10,007 research outputs found
Meteor light curves: the relevant parameters
We investigate a uniform sample of 113 light curves (LCs) of meteors
collected at the Wise Observatory in November 2002 while observing the Leonid
meteor shower. We use previously defined descriptors such as the skewness F and
a recently defined pointedness parameter along with a number of other
measurable or derived quantities to explore the parameter space in search of
meaningful LC descriptors. We make extensive use of statistical techniques to
reveal links among the variables and to understand their relative importance.
In particular, we show that meteors with long-duration trails rise slowly to
their maximal brightness and also decay slowly from there while showing milder
flaring than other meteors. Early skewed LCs show a fast rise to the peak. We
show that the duration of te luminous phase of the meteor is th emost important
variable differentiating among the 2002 LCs. The skewness parameter F appears
only as the 2nd or 3rd in explaining the LC variance. We suggest that the
pointedness parameter P could possibly be useful to discriminate among meteors
from different showers, or to compare observations and model predictions.Comment: 10 pages (2 figures) in press with MNRA
AFLOW-SYM: Platform for the complete, automatic and self-consistent symmetry analysis of crystals
Determination of the symmetry profile of structures is a persistent challenge
in materials science. Results often vary amongst standard packages, hindering
autonomous materials development by requiring continuous user attention and
educated guesses. Here, we present a robust procedure for evaluating the
complete suite of symmetry properties, featuring various representations for
the point-, factor-, space groups, site symmetries, and Wyckoff positions. The
protocol determines a system-specific mapping tolerance that yields symmetry
operations entirely commensurate with fundamental crystallographic principles.
The self consistent tolerance characterizes the effective spatial resolution of
the reported atomic positions. The approach is compared with the most used
programs and is successfully validated against the space group information
provided for over 54,000 entries in the Inorganic Crystal Structure Database.
Subsequently, a complete symmetry analysis is applied to all 1.7 million
entries of the AFLOW data repository. The AFLOW-SYM package has been
implemented in, and made available for, public use through the automated,
framework AFLOW.Comment: 24 pages, 6 figure
A Framework for Symmetric Part Detection in Cluttered Scenes
The role of symmetry in computer vision has waxed and waned in importance
during the evolution of the field from its earliest days. At first figuring
prominently in support of bottom-up indexing, it fell out of favor as shape
gave way to appearance and recognition gave way to detection. With a strong
prior in the form of a target object, the role of the weaker priors offered by
perceptual grouping was greatly diminished. However, as the field returns to
the problem of recognition from a large database, the bottom-up recovery of the
parts that make up the objects in a cluttered scene is critical for their
recognition. The medial axis community has long exploited the ubiquitous
regularity of symmetry as a basis for the decomposition of a closed contour
into medial parts. However, today's recognition systems are faced with
cluttered scenes, and the assumption that a closed contour exists, i.e. that
figure-ground segmentation has been solved, renders much of the medial axis
community's work inapplicable. In this article, we review a computational
framework, previously reported in Lee et al. (2013), Levinshtein et al. (2009,
2013), that bridges the representation power of the medial axis and the need to
recover and group an object's parts in a cluttered scene. Our framework is
rooted in the idea that a maximally inscribed disc, the building block of a
medial axis, can be modeled as a compact superpixel in the image. We evaluate
the method on images of cluttered scenes.Comment: 10 pages, 8 figure
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