27,157 research outputs found
Tracking Performance of the Scintillating Fiber Detector in the K2K Experiment
The K2K long-baseline neutrino oscillation experiment uses a Scintillating
Fiber Detector (SciFi) to reconstruct charged particles produced in neutrino
interactions in the near detector. We describe the track reconstruction
algorithm and the performance of the SciFi after three years of operation.Comment: 24pages,18 figures, and 1 table. Preprint submitted to NI
Methods for removal of unwanted signals from gravity time-series : comparison using linear techniques complemented with analysis of system dynamics
We thanks the participants of the 35th General Assembly of the European Seismological Commission for comments on preliminary results. The authors are grateful to all IGETS contributors, particularly to the station operators and to ISDC/GFZ-Potsdam for providing the original gravity data used in this study. We also thank the developers of ATLANTIDA3.1 and UTide. Part of this work was performed using the ICSMB High Performance Computing Cluster, University of Aberdeen. We also thanks M. Thiel and A. Moura for reviewing a preliminary version and making comments on the methods section and M.A. Ara´ujo for comments on Lyapunov exponents. Funding: A. Valencio is supported by CNPq, Brazil [206246/2014-5]; and received a travel grant from the School of Natural and Computing Sciences, University of Aberdeen [PO2073498], for a presentation including preliminary results.Peer reviewedPostprintPublisher PD
VNect: Real-time 3D Human Pose Estimation with a Single RGB Camera
We present the first real-time method to capture the full global 3D skeletal
pose of a human in a stable, temporally consistent manner using a single RGB
camera. Our method combines a new convolutional neural network (CNN) based pose
regressor with kinematic skeleton fitting. Our novel fully-convolutional pose
formulation regresses 2D and 3D joint positions jointly in real time and does
not require tightly cropped input frames. A real-time kinematic skeleton
fitting method uses the CNN output to yield temporally stable 3D global pose
reconstructions on the basis of a coherent kinematic skeleton. This makes our
approach the first monocular RGB method usable in real-time applications such
as 3D character control---thus far, the only monocular methods for such
applications employed specialized RGB-D cameras. Our method's accuracy is
quantitatively on par with the best offline 3D monocular RGB pose estimation
methods. Our results are qualitatively comparable to, and sometimes better
than, results from monocular RGB-D approaches, such as the Kinect. However, we
show that our approach is more broadly applicable than RGB-D solutions, i.e. it
works for outdoor scenes, community videos, and low quality commodity RGB
cameras.Comment: Accepted to SIGGRAPH 201
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