3,010 research outputs found
Timing analysis techniques at large core distances for multi-TeV gamma ray astronomy
We present an analysis technique that uses the timing information of
Cherenkov images from extensive air showers (EAS). Our emphasis is on distant,
or large core distance gamma-ray induced showers at multi-TeV energies.
Specifically, combining pixel timing information with an improved direction
reconstruction algorithm, leads to improvements in angular and core resolution
as large as ~40% and ~30%, respectively, when compared with the same algorithm
without the use of timing. Above 10 TeV, this results in an angular resolution
approaching 0.05 degrees, together with a core resolution better than ~15 m.
The off-axis post-cut gamma-ray acceptance is energy dependent and its full
width at half maximum ranges from 4 degrees to 8 degrees. For shower directions
that are up to ~6 degrees off-axis, the angular resolution achieved by using
timing information is comparable, around 100 TeV, to the on-axis angular
resolution. The telescope specifications and layout we describe here are geared
towards energies above 10 TeV. However, the methods can in principle be applied
to other energies, given suitable telescope parameters. The 5-telescope cell
investigated in this study could initially pave the way for a larger array of
sparsely spaced telescopes in an effort to push the collection area to >10 km2.
These results highlight the potential of a `sparse array' approach in
effectively opening up the energy range above 10 TeV.Comment: Published in Astroparticle Physic
Superpixel-based spatial amplitude and phase modulation using a digital micromirror device
We present a superpixel method for full spatial phase and amplitude control
of a light beam using a digital micromirror device (DMD) combined with a
spatial filter. We combine square regions of nearby micromirrors into
superpixels by low pass filtering in a Fourier plane of the DMD. At each
superpixel we are able to independently modulate the phase and the amplitude of
light, while retaining a high resolution and the very high speed of a DMD. The
method achieves a measured fidelity for a target field with fully
independent phase and amplitude at a resolution of pixels per
diffraction limited spot. For the LG orbital angular momentum mode the
calculated fidelity is , using DMD pixels. The
superpixel method reduces the errors when compared to the state of the art Lee
holography method for these test fields by and , with a comparable
light efficiency of around . Our control software is publicly available.Comment: 9 pages, 6 figure
The Topology ToolKit
This system paper presents the Topology ToolKit (TTK), a software platform
designed for topological data analysis in scientific visualization. TTK
provides a unified, generic, efficient, and robust implementation of key
algorithms for the topological analysis of scalar data, including: critical
points, integral lines, persistence diagrams, persistence curves, merge trees,
contour trees, Morse-Smale complexes, fiber surfaces, continuous scatterplots,
Jacobi sets, Reeb spaces, and more. TTK is easily accessible to end users due
to a tight integration with ParaView. It is also easily accessible to
developers through a variety of bindings (Python, VTK/C++) for fast prototyping
or through direct, dependence-free, C++, to ease integration into pre-existing
complex systems. While developing TTK, we faced several algorithmic and
software engineering challenges, which we document in this paper. In
particular, we present an algorithm for the construction of a discrete gradient
that complies to the critical points extracted in the piecewise-linear setting.
This algorithm guarantees a combinatorial consistency across the topological
abstractions supported by TTK, and importantly, a unified implementation of
topological data simplification for multi-scale exploration and analysis. We
also present a cached triangulation data structure, that supports time
efficient and generic traversals, which self-adjusts its memory usage on demand
for input simplicial meshes and which implicitly emulates a triangulation for
regular grids with no memory overhead. Finally, we describe an original
software architecture, which guarantees memory efficient and direct accesses to
TTK features, while still allowing for researchers powerful and easy bindings
and extensions. TTK is open source (BSD license) and its code, online
documentation and video tutorials are available on TTK's website
InfiniTAM v3: A Framework for Large-Scale 3D Reconstruction with Loop Closure
Volumetric models have become a popular representation for 3D scenes in
recent years. One breakthrough leading to their popularity was KinectFusion,
which focuses on 3D reconstruction using RGB-D sensors. However, monocular SLAM
has since also been tackled with very similar approaches. Representing the
reconstruction volumetrically as a TSDF leads to most of the simplicity and
efficiency that can be achieved with GPU implementations of these systems.
However, this representation is memory-intensive and limits applicability to
small-scale reconstructions. Several avenues have been explored to overcome
this. With the aim of summarizing them and providing for a fast, flexible 3D
reconstruction pipeline, we propose a new, unifying framework called InfiniTAM.
The idea is that steps like camera tracking, scene representation and
integration of new data can easily be replaced and adapted to the user's needs.
This report describes the technical implementation details of InfiniTAM v3,
the third version of our InfiniTAM system. We have added various new features,
as well as making numerous enhancements to the low-level code that
significantly improve our camera tracking performance. The new features that we
expect to be of most interest are (i) a robust camera tracking module; (ii) an
implementation of Glocker et al.'s keyframe-based random ferns camera
relocaliser; (iii) a novel approach to globally-consistent TSDF-based
reconstruction, based on dividing the scene into rigid submaps and optimising
the relative poses between them; and (iv) an implementation of Keller et al.'s
surfel-based reconstruction approach.Comment: This article largely supersedes arxiv:1410.0925 (it describes version
3 of the InfiniTAM framework
High-Performance and Tunable Stereo Reconstruction
Traditional stereo algorithms have focused their efforts on reconstruction
quality and have largely avoided prioritizing for run time performance. Robots,
on the other hand, require quick maneuverability and effective computation to
observe its immediate environment and perform tasks within it. In this work, we
propose a high-performance and tunable stereo disparity estimation method, with
a peak frame-rate of 120Hz (VGA resolution, on a single CPU-thread), that can
potentially enable robots to quickly reconstruct their immediate surroundings
and maneuver at high-speeds. Our key contribution is a disparity estimation
algorithm that iteratively approximates the scene depth via a piece-wise planar
mesh from stereo imagery, with a fast depth validation step for semi-dense
reconstruction. The mesh is initially seeded with sparsely matched keypoints,
and is recursively tessellated and refined as needed (via a resampling stage),
to provide the desired stereo disparity accuracy. The inherent simplicity and
speed of our approach, with the ability to tune it to a desired reconstruction
quality and runtime performance makes it a compelling solution for applications
in high-speed vehicles.Comment: Accepted to International Conference on Robotics and Automation
(ICRA) 2016; 8 pages, 5 figure
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