34,169 research outputs found
Down-Sampling coupled to Elastic Kernel Machines for Efficient Recognition of Isolated Gestures
In the field of gestural action recognition, many studies have focused on
dimensionality reduction along the spatial axis, to reduce both the variability
of gestural sequences expressed in the reduced space, and the computational
complexity of their processing. It is noticeable that very few of these methods
have explicitly addressed the dimensionality reduction along the time axis.
This is however a major issue with regard to the use of elastic distances
characterized by a quadratic complexity. To partially fill this apparent gap,
we present in this paper an approach based on temporal down-sampling associated
to elastic kernel machine learning. We experimentally show, on two data sets
that are widely referenced in the domain of human gesture recognition, and very
different in terms of quality of motion capture, that it is possible to
significantly reduce the number of skeleton frames while maintaining a good
recognition rate. The method proves to give satisfactory results at a level
currently reached by state-of-the-art methods on these data sets. The
computational complexity reduction makes this approach eligible for real-time
applications.Comment: ICPR 2014, International Conference on Pattern Recognition, Stockholm
: Sweden (2014
Model fitting of kink waves in the solar atmosphere: Gaussian damping and time-dependence
{Observations of the solar atmosphere have shown that magnetohydrodynamic
waves are ubiquitous throughout. Improvements in instrumentation and the
techniques used for measurement of the waves now enables subtleties of
competing theoretical models to be compared with the observed waves behaviour.
Some studies have already begun to undertake this process. However, the
techniques employed for model comparison have generally been unsuitable and can
lead to erroneous conclusions about the best model. The aim here is to
introduce some robust statistical techniques for model comparison to the solar
waves community, drawing on the experiences from other areas of astrophysics.
In the process, we also aim to investigate the physics of coronal loop
oscillations. } {The methodology exploits least-squares fitting to compare
models to observational data. We demonstrate that the residuals between the
model and observations contain significant information about the ability for
the model to describe the observations, and show how they can be assessed using
various statistical tests. In particular we discuss the Kolmogorov-Smirnoff one
and two sample tests, as well as the runs test. We also highlight the
importance of including any observational trend line in the model-fitting
process.} {To demonstrate the methodology, an observation of an oscillating
coronal loop undergoing standing kink motion is used. The model comparison
techniques provide evidence that a Gaussian damping profile provides a better
description of the observed wave attenuation than the often used exponential
profile. This supports previous analysis from Pascoe et al. (2016). Further, we
use the model comparison to provide evidence of time-dependent wave properties
of a kink oscillation, attributing the behaviour to the thermodynamic evolution
of the local plasma.}Comment: Accepted in Astronomy & Astrophysics
http://dx.doi.org/10.1051/0004-6361/20162861
Engineering data compendium. Human perception and performance. User's guide
The concept underlying the Engineering Data Compendium was the product of a research and development program (Integrated Perceptual Information for Designers project) aimed at facilitating the application of basic research findings in human performance to the design and military crew systems. The principal objective was to develop a workable strategy for: (1) identifying and distilling information of potential value to system design from the existing research literature, and (2) presenting this technical information in a way that would aid its accessibility, interpretability, and applicability by systems designers. The present four volumes of the Engineering Data Compendium represent the first implementation of this strategy. This is the first volume, the User's Guide, containing a description of the program and instructions for its use
EyeRIS: A General-Purpose System for Eye Movement Contingent Display Control
In experimental studies of visual performance, the need often emerges to modify the stimulus according to the eye movements perfonncd by the subject. The methodology of Eye Movement-Contingent Display (EMCD) enables accurate control of the position and motion of the stimulus on the retina. EMCD procedures have been used successfully in many areas of vision science, including studies of visual attention, eye movements, and physiological characterization of neuronal response properties. Unfortunately, the difficulty of real-time programming and the unavailability of flexible and economical systems that can be easily adapted to the diversity of experimental needs and laboratory setups have prevented the widespread use of EMCD control. This paper describes EyeRIS, a general-purpose system for performing EMCD experiments on a Windows computer. Based on a digital signal processor with analog and digital interfaces, this integrated hardware and software system is responsible for sampling and processing oculomotor signals and subject responses and modifying the stimulus displayed on a CRT according to the gaze-contingent procedure specified by the experimenter. EyeRIS is designed to update the stimulus within a delay of 10 ms. To thoroughly evaluate EyeRIS' perforltlancc, this study (a) examines the response of the system in a number of EMCD procedures and computational benchmarking tests, (b) compares the accuracy of implementation of one particular EMCD procedure, retinal stabilization, to that produced by a standard tool used for this task, and (c) examines EyeRIS' performance in one of the many EMCD procedures that cannot be executed by means of any other currently available device.National Institute of Health (EY15732-01
Recommended from our members
Cloud base height estimates from sky imagery and a network of pyranometers
Cloud base height (CBH) is an important parameter for physics-based high resolution solar radiation modeling. In sky imager-based forecasts, a ceilometer or stereographic setup is needed to derive the CBH; otherwise erroneous CBHs lead to incorrect physical cloud velocity and incorrect projection of cloud shadows, causing solar power forecast errors due to incorrect shadow positions and timing of shadowing events. In this paper, two methods to estimate cloud base height from a single sky imager and distributed ground solar irradiance measurements are proposed. The first method (Time Series Correlation, denoted as “TSC”) is based upon the correlation between ground-observed global horizontal irradiance (GHI) time series and a modeled GHI time series generated from a sequence of sky images geo-rectified to a candidate set of CBH. The estimated CBH is taken as the candidate that produces the highest correlation coefficient. The second method (Geometric Cloud Shadow Edge, denoted as “GCSE”) integrates a numerical ramp detection method for ground-observed GHI time series with solar and cloud geometry applied to cloud edges in a sky image. CBH are benchmarked against a collocated ceilometer and stereographically estimated CBH from two sky imagers for 15 min median-filtered CBHs. Over 30 days covering all seasons, the TSC method performs similarly to the GCSE method with nRMSD of 18.9% versus 20.8%. A key limitation of both proposed methods is the requirement of sufficient variation in GHI to enable reliable correlation and ramp detection. The advantage of the two proposed methods is that they can be applied when measurements from only a single sky imager and pyranometers are available
Advanced analog television study final report, 4 nov. - 19 dec. 1963
Information bandwidth reduction for analog television signals - Description of multiple interlace syste
- …