1,007 research outputs found
Video analytics system for surveillance videos
Developing an intelligent inspection system that can enhance the public safety is challenging. An efficient video analytics system can help monitor unusual events and mitigate possible damage or loss. This thesis aims to analyze surveillance video data, report abnormal activities and retrieve corresponding video clips. The surveillance video dataset used in this thesis is derived from ALERT Dataset, a collection of surveillance videos at airport security checkpoints.
The video analytics system in this thesis can be thought as a pipelined process. The system takes the surveillance video as input, and passes it through a series of processing such as object detection, multi-object tracking, person-bin association and re-identification. In the end, we can obtain trajectories of passengers and baggage in the surveillance videos. Abnormal events like taking away other's belongings will be detected and trigger the alarm automatically. The system could also retrieve the corresponding video clips based on user-defined query
The Luminosity and Mass Function of the Globular Cluster NGC1261
I-band CCD images of two large regions of the Galactic globular cluster NGC
1261 have been used to construct stellar luminosity functions (LF) for 14000
stars in three annuli from 1.4' from the cluster center to the tidal radius.
The LFs extend to M_I~8 and tend to steepen from the inner to the outer
annulus, in agreement with the predictions of the multimass King-Michie model
that we have calculated for this cluster. The LFs have been transformed into
mass functions. Once corrected for mass segregation the global mass function of
NGC 1261 has a slope x_0=0.8+/-0.5Comment: 9 pages, A&A macros, accepted for publication in A&
Human Pose Estimation using Deep Consensus Voting
In this paper we consider the problem of human pose estimation from a single
still image. We propose a novel approach where each location in the image votes
for the position of each keypoint using a convolutional neural net. The voting
scheme allows us to utilize information from the whole image, rather than rely
on a sparse set of keypoint locations. Using dense, multi-target votes, not
only produces good keypoint predictions, but also enables us to compute
image-dependent joint keypoint probabilities by looking at consensus voting.
This differs from most previous methods where joint probabilities are learned
from relative keypoint locations and are independent of the image. We finally
combine the keypoints votes and joint probabilities in order to identify the
optimal pose configuration. We show our competitive performance on the MPII
Human Pose and Leeds Sports Pose datasets
Recovering 6D Object Pose and Predicting Next-Best-View in the Crowd
Object detection and 6D pose estimation in the crowd (scenes with multiple
object instances, severe foreground occlusions and background distractors), has
become an important problem in many rapidly evolving technological areas such
as robotics and augmented reality. Single shot-based 6D pose estimators with
manually designed features are still unable to tackle the above challenges,
motivating the research towards unsupervised feature learning and
next-best-view estimation. In this work, we present a complete framework for
both single shot-based 6D object pose estimation and next-best-view prediction
based on Hough Forests, the state of the art object pose estimator that
performs classification and regression jointly. Rather than using manually
designed features we a) propose an unsupervised feature learnt from
depth-invariant patches using a Sparse Autoencoder and b) offer an extensive
evaluation of various state of the art features. Furthermore, taking advantage
of the clustering performed in the leaf nodes of Hough Forests, we learn to
estimate the reduction of uncertainty in other views, formulating the problem
of selecting the next-best-view. To further improve pose estimation, we propose
an improved joint registration and hypotheses verification module as a final
refinement step to reject false detections. We provide two additional
challenging datasets inspired from realistic scenarios to extensively evaluate
the state of the art and our framework. One is related to domestic environments
and the other depicts a bin-picking scenario mostly found in industrial
settings. We show that our framework significantly outperforms state of the art
both on public and on our datasets.Comment: CVPR 2016 accepted paper, project page:
http://www.iis.ee.ic.ac.uk/rkouskou/6D_NBV.htm
The Panchromatic Hubble Andromeda Treasury
The Panchromatic Hubble Andromeda Treasury (PHAT) is an on-going HST
Multicycle Treasury program to image ~1/3 of M31's star forming disk in 6
filters, from the UV to the NIR. The full survey will resolve the galaxy into
more than 100 million stars with projected radii from 0-20 kpc over a
contiguous 0.5 square degree area in 828 orbits, producing imaging in the F275W
and F336W filters with WFC3/UVIS, F475W and F814W with ACS/WFC, and F110W and
F160W with WFC3/IR. The resulting wavelength coverage gives excellent
constraints on stellar temperature, bolometric luminosity, and extinction for
most spectral types. The photometry reaches SNR=4 at F275W=25.1, F336W=24.9,
F475W=27.9, F814W=27.1, F110W=25.5, and F160W=24.6 for single pointings in the
uncrowded outer disk; however, the optical and NIR data are crowding limited,
and the deepest reliable magnitudes are up to 5 magnitudes brighter in the
inner bulge. All pointings are dithered and produce Nyquist-sampled images in
F475W, F814W, and F160W. We describe the observing strategy, photometry,
astrometry, and data products, along with extensive tests of photometric
stability, crowding errors, spatially-dependent photometric biases, and
telescope pointing control. We report on initial fits to the structure of M31's
disk, derived from the density of RGB stars, in a way that is independent of
the assumed M/L and is robust to variations in dust extinction. These fits also
show that the 10 kpc ring is not just a region of enhanced recent star
formation, but is instead a dynamical structure containing a significant
overdensity of stars with ages >1 Gyr. (Abridged)Comment: 48 pages including 22 pages of figures. Accepted to the Astrophysical
Journal Supplements. Some figures slightly degraded to reduce submission siz
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