Learning Deep Representations of Appearance and Motion for Anomalous Event Detection

We present a novel unsupervised deep learning framework for anomalous event detection in complex video scenes. While most existing works merely use hand-crafted appearance and motion features, we propose Appearance and Motion DeepNet (AMDN) which utilizes deep neural networks to automatically learn feature representations. To exploit the complementary information of both appearance and motion patterns, we introduce a novel double fusion framework, combining both the benefits of traditional early fusion and late fusion strategies. Specifically, stacked denoising autoencoders are proposed to separately learn both appearance and motion features as well as a joint representation (early fusion). Based on the learned representations, multiple one-class SVM models are used to predict the anomaly scores of each input, which are then integrated with a late fusion strategy for final anomaly detection. We evaluate the proposed method on two publicly available video surveillance datasets, showing competitive performance with respect to state of the art approaches.Comment: Oral paper in BMVC 201

A Neural System for Automated CCTV Surveillance

This paper overviews a new system, the “Owens Tracker,” for automated identification of suspicious pedestrian activity in a car-park. Centralized CCTV systems relay multiple video streams to a central point for monitoring by an operator. The operator receives a continuous stream of information, mostly related to normal activity, making it difficult to maintain concentration at a sufficiently high level. While it is difficult to place quantitative boundaries on the number of scenes and time period over which effective monitoring can be performed, Wallace and Diffley [1] give some guidance, based on empirical and anecdotal evidence, suggesting that the number of cameras monitored by an operator be no greater than 16, and that the period of effective monitoring may be as low as 30 minutes before recuperation is required. An intelligent video surveillance system should therefore act as a filter, censuring inactive scenes and scenes showing normal activity. By presenting the operator only with unusual activity his/her attention is effectively focussed, and the ratio of cameras to operators can be increased. The Owens Tracker learns to recognize environmentspecific normal behaviour, and refers sequences of unusual behaviour for operator attention. The system was developed using standard low-resolution CCTV cameras operating in the car-parks of Doxford Park Industrial Estate (Sunderland, Tyne and Wear), and targets unusual pedestrian behaviour. The modus operandi of the system is to highlight excursions from a learned model of normal behaviour in the monitored scene. The system tracks objects and extracts their centroids; behaviour is defined as the trajectory traced by an object centroid; normality as the trajectories typically encountered in the scene. The essential stages in the system are: segmentation of objects of interest; disambiguation and tracking of multiple contacts, including the handling of occlusion and noise, and successful tracking of objects that “merge” during motion; identification of unusual trajectories. These three stages are discussed in more detail in the following sections, and the system performance is then evaluated

FUSE Observations of the Dwarf Nova SW UMa During Quiescence

We present spectroscopic observations of the short-period cataclysmic variable SW Ursa Majoris, obtained by the Far Ultraviolet Spectroscopic Explorer (FUSE) satellite while the system was in quiescence. The data include the resonance lines of O VI at 1031.91 and 1037.61 A. These lines are present in emission, and they exhibit both narrow (~ 150 km/s) and broad (~ 2000 km/s) components. The narrow O VI emission lines exhibit unusual double-peaked and redshifted profiles. We attribute the source of this emission to a cooling flow onto the surface of the white dwarf primary. The broad O VI emission most likely originates in a thin, photoionized surface layer on the accretion disk. We searched for emission from H_2 at 1050 and 1100 A, motivated by the expectation that the bulk of the quiescent accretion disk is in the form of cool, molecular gas. If H_2 is present, then our limits on the fluxes of the H_2 lines are consistent with the presence of a surface layer of atomic H that shields the interior of the disk. These results may indicate that accretion operates primarily in the surface layers of the disk in SW UMa. We also investigate the far-UV continuum of SW UMa and place an upper limit of 15,000 K on the effective temperature of the white dwarf.Comment: 21 Pages, 3 figures, to be published in Ap

Ionospheric effects during first 2 hours after the Chelyabinsk meteorite impact

This paper presents the analysis of ionospheric effects in the region close to the Chelyabinsk meteorite explosion at 03:20UT 2013 February 15 from the Institute of Solar-Terrestrial Physics of Siberian Branch of Russian Academy of Sciences (ISTP SB RAS) EKB radar data, and from the Institute of Geophysics of Ural Branch of Russian Academy of Sciences (IG UB RAS) PARUS ionosonde data. Both instruments are located within the IG UB RAS Arti Observatory approximately 200 km northward from the estimated explosion site. According to the data obtained, the ionospheric disturbance caused by the meteorite flyby, explosion, and impact had high dynamics and amplitude. However, it obviously did not lead to a variation in the ionosphere mean parameters in the region above the disturbance center during the first 2 hours. Essential effects, however, were observed at more than 100-200 km from the explosion site and farther up to 1500 km.Comment: 30 pages, 15 figures, submitted to JAST

The cuticle

The nematode cuticle is an extremely flexible and resilient exoskeleton that permits locomotion via attachment to muscle, confers environmental protection and allows growth by molting. It is synthesised five times, once in the embryo and subsequently at the end of each larval stage prior to molting. It is a highly structured extra-cellular matrix (ECM), composed predominantly of cross-linked collagens, additional insoluble proteins termed cuticlins, associated glycoproteins and lipids. The cuticle collagens are encoded by a large gene family that are subject to strict patterns of temporal regulation. Cuticle collagen biosynthesis involves numerous co- and post-translational modification, processing, secretion and cross-linking steps that in turn are catalysed by specific enzymes and chaperones. Mutations in individual collagen genes and their biosynthetic pathway components can result in a range of defects from abnormal morphology (dumpy and blister) to embryonic and larval death, confirming an essential role for this structure and highlighting its potential as an ECM experimental model system

Recoil polarization and beam-recoil double polarization measurement of \eta electroproduction on the proton in the region of the S_{11}(1535) resonance

The beam-recoil double polarization P_{x'}^h and P_{z'}^h and the recoil polarization P_{y'} were measured for the first time for the p(\vec{e},e'\vec{p})\eta reaction at a four-momentum transfer of Q^2=0.1 GeV^2/c^2 and a center of mass production angle of \theta = 120^\circ at MAMI C. With a center of mass energy range of 1500 MeV < W < 1550 MeV the region of the S_{11}(1535) and D_{13}(1520) resonance was covered. The results are discussed in the framework of a phenomenological isobar model (Eta-MAID). While P_{x'}^h and P_{z'}^h are in good agreement with the model, P_{y'} shows a significant deviation, consistent with existing photoproduction data on the polarized-target asymmetry.Comment: 4 pages, 1 figur

Transport congestion events detection (TCED): towards decorrelating congestion detection from TCP

TCP (Transmission Control Protocol) uses a loss-based algorithm to estimate whether the network is congested or not. The main difficulty for this algorithm is to distinguish spurious from real network congestion events. Other research studies have proposed to enhance the reliability of this congestion estimation by modifying the internal TCP algorithm. In this paper, we propose an original congestion event algorithm implemented independently of the TCP source code. Basically, we propose a modular architecture to implement a congestion event detection algorithm to cope with the increasing complexity of the TCP code and we use it to understand why some spurious congestion events might not be detected in some complex cases. We show that our proposal is able to increase the reliability of TCP NewReno congestion detection algorithm that might help to the design of detection criterion independent of the TCP code. We find out that solutions based only on RTT (Round-Trip Time) estimation are not accurate enough to cover all existing cases. Furthermore, we evaluate our algorithm with and without network reordering where other inaccuracies, not previously identified, occur