruction from data captured by a stereo event-camera rig
moving in a static
scene, such as in the context of stereo Simultaneous Localization
and Mapping
Design study for LANDSAT D attitude control system
A design and performance evaluation is presented for the LANDSAT D attitude control system (ACS). Control and configuration of the gimballed Ku-band antenna system for communication with the tracking and data relay satellite (TDRS). Control of the solar array drive considered part of the ACS is also addressed
Design study for LANDSAT-D attitude control system
The gimballed Ku-band antenna system for communication with TDRS was studied. By means of an error analysis it was demonstrated that the antenna cannot be open loop pointed to TDRS by an onboard programmer, but that an autotrack system was required. After some tradeoffs, a two-axis, azimuth-elevation type gimbal configuration was recommended for the antenna. It is shown that gimbal lock only occurs when LANDSAT-D is over water where a temporary loss of the communication link to TDRS is of no consequence. A preliminary gimbal control system design is also presented. A digital computer program was written that computes antenna gimbal angle profiles, assesses percent antenna beam interference with the solar array, and determines whether the spacecraft is over land or water, a lighted earth or a dark earth, and whether the spacecraft is in eclipse
Modeling and visualization of medical anesthesiology acts
Dissertação para obtenção do Grau de Mestre em
Engenharia InformáticaIn recent years, medical visualization has evolved from simple 2D images on a light
board to 3D computarized images. This move enabled doctors to find better ways of
planning surgery and to diagnose patients. Although there is a great variety of 3D medical imaging software, it falls short when dealing with anesthesiology acts. Very little anaesthesia related work has been done. As a consequence, doctors and medical students have had little support to study the subject of anesthesia in the human body. We all are aware of how costly can be setting medical experiments, covering not just medical aspects but ethical and financial ones as well. With this work we hope to contribute for having better medical visualization tools in the area of anesthesiology. Doctors and in particular medical students should study anesthesiology acts more efficiently. They should be able to identify better locations to administrate the anesthesia, to study how long does it take for the anesthesia to affect patients, to relate the effect on patients with
quantity of anaesthesia provided, etc. In this work, we present a medical visualization
prototype with three main functionalities: image pre-processing, segmentation and rendering.
The image pre-processing is mainly used to remove noise from images, which were obtained via imaging scanners. In the segmentation stage it is possible to identify
relevant anatomical structures using proper segmentation algorithms. As a proof of concept, we focus our attention in the lumbosacral region of the human body, with
data acquired via MRI scanners. The segmentation we provide relies mostly in two algorithms:
region growing and level sets. The outcome of the segmentation implies the creation of a 3D model of the anatomical structure under analysis. As for the rendering, the 3D models are visualized using the marching cubes algorithm. The software we have
developed also supports time-dependent data. Hence, we could represent the anesthesia
flowing in the human body. Unfortunately, we were not able to obtain such type of data
for testing. But we have used human lung data to validate this functionality
Real-space imaging of polar and elastic nano-textures in thin films via inversion of diffraction data
Exploiting the emerging nanoscale periodicities in epitaxial, single-crystal
thin films is an exciting direction in quantum materials science: confinement
and periodic distortions induce novel properties. The structural motifs of
interest are ferroelastic, ferroelectric, multiferroic, and, more recently,
topologically protected magnetization and polarization textures. A critical
step towards heterostructure engineering is understanding their nanoscale
structure, best achieved through real-space imaging. X-ray Bragg coherent
diffractive imaging visualizes sub-picometer crystalline displacements with
tens of nanometers spatial resolution. Yet, it is limited to objects spatially
confined in all three dimensions and requires highly coherent, laser-like
x-rays. Here we lift the confinement restriction by developing real-space
imaging of periodic lattice distortions: we combine an iterative phase
retrieval algorithm with unsupervised machine learning to invert the diffuse
scattering in conventional x-ray reciprocal-space mapping into real-space
images of polar and elastic textures in thin epitaxial films. We first
demonstrate our imaging in PbTiO3/SrTiO3 superlattices to be consistent with
published phase-field model calculations. We then visualize strain-induced
ferroelastic domains emerging during the metal-insulator transition in Ca2RuO4
thin films. Instead of homogeneously transforming into a low-temperature
structure (like in bulk), the strained Mott insulator splits into nanodomains
with alternating lattice constants, as confirmed by cryogenic scanning
transmission electron microscopy. Our study reveals the type, size,
orientation, and crystal displacement field of the nano-textures. The
non-destructive imaging of textures promises to improve models for their
dynamics and enable advances in quantum materials and microelectronics
Reflectance Intensity Assisted Automatic and Accurate Extrinsic Calibration of 3D LiDAR and Panoramic Camera Using a Printed Chessboard
This paper presents a novel method for fully automatic and convenient
extrinsic calibration of a 3D LiDAR and a panoramic camera with a normally
printed chessboard. The proposed method is based on the 3D corner estimation of
the chessboard from the sparse point cloud generated by one frame scan of the
LiDAR. To estimate the corners, we formulate a full-scale model of the
chessboard and fit it to the segmented 3D points of the chessboard. The model
is fitted by optimizing the cost function under constraints of correlation
between the reflectance intensity of laser and the color of the chessboard's
patterns. Powell's method is introduced for resolving the discontinuity problem
in optimization. The corners of the fitted model are considered as the 3D
corners of the chessboard. Once the corners of the chessboard in the 3D point
cloud are estimated, the extrinsic calibration of the two sensors is converted
to a 3D-2D matching problem. The corresponding 3D-2D points are used to
calculate the absolute pose of the two sensors with Unified Perspective-n-Point
(UPnP). Further, the calculated parameters are regarded as initial values and
are refined using the Levenberg-Marquardt method. The performance of the
proposed corner detection method from the 3D point cloud is evaluated using
simulations. The results of experiments, conducted on a Velodyne HDL-32e LiDAR
and a Ladybug3 camera under the proposed re-projection error metric,
qualitatively and quantitatively demonstrate the accuracy and stability of the
final extrinsic calibration parameters.Comment: 20 pages, submitted to the journal of Remote Sensin
SURVEILLANCE MISSION PLANNING FOR UAVS IN GPS-DENIED URBAN ENVIRONMENT
Ph.DDOCTOR OF PHILOSOPH
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