503,534 research outputs found
Efficiently Tracking Homogeneous Regions in Multichannel Images
We present a method for tracking Maximally Stable Homogeneous Regions (MSHR)
in images with an arbitrary number of channels. MSHR are conceptionally very
similar to Maximally Stable Extremal Regions (MSER) and Maximally Stable Color
Regions (MSCR), but can also be applied to hyperspectral and color images while
remaining extremely efficient. The presented approach makes use of the
edge-based component-tree which can be calculated in linear time. In the
tracking step, the MSHR are localized by matching them to the nodes in the
component-tree. We use rotationally invariant region and gray-value features
that can be calculated through first and second order moments at low
computational complexity. Furthermore, we use a weighted feature vector to
improve the data association in the tracking step. The algorithm is evaluated
on a collection of different tracking scenes from the literature. Furthermore,
we present two different applications: 2D object tracking and the 3D
segmentation of organs.Comment: to be published in ICPRS 2017 proceeding
Solar Magnetic Feature Detection and Tracking for Space Weather Monitoring
We present an automated system for detecting, tracking, and cataloging
emerging active regions throughout their evolution and decay using SOHO
Michelson Doppler Interferometer (MDI) magnetograms. The SolarMonitor Active
Region Tracking (SMART) algorithm relies on consecutive image differencing to
remove both quiet-Sun and transient magnetic features, and region-growing
techniques to group flux concentrations into classifiable features. We
determine magnetic properties such as region size, total flux, flux imbalance,
flux emergence rate, Schrijver's R-value, R* (a modified version of R), and
Falconer's measurement of non-potentiality. A persistence algorithm is used to
associate developed active regions with emerging flux regions in previous
measurements, and to track regions beyond the limb through multiple solar
rotations. We find that the total number and area of magnetic regions on disk
vary with the sunspot cycle. While sunspot numbers are a proxy to the solar
magnetic field, SMART offers a direct diagnostic of the surface magnetic field
and its variation over timescale of hours to years. SMART will form the basis
of the active region extraction and tracking algorithm for the Heliophysics
Integrated Observatory (HELIO)
Anatomy of the Third-Party Web Tracking Ecosystem
The presence of third-party tracking on websites has become customary.
However, our understanding of the third-party ecosystem is still very
rudimentary. We examine third-party trackers from a geographical perspective,
observing the third-party tracking ecosystem from 29 countries across the
globe. When examining the data by region (North America, South America, Europe,
East Asia, Middle East, and Oceania), we observe significant geographical
variation between regions and countries within regions. We find trackers that
focus on specific regions and countries, and some that are hosted in countries
outside their expected target tracking domain. Given the differences in
regulatory regimes between jurisdictions, we believe this analysis sheds light
on the geographical properties of this ecosystem and on the problems that these
may pose to our ability to track and manage the different data silos that now
store personal data about us all
Satellite height determination using satellite-to-satellite tracking and ground laser systems
An attempt was made to use GEOS-C spacecraft height, as measured by the onboard radar altimeter, for an improved determination of the earth's gravitational field and for the determination of the variation of the physical surface of the oceans. Two tracking system approaches to accurately determine the spacecraft height (orbit) are described and their results stated. These are satellite-to-satellite tracking (SST) and ground-laser tracking (GLT). Height variations can be observed in the dm-regions using SST and in the m-region using present GLT
Prediction and Tracking of Moving Objects in Image Sequences
We employ a prediction model for moving object velocity and location estimation derived from Bayesian theory. The optical flow of a certain moving object depends on the history of its previous values. A joint optical flow estimation and moving object segmentation algorithm is used for the initialization of the tracking algorithm. The segmentation of the moving objects is determined by appropriately classifying the unlabeled and the occluding regions. Segmentation and optical flow tracking is used for predicting future frames
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