21,393 research outputs found
Calibration by correlation using metric embedding from non-metric similarities
This paper presents a new intrinsic calibration method that allows us to calibrate a generic single-view point camera just
by waving it around. From the video sequence obtained while the camera undergoes random motion, we compute the pairwise time
correlation of the luminance signal for a subset of the pixels. We show that, if the camera undergoes a random uniform motion, then
the pairwise correlation of any pixels pair is a function of the distance between the pixel directions on the visual sphere. This leads to
formalizing calibration as a problem of metric embedding from non-metric measurements: we want to find the disposition of pixels on
the visual sphere from similarities that are an unknown function of the distances. This problem is a generalization of multidimensional
scaling (MDS) that has so far resisted a comprehensive observability analysis (can we reconstruct a metrically accurate embedding?)
and a solid generic solution (how to do so?). We show that the observability depends both on the local geometric properties (curvature)
as well as on the global topological properties (connectedness) of the target manifold. We show that, in contrast to the Euclidean case,
on the sphere we can recover the scale of the points distribution, therefore obtaining a metrically accurate solution from non-metric
measurements. We describe an algorithm that is robust across manifolds and can recover a metrically accurate solution when the metric
information is observable. We demonstrate the performance of the algorithm for several cameras (pin-hole, fish-eye, omnidirectional),
and we obtain results comparable to calibration using classical methods. Additional synthetic benchmarks show that the algorithm
performs as theoretically predicted for all corner cases of the observability analysis
Topographical coloured plasmonic coins
The use of metal nanostructures for colourization has attracted a great deal
of interest with the recent developments in plasmonics. However, the current
top-down colourization methods based on plasmonic concepts are tedious and time
consuming, and thus unviable for large-scale industrial applications. Here we
show a bottom-up approach where, upon picosecond laser exposure, a full colour
palette independent of viewing angle can be created on noble metals. We show
that colours are related to a single laser processing parameter, the total
accumulated fluence, which makes this process suitable for high throughput
industrial applications. Statistical image analyses of the laser irradiated
surfaces reveal various distributions of nanoparticle sizes which control
colour. Quantitative comparisons between experiments and large-scale
finite-difference time-domain computations, demonstrate that colours are
produced by selective absorption phenomena in heterogeneous nanoclusters.
Plasmonic cluster resonances are thus found to play the key role in colour
formation.Comment: 9 pages, 5 figure
Incorporating interactive 3-dimensional graphics in astronomy research papers
Most research data collections created or used by astronomers are
intrinsically multi-dimensional. In contrast, all visual representations of
data presented within research papers are exclusively 2-dimensional. We present
a resolution of this dichotomy that uses a novel technique for embedding
3-dimensional (3-d) visualisations of astronomy data sets in electronic-format
research papers. Our technique uses the latest Adobe Portable Document Format
extensions together with a new version of the S2PLOT programming library. The
3-d models can be easily rotated and explored by the reader and, in some cases,
modified. We demonstrate example applications of this technique including: 3-d
figures exhibiting subtle structure in redshift catalogues, colour-magnitude
diagrams and halo merger trees; 3-d isosurface and volume renderings of
cosmological simulations; and 3-d models of instructional diagrams and
instrument designs.Comment: 18 pages, 7 figures, submitted to New Astronomy. For paper with
3-dimensional embedded figures, see http://astronomy.swin.edu.au/s2plot/3dpd
Incorporating interactive 3-dimensional graphics in astronomy research papers
Most research data collections created or used by astronomers are
intrinsically multi-dimensional. In contrast, all visual representations of
data presented within research papers are exclusively 2-dimensional. We present
a resolution of this dichotomy that uses a novel technique for embedding
3-dimensional (3-d) visualisations of astronomy data sets in electronic-format
research papers. Our technique uses the latest Adobe Portable Document Format
extensions together with a new version of the S2PLOT programming library. The
3-d models can be easily rotated and explored by the reader and, in some cases,
modified. We demonstrate example applications of this technique including: 3-d
figures exhibiting subtle structure in redshift catalogues, colour-magnitude
diagrams and halo merger trees; 3-d isosurface and volume renderings of
cosmological simulations; and 3-d models of instructional diagrams and
instrument designs.Comment: 18 pages, 7 figures, submitted to New Astronomy. For paper with
3-dimensional embedded figures, see http://astronomy.swin.edu.au/s2plot/3dpd
Physics and Applications of Laser Diode Chaos
An overview of chaos in laser diodes is provided which surveys experimental
achievements in the area and explains the theory behind the phenomenon. The
fundamental physics underpinning this behaviour and also the opportunities for
harnessing laser diode chaos for potential applications are discussed. The
availability and ease of operation of laser diodes, in a wide range of
configurations, make them a convenient test-bed for exploring basic aspects of
nonlinear and chaotic dynamics. It also makes them attractive for practical
tasks, such as chaos-based secure communications and random number generation.
Avenues for future research and development of chaotic laser diodes are also
identified.Comment: Published in Nature Photonic
Implementation of Adaptive Unsharp Masking as a pre-filtering method for watermark detection and extraction
Digital watermarking has been one of the focal points of research interests in order to provide multimedia security in the last decade. Watermark data, belonging to the user, are embedded on an original work such as text, audio, image, and video and thus, product ownership can be proved. Various robust watermarking algorithms have been developed in order to extract/detect the watermark against such attacks. Although watermarking algorithms in the transform domain differ from others by different combinations of transform techniques, it is difficult to decide on an algorithm for a specific application. Therefore, instead of developing a new watermarking algorithm with different combinations of transform techniques, we propose a novel and effective watermark extraction and detection method by pre-filtering, namely Adaptive Unsharp Masking (AUM). In spite of the fact that Unsharp Masking (UM) based pre-filtering is used for watermark extraction/detection in the literature by causing the details of the watermarked image become more manifest, effectiveness of UM may decrease in some cases of attacks. In this study, AUM has been proposed for pre-filtering as a solution to the disadvantages of UM. Experimental results show that AUM performs better up to 11\% in objective quality metrics than that of the results when pre-filtering is not used. Moreover; AUM proposed for pre-filtering in the transform domain image watermarking is as effective as that of used in image enhancement and can be applied in an algorithm-independent way for pre-filtering in transform domain image watermarking
Informative and misinformative interactions in a school of fish
It is generally accepted that, when moving in groups, animals process
information to coordinate their motion. Recent studies have begun to apply
rigorous methods based on Information Theory to quantify such distributed
computation. Following this perspective, we use transfer entropy to quantify
dynamic information flows locally in space and time across a school of fish
during directional changes around a circular tank, i.e. U-turns. This analysis
reveals peaks in information flows during collective U-turns and identifies two
different flows: an informative flow (positive transfer entropy) based on fish
that have already turned about fish that are turning, and a misinformative flow
(negative transfer entropy) based on fish that have not turned yet about fish
that are turning. We also reveal that the information flows are related to
relative position and alignment between fish, and identify spatial patterns of
information and misinformation cascades. This study offers several
methodological contributions and we expect further application of these
methodologies to reveal intricacies of self-organisation in other animal groups
and active matter in general
On empirical methodology, constraints, and hierarchy in artificial grammar learning
This paper considers the AGL literature from a psycholinguistic perspective. It first presents a taxonomy of the experimental familiarization test procedures used, which is followed by a consideration of shortcomings and potential improvements of the empirical methodology. It then turns to reconsidering the issue of grammar learning from the point of view of acquiring constraints, instead of the traditional AGL approach in terms of acquiring sets of rewrite rules. This is, in particular, a natural way of handling longâdistance dependences. The final section addresses an underdeveloped issue in the AGL literature, namely how to detect latent hierarchical structure in AGL response patterns
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