Simple Online and Realtime Tracking with a Deep Association Metric

Simple Online and Realtime Tracking (SORT) is a pragmatic approach to multiple object tracking with a focus on simple, effective algorithms. In this paper, we integrate appearance information to improve the performance of SORT. Due to this extension we are able to track objects through longer periods of occlusions, effectively reducing the number of identity switches. In spirit of the original framework we place much of the computational complexity into an offline pre-training stage where we learn a deep association metric on a large-scale person re-identification dataset. During online application, we establish measurement-to-track associations using nearest neighbor queries in visual appearance space. Experimental evaluation shows that our extensions reduce the number of identity switches by 45%, achieving overall competitive performance at high frame rates.Comment: 5 pages, 1 figur

Computational Simulation as an Innovative Approach in Personalized Medicine

Background: Statistical analyses show that both the spine curvature and the morphological properties of the vertebral bodies can differ considerably. Therefore, the best outcome of a surgery for the individual patient could be achieved by developing patient specific implants to prevent inadequate anchorage of implants that don?t optimally fit to the anatomy and can cause damages of spinal structures

Impact of Weak Lensing Mass Calibration on eROSITA Galaxy Cluster Cosmological Studies -- a Forecast

We forecast the impact of weak lensing (WL) cluster mass calibration on the cosmological constraints from the X-ray selected galaxy cluster counts in the upcoming eROSITA survey. We employ a prototype cosmology pipeline to analyze mock cluster catalogs. Each cluster is sampled from the mass function in a fiducial cosmology and given an eROSITA count rate and redshift, where count rates are modeled using the eROSITA effective area, a typical exposure time, Poisson noise and the scatter and form of the observed X-ray luminosity-- and temperature--mass--redshift relations. A subset of clusters have mock shear profiles to mimic either those from DES and HSC or from the future Euclid and LSST surveys. Using a count rate selection, we generate a baseline cluster cosmology catalog that contains 13k clusters over 14,892~deg$^2$ of extragalactic sky. Low mass groups are excluded using raised count rate thresholds at low redshift. Forecast parameter uncertainties for $\Omega_\mathrm{M}$, $\sigma_8$ and $w$ are 0.023 (0.016; 0.014), 0.017 (0.012; 0.010), and 0.085 (0.074; 0.071), respectively, when adopting DES+HSC WL (Euclid; LSST), while marginalizing over the sum of the neutrino masses. A degeneracy between the distance--redshift relation and the parameters of the observable--mass scaling relation limits the impact of the WL calibration on the $w$ constraints, but with BAO measurements from DESI an improved determination of $w$ to 0.043 becomes possible. With Planck CMB priors, $\Omega_\text{M}$ ($\sigma_8$) can be determined to $0.005$ ($0.007$), and the summed neutrino mass limited to $\sum m_\nu < 0.241$ eV (at 95\%). If systematics on the group mass scale can be controlled, the eROSITA group and cluster sample with 43k objects and LSST WL could constrain $\Omega_\mathrm{M}$ and $\sigma_8$ to 0.007 and $w$ to 0.050.Comment: 28 pages, 13 figur