Swimmer localization from a moving camera

At the highest level of competitive sport, nearly all performances of athletes (both training and competitive) are chronicled using video. Video is then often viewed by expert coaches/analysts who then manually label important performance indicators to gauge performance. Stroke-rate and pacing are important performance measures in swimming, and these are previously digitised manually by a human. This is problematic as annotating large volumes of video can be costly, and time-consuming. Further, since it is difficult to accurately estimate the position of the swimmer at each frame, measures such as stroke rate are generally aggregated over an entire swimming lap. Vision-based techniques which can automatically, objectively and reliably track the swimmer and their location can potentially solve these issues and allow for large-scale analysis of a swimmer across many videos. However, the aquatic environment is challenging due to fluctuations in scene from splashes, reflections and because swimmers are frequently submerged at different points in a race. In this paper, we temporally segment races into distinct and sequential states, and propose a multimodal approach which employs individual detectors tuned to each race state. Our approach allows the swimmer to be located and tracked smoothly in each frame despite a diverse range of constraints. We test our approach on a video dataset compiled at the 2012 Australian Short Course Swimming Championships.

Video analytics for the detection of near-miss incidents on approach to railway level crossings

Recent modelling of socio-economic costs by the Australian railway industry in 2010 has estimated the cost of level crossing accidents to exceed AU$116 million annually. To better understand causal factors that contribute to these accidents, the Cooperative Research Centre for Rail Innovation is running a project entitled Baseline Level Crossing Video. The project aims to improve the recording of level crossing safety data by developing an intelligent system capable of detecting near-miss incidents and capturing quantitative data around these incidents. To detect near-miss events at railway level crossings a video analytics module is being developed to analyse video footage obtained from forward-facing cameras installed on trains. This paper presents a vision base approach for the detection of these near-miss events. The video analytics module is comprised of object detectors and a rail detection algorithm, allowing the distance between a detected object and the rail to be determined. An existing publicly available Histograms of Oriented Gradients (HOG) based object detector algorithm is used to detect various types of vehicles in each video frame. As vehicles are usually seen from a sideway view from the cabin’s perspective, the results of the vehicle detector are verified using an algorithm that can detect the wheels of each detected vehicle. Rail detection is facilitated using a projective transformation of the video, such that the forward-facing view becomes a bird’s eye view. Line Segment Detector is employed as the feature extractor and a sliding window approach is developed to track a pair of rails. Localisation of the vehicles is done by projecting the results of the vehicle and rail detectors on the ground plane allowing the distance between the vehicle and rail to be calculated. The resultant vehicle positions and distance are logged to a database for further analysis. We present preliminary results regarding the performance of a prototype video analytics module on a data set of videos containing more than 30 different railway level crossings. The video data is captured from a journey of a train that has passed through these level crossings.

Learning detectors quickly with stationary statistics

Computer vision is increasingly becoming interested in the rapid estimation of object detectors. The canonical strategy of using Hard Negative Mining to train a Support Vector Machine is slow, since the large negative set must be traversed at least once per detector. Recent work has demonstrated that, with an assumption of signal stationarity, Linear Discriminant Analysis is able to learn comparable detectors without ever revisiting the negative set. Even with this insight, the time to learn a detector can still be on the order of minutes. Correlation filters, on the other hand, can produce a detector in under a second. However, this involves the unnatural assumption that the statistics are periodic, and requires the negative set to be re-sampled per detector size. These two methods differ chie y in the structure which they impose on the co- variance matrix of all examples. This paper is a comparative study which develops techniques (i) to assume periodic statistics without needing to revisit the negative set and (ii) to accelerate the estimation of detectors with aperiodic statistics. It is experimentally verified that periodicity is detrimental.

Frequency dielectric influence of imaginary admittance on oil-paper insulation system-a case study

Frequency Domain Spectroscopy (FDS) is used to assess the insulation condition of oil-paper power transformers. Dissipation factor is one of the conventional indicators to analyze insulation ageing status. In this paper, the imaginary admittance of the transformers insulation, after removal of the geometric capacitance, is proposed as an alternative indicator to assist in the interpretation of ageing status. Ageing effects on the imaginary admittance are investigated both through simulation results and experimental results.

State-of-the-art : track degradation at bridge transitions

Transition zones between bridge decks and rail tracks suffer early failure due to poor interaction between rail vehicles and sudden changes of stiffness. This has been an ongoing problem to rail industry and yet still no systematic studies appear to have been taken to maintain a gradually smoothening transmission of forces between the bridge and its approach. Differential settlement between the bridge deck and rail track in the transition zone is the fundamental issue, which negatively impacts the rail industry by causing passenger discomfort, early damage to infrastructure and vehicle components, speed reduction, and frequent maintenance cycles. Identification of mechanism of the track degradation and factors affecting is imperative to design any mitigation method for reducing track degradation rate at the bridge transition zone. Unfortunately this issue is still not well understood, after conducting a numbers of reviews to evaluate the key causes, and introducing a wide range of mitigation techniques. In this study, a comprehensive analysis of the available literature has been carried out to develop either a novel design framework or a mitigation technique for the bridge transition zone. This paper addresses three critical questions in relation to the track degradation at transition zone: (1) what are the causes of bridge transition track degradation?; (2) what are the available mitigation techniques in reducing the track degradation rate?; (3) what are the factors affecting on poor performance of the existing mitigation techniques?. It is found that the absence of soil-water response, dynamic loading response, and behaviour of geotechnical characteristics under long-term conditions in existing track transition design frameworks critically influence on the failures of existing mitigation techniques. This paper also evaluates some of the existing design frameworks to identify how each design framework addresses the track degradation at the bridge transition zone.

Overview of the INEX 2008 Ad Hoc Track

This paper gives an overview of the INEX 2008 Ad Hoc Track. The main goals of the Ad Hoc Track were two-fold. The first goal was to investigate the value of the internal document structure (as provided by the XML mark-up) for retrieving relevant information. This is a continuation of INEX 2007 and, for this reason, the retrieval results are liberalized to arbitrary passages and measures were chosen to fairly compare systems retrieving elements, ranges of elements, and arbitrary passages. The second goal was to compare focused retrieval to article retrieval more directly than in earlier years. For this reason, standard document retrieval rankings have been derived from all runs, and evaluated with standard measures. In addition, a set of queries targeting Wikipedia have been derived from a proxy log, and the runs are also evaluated against the clicked Wikipedia pages. The INEX 2008 Ad Hoc Track featured three tasks: For the Focused Task a ranked-list of nonoverlapping results (elements or passages) was needed. For the Relevant in Context Task non-overlapping results (elements or passages) were returned grouped by the article from which they came. For the Best in Context Task a single starting point (element start tag or passage start) for each article was needed. We discuss the results for the three tasks, and examine the relative effectiveness of element and passage retrieval. This is examined in the context of content only (CO, or Keyword) search as well as content and structure (CAS, or structured) search. Finally, we look at the ability of focused retrieval techniques to rank articles, using standard document retrieval techniques, both against the judged topics as well as against queries and clicks from a proxy log.

Calibration functions for estimating soil moisture from GPR dielectric constant measurements

Ground-penetrating radar (GPR) is widely used for assessment of soil moisture variability in field soils. Because GPR does not measure soil water content directly, it is common practice to use calibration functions that describe its relationship with the soil dielectric properties and textural parameters. However, the large variety of models complicates the selection of the appropriate function. In this article an overview is presented of the different functions available, including volumetric models, empirical functions, effective medium theories, and frequency-specific functions. Using detailed information presented in summary tables, the choice for which calibration function to use can be guided by the soil variables available to the user, the frequency of the GPR equipment, and the desired level of detail of the output. This article can thus serve as a guide for GPR practitioners to obtain soil moisture values and to estimate soil dielectric properties.

Plasma polymer-coated on nanoparticles to improve dielectric and electrical insulation properties of nanocomposites

Polymeric nanocomposites have been shown to possess superior electrical insulation properties compared to traditional filled-resins. However, poor dispersion uniformity and insufficient filler-matrix interaction can adversely affect insulation properties of nanocomposites. In this study, the use of plasma polymerization is proposed to coat poly(ethylene oxide) polymer layers on silica nanoparticles. It is shown that better dispersion is achieved and C-O bonds are created between the surface functional groups of the nanoparticles and the host epoxy polymer. Electrical insulation tests demonstrate that the nanocomposites with plasma polymerized silica nanoparticles feature better resistance against electrical treeing, lower dielectric constant, and also mitigated space charge built-up. Therefore, plasma polymerization offers a promising fabrication technique to further improve the synthesis of nanocomposite dielectrics with superior electrical insulation properties.

Dielectric performance of polymer nanocomposites synthesized by atmospheric-pressure plasma-treated silica nanoparticles

In this study, atmospheric-pressure plasmas were applied to modify the surface of silane-coated silica nanoparticles. Subsequently nanocomposites were synthesized by incorporating plasma-treated nanoparticles into an epoxy resin matrix. Electrical testing showed that such novel dielectric materials obtained high partial discharge resistance, high dielectric breakdown strength, and enhanced endurance under highly stressed electric field. Through spectroscopic and microscopic analysis, we found surface groups of nanoparticles were activated and radicals were created after the plasma treatment. Moreover, a uniform dispersion of nanoparticles in nanocomposites was observed. It was expected that the improved dielectric performance of the nanocomposites can attribute to stronger chemical bonds formed between surface groups of plasma-treated nanoparticles and molecules in the matrix. This simple yet effective and environmentally friendly approach aims to synthesize the next generation of high-performance nanocomposite dielectric insulation materials for applications in high-voltage power systems.

Silica nanoparticles treated by cold atmospheric-pressure plasmas improve the dielectric performance of organic–inorganic nanocomposites

We report on the application of cold atmospheric-pressure plasmas to modify silica nanoparticles to enhance their compatibility with polymer matrices. Thermally nonequilibrium atmospheric-pressure plasma is generated by a high-voltage radio frequency power source operated in the capacitively coupled mode with helium as the working gas. Compared to the pure polymer and the polymer nanocomposites with untreated SiO2, the plasma-treated SiO2–polymer nanocomposites show higher dielectric breakdown strength and extended endurance under a constant electrical stress. These improvements are attributed to the stronger interactions between the SiO2 nanoparticles and the surrounding polymer matrix after the plasma treatment. Our method is generic and can be used in the production of high-performance organic–inorganic functional nanocomposites.

Dielectric barrier discharge plasma in Ar/O2 promoting apoptosis behavior in A549 cancer cells

The Ar/O2plasma needle in the induction of A549 cancer cells apoptosis process is studied by means of real-time observation. The entire process of programmed cell death is observed. The typical morphological changes of A549 apoptosis are detected by 4′, 6-diamidino-2-phenylindole staining, for example, chromatin condensation and nuclear fragmentation. Cell viability is determined and quantified by neutral red uptake assay, and the survival rate of A549 from Ar/O2plasmas is presented. Further spectral analysis indicates the reactive species, including O and OH play crucial roles in the cell inactivation.

Nanopore processing in dielectric materials and dielectric template-assisted nanoarray synthesis : using pulsed bias to enhance process throughput and precision

An effective technique to improve the precision and throughput of energetic ion condensation through dielectric nanoporous templates and reduce nanopore clogging by using finely tuned pulsed bias is proposed. Multiscale numerical simulations of ion deposition show the possibility of controlling the dynamic charge balance on the upper template's surface to minimize ion deposition on nanopore sidewalls and to deposit ions selectively on the substrate surface in contact with the pore opening. In this way, the shapes of nanodots in template-assisted nanoarray fabrication can be effectively controlled. The results are applicable to various processes involving porous dielectric nanomaterials and dense nanoarrays.

Ion-acoustic surface waves on a dielectric-dusty plasma interface

The theory of ion-acoustic surface wave propagation on the interface between a dusty plasma and a dielectric is presented. Both the constant and variable dust-charge cases are considered. It is found that massive negatively charged dust grains can significantly affect the propagation and damping of the surface waves. Application of the results to surface-wave generated plasmas is discussed. © 1998 IEEE.

Pulsed i-PVD of dielectric nanodot arrays using a nanoporous template

The results of multi-scale numerical simulations of pulsed i-PVD template-assisted nanofabrication of ZnO nanodot arrays on a silicon substrate are presented. The ratios and spatial distributions of the ion fluxes deposited on the lateral and bottom surfaces of the nanopores are computed as a function of the external bias and plasma parameters. The results show that the pulsed bias plays a significant role in the ion current distribution inside the nanopores. The results of numerical experiments of this work suggest that by finely adjusting the pulse voltage, the pulse duration and the duty cycle of the external pulsed bias, the nanopore clogging can be successfully avoided during the deposition and the shapes of the deposited ZnO nanodots can be effectively controlled. A figure is presented.

A model of a large-area planar plasma producer based on surface wave propagation in a plasma-metal structure with a dielectric sheath

A theoretical model of a large-area planar plasma producer based on surface wave (SW) propagation in a plasma-metal structure with a dielectric sheath is presented. The SW which produces and sustains the microwave gas discharge in the planar structure propagates along an external magnetic field and possesses an eigenfrequency within the range between electron cyclotron and electron plasma frequencies. The spatial distributions of the produced plasma density, electromagnetic fields, energy flow density, phase velocity and reverse skin depth of the SW are obtained analytically and numerically.