1,007 research outputs found

    Video analytics system for surveillance videos

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    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

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    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

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    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

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    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

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    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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