2,062 research outputs found
Modelling potential movement in constrained travel environments using rough space-time prisms
The widespread adoption of location-aware technologies (LATs) has afforded analysts new opportunities for efficiently collecting trajectory data of moving individuals. These technologies enable measuring trajectories as a finite sample set of time-stamped locations. The uncertainty related to both finite sampling and measurement errors makes it often difficult to reconstruct and represent a trajectory followed by an individual in space-time. Time geography offers an interesting framework to deal with the potential path of an individual in between two sample locations. Although this potential path may be easily delineated for travels along networks, this will be less straightforward for more nonnetwork-constrained environments. Current models, however, have mostly concentrated on network environments on the one hand and do not account for the spatiotemporal uncertainties of input data on the other hand. This article simultaneously addresses both issues by developing a novel methodology to capture potential movement between uncertain space-time points in obstacle-constrained travel environments
Robust curvature extrema detection based on new numerical derivation
International audienceExtrema of curvature are useful key points for different image analysis tasks. Indeed, polygonal approximation or arc decomposition methods used often these points to initialize or to improve their algorithms. Several shape-based image retrieval methods focus also their descriptors on key points. This paper is focused on the detection of extrema of curvature points for a raster-to-vector-conversion framework. We propose an original adaptation of an approach used into nonlinear control for fault-diagnosis and fault-tolerant control based on algebraic derivation and which is robust to noise. The experimental results are promising and show the robustness of the approach when the contours are bathed into a high level speckled noise
Computational advances in gravitational microlensing: a comparison of CPU, GPU, and parallel, large data codes
To assess how future progress in gravitational microlensing computation at
high optical depth will rely on both hardware and software solutions, we
compare a direct inverse ray-shooting code implemented on a graphics processing
unit (GPU) with both a widely-used hierarchical tree code on a single-core CPU,
and a recent implementation of a parallel tree code suitable for a CPU-based
cluster supercomputer. We examine the accuracy of the tree codes through
comparison with a direct code over a much wider range of parameter space than
has been feasible before. We demonstrate that all three codes present
comparable accuracy, and choice of approach depends on considerations relating
to the scale and nature of the microlensing problem under investigation. On
current hardware, there is little difference in the processing speed of the
single-core CPU tree code and the GPU direct code, however the recent plateau
in single-core CPU speeds means the existing tree code is no longer able to
take advantage of Moore's law-like increases in processing speed. Instead, we
anticipate a rapid increase in GPU capabilities in the next few years, which is
advantageous to the direct code. We suggest that progress in other areas of
astrophysical computation may benefit from a transition to GPUs through the use
of "brute force" algorithms, rather than attempting to port the current best
solution directly to a GPU language -- for certain classes of problems, the
simple implementation on GPUs may already be no worse than an optimised
single-core CPU version.Comment: 11 pages, 4 figures, accepted for publication in New Astronom
Multiorder polygonal approximation of digital curves
In this paper, we propose a quick threshold-free algorithm, which computes the angular shape of a 2D object from the points of its contour. For that, we have extended the method defined in [4, 5] to a multiorder analysis. It is based on the arithmetical definition of discrete lines [11] with variable thickness. We provide a framework to analyse a digital curve at different levels of thickness. The extremities of a segment provided at a high resolution are tracked at lower resolution in order to refine their location. The method is thresholdfree and automatically provides a partitioning of a digital curve into its meaningful parts
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