Dense Multiperson Tracking with Robust Hierarchical Linear Assignment

We introduce a novel dual-stage algorithm for online multi-target tracking in realistic conditions. In the first stage, the problem of data association between tracklets and detections, given partial occlusion, is addressed using a novel occlusion robust appearance similarity method. This is used to robustly link tracklets with detections without requiring explicit knowledge of the occluded regions. In the second stage, tracklets are linked using a novel method of constraining the linking process that removes the need for ad-hoc tracklet linking rules. In this method, links between tracklets are permitted based on their agreement with optical flow evidence. Tests of this new tracking system have been performed using several public datasets.

Recurrent Convolutional Network for Video-based Person Re-Identification

In this paper we propose a novel recurrent neural networkarchitecture for video-based person re-identification.Given the video sequence of a person, features are extracted from each frame using a convolutional neural network that incorporates a recurrent final layer, which allows information to flow between time-steps. The features from all time steps are then combined using temporal pooling to give an overall appearance feature for the complete sequence. The convolutional network, recurrent layer, and temporal pooling layer, are jointly trained to act as a feature extractor for video-based re-identification using a Siamese network architecture.Our approach makes use of colour and optical flow information in order to capture appearance and motion information which is useful for video re-identification. Experiments are conduced on the iLIDS-VID and PRID-2011 datasets to show that this approach outperforms existing methods of video-based re-identification.

https://github.com/niallmcl/Recurrent-Convolutional-Video-ReID
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Field investigation of contactless displacement measurement using computer vision systems for civil engineering applications

Much of the bridge stock on major transport links in North America and Europe was constructed in the 1950s and 1960s and has since deteriorated or is carrying loads far in excess of the original design loads. Structural Health Monitoring Systems (SHM) can provide valuable information on the bridge capacity but the application of such systems is currently limited by access and bridge type. This paper investigates the use of computer vision systems for SHM. A series of field tests have been carried out to test the accuracy of displacement measurements using contactless methods. A video image of each test was processed using a modified version of the optical flow tracking method to track displacement. These results have been validated with an established measurement method using linear variable differential transformers (LVDTs). The results obtained from the algorithm provided an accurate comparison with the validation measurements. The calculated displacements agree within 2% of the verified LVDT measurements, a number of post processing methods were then applied to attempt to reduce this error.

Electrical, Thermal and Optical Diagnostics of an Atmospheric Plasma Jet System

Plasma diagnostics of atmospheric plasmas is a key tool in helping to understand processing performance issues. This paper presents an electrical, optical and thermographic imaging study of the PlasmaStream atmospheric plasma jet system. The system was found to exhibit three operating modes; one constricted/localized plasma and two extended volume plasmas. At low power and helium flows the plasma is localized at the electrodes and has the electrical properties of a corona/filamentary discharge with electrical chaotic temporal structure. With increasing discharge power and helium flow the plasma expands into the volume of the tube, becoming regular and homogeneous in appearance. Emission spectra show evidence of atomic oxygen, nitric oxide and the hydroxyl radical production. Plasma activated gas temperature deduced from the rotational temperature of nitrogen molecules was found to be of order of 400 K: whereas thermographic imaging of the quartz tube yielded surface temperatures between 319 and 347 K.

Pressure drop of gas–liquid Taylor flow in round micro-capillaries for low to intermediate Reynolds numbers

In this paper, a model is presented that describes the pressure drop of gas-liquid Taylor flow in round capillaries with a channel diameter typically less than 1 mm. The analysis of Bretherton (J Fluid Mech 10:166-188, 1961) for the pressure drop over a single gas bubble for vanishing liquid film thickness is extended to include a non-negligible liquid film thickness using the analysis of Aussillous and Qu,r, (Phys Fluids 12(10):2367-2371, 2000). This result is combined with the Hagen-Poiseuille equation for liquid flow using a mass balance-based Taylor flow model previously developed by the authors (Warnier et al. in Chem Eng J 135S:S153-S158, 2007). The model presented in this paper includes the effect of the liquid slug length on the pressure drop similar to the model of Kreutzer et al. (AIChE J 51(9):2428-2440, 2005). Additionally, the gas bubble velocity is taken into account, thereby increasing the accuracy of the pressure drop predictions compared to those of the model of Kreutzer et al. Experimental data were obtained for nitrogen-water Taylor flow in a round glass channel with an inner diameter of 250 mu m. The capillary number Ca (gl) varied between 2.3 x 10(-3) and 8.8 x 10(-3) and the Reynolds number Re (gl) varied between 41 and 159. The presented model describes the experimental results with an accuracy of +/- 4% of the measured values.

Comparison of Experimental PIV Data and CFD Simulations for Flow in a Diesel Particulate Filter Inlet Diffuser

Flow maldistribution of the exhaust gas entering a Diesel Particulate Filter (DPF) can cause uneven soot distribution during loading and excessive temperature gradients during the regeneration phase. Minimising the magnitude of this maldistribution is therefore an important consideration in the design of the inlet pipe and diffuser, particularly in situations where packaging constraints dictate bends in the inlet pipe close to the filter, or a sharp diffuser angle. This paper describes the use of Particle Image Velocimetry (PIV) to validate a Computational Fluid Dynamic (CFD) model of the flow within the inlet diffuser of a DPF so that CFD can be used with confidence as a tool to minimise this flow maldistribution. PIV is used to study the flow of gas into a DPF over a range of steady state flow conditions. The distribution of flow approaching the front face of the substrate was of particular interest to this study. Optically clear diffusing cones were designed and placed between pipe and substrate to allow PIV analysis to take place. Stereoscopic PIV was used to eliminate any error produced by the optical aberrations caused by looking through the curved wall of the inlet cone. In parallel to the experiments, numerical analysis was carried out using a CFD program with an incorporated DPF model. Boundary conditions for the CFD simulations were taken from the experimental data, allowing an experimental validation of the numerical results. The CFD model incorporated a DPF model, the cement layers seen in segmented filters and the intumescent matting that is commonly used to pack the filter into a metal casing. The mesh contained approximately 580,000 cells and used the realizable ?-e turbulence model. The CFD simulation predicted both pressure drop across the DPF and the velocity field within the cone and at the DPF face with reasonable accuracy, providing confidence in the use the CFD in future work to design new, more efficient cones.

Optical coherence tomography for the diagnosis of neovascular age-related macular degeneration: a systematic review

The purpose is to study the diagnostic performance of optical coherence tomography (OCT) and alternative diagnostic tests for neovascular age-related macular degeneration (nAMD). Methods employed are as follows:systematic review and meta-analysis; Index test: OCT including time-domain (TD-OCT) and the most recently developed spectral domain (SD-OCT); comparator tests: visual acuity, clinical evaluation (slit lamp), Amsler chart, colour fundus photographs, infra-red reflectance, red-free images/blue reflectance, fundus autofluorescence imaging (FAF), indocyanine green angiography (ICGA), preferential hyperacuity perimetry (PHP), and microperimetry; reference standard: fundus fluorescein angiography. Databases searched included MEDLINE, MEDLINE In Process, EMBASE, Biosis, SCI, the Cochrane Library, DARE, MEDION, and HTA database. Last literature searches: March 2013. Risk of bias assessed using QUADAS-2. Meta-analysis models were fitted using hierarchical summary receiver operating characteristic (HSROC) curves. Twenty-two studies (2 abstracts and 20 articles) enrolling 2124 participants were identified, reporting TD-OCT (12 studies), SD-OCT (1 study), ICGA (8 studies), PHP (3 studies), Amsler grid, colour fundus photography and FAF (1 study each). Most studies were considered to have a high risk of bias in the patient selection (55%, 11/20), and flow and timing (40%, 8/20) domains. In a meta-analysis of TD-OCT studies, sensitivity and specificity (95% CI) were 88% (46–98%) and 78% (64–88%), respectively. There was insufficient information to undertake meta-analysis for other tests. TD-OCT is a sensitive test for detecting nAMD, although specificity was only moderate. Data on SD-OCT are sparse. Diagnosis of nAMD should not rely solely on OCT.