Devon: Deformable Volume Network for Learning Optical Flow

State-of-the-art neural network models estimate large displacement optical flow in multi-resolution and use warping to propagate the estimation between two resolutions. Despite their impressive results, it is known that there are two problems with the approach. First, the multi-resolution estimation of optical flow fails in situations where small objects move fast. Second, warping creates artifacts when occlusion or dis-occlusion happens. In this paper, we propose a new neural network module, Deformable Cost Volume, which alleviates the two problems. Based on this module, we designed the Deformable Volume Network (Devon) which can estimate multi-scale optical flow in a single high resolution. Experiments show Devon is more suitable in handling small objects moving fast and achieves comparable results to the state-of-the-art methods in public benchmarks

On the accelerated settling of fine particles in a bidisperse slurry

An estimation of increasing the volume average sedimentation velocity of fine particles in bidisperse suspension due to their capturing in the circulation zone formed in the laminar flow of incompressible viscous fluid around the spherical coarse particle is proposed. The estimation is important for an explanation of the nonmonotonic shape of the separation curve observed for hydrocyclones. The volume average sedimentation velocity is evaluated on the basis of a cellular model. The characteristic dimensions of the circulation zone are obtained on the basis of a numerical solution of Navier-Stokes equations. Furthermore, these calculations are used for modelling the fast sedimentation of fine particles during their cosedimentation in bidisperse suspension. It was found that the acceleration of sedimentation of fine particles is determined by the concentration of coarse particles in bidisperse suspension, and the sedimentation velocity of fine fraction is proportional to the square of the coarse and fine particle diameter ratio. The limitations of the proposed model are ascertained

Direct Measurements of the Volume Flow Rate and Emissions in a Large Naturally Ventilated Building

The direct measurement of emissions from naturally ventilated dairy barns is challenging due to their large openings and the turbulent and unsteady airflow at the inlets and outlets. The aim of this study was to quantify the impacts of the number and positions of sensors on the estimation of volume flow rate and emissions. High resolution measurements of a naturally ventilated scaled building model in an atmospheric boundary layer wind tunnel were done. Tracer gas was released inside the model and measured at the outlet area, using a fast flame ionization detector (FFID). Additionally, the normal velocity on the area was measured using laser Doppler anemometry (LDA). In total, for a matrix of 65 × 4 sensor positions, the mean normal velocities and the mean concentrations were measured and used to calculate the volume flow rate and the emissions. This dataset was used as a reference to assess the accuracy while systematically reducing the number of sensors and varying the positions of them. The results showed systematic errors in the emission estimation up to +97%, when measurements of concentration and velocity were done at one constant height. This error could be lowered under 5%, when the concentrations were measured as a vertical composite sample

BEST-2K Method for Characterizing Dual-Permeability Unsaturated Soils with Ponded and Tension Infiltrometers

This study presents a new method (BEST-2K) that extends the existing BEST methods for use in characterizing the water retention and hydraulic conductivity functions of matrix and fast-flow regions in dual-permeability soils. BEST-2K requires input information from two water infiltration experiments that are performed under ponded (Beerkan) and unsaturated (tension infiltrometer) conditions at the surface. Other required inputs include water content measurements and the traditional BEST inputs (particle size distribution and bulk density). In this study, first, a flowchart of the BEST-2K method was developed and illustrated with analytically generated data for a synthetic dual-permeability soil. Next, a sensitivity analysis was performed to assess the accuracy of BEST-2K and its sensitivity to the quality of the inputs (water contents and cumulative infiltrations, and the prior estimation of the volume ratio occupied by the fast-flow region). Lastly, BEST-2K was applied to real experimental data to characterize three soils that are prone to preferential flow. BEST-2K was found to be a particularly useful tool that combines experimental and modeling approaches for characterizing dual-permeability soils and, more generally, soils prone to preferential flows

Dynamic Magnetic Resonance Imaging of Endoscopic Third Ventriculostomy Patency With Differently Acquired Fast Imaging With Steady-State Precission Sequences

The aim of the study was to determine the possibilities of two differently acquired two-dimensional fast imaging with steady-state precession (FISP 2D) magnetic resonance sequences in estimation of the third ventricle floor fenestration patency after endoscopic third ventriculostomy (ETV) in the subjects with aqueductal stenosis/obstruction. Fifty eight subjects (37 males, 21 females, mean age 27 years) with previously successfully performed ETV underwent brain MRI on 1.5T MR imager 3-6 months after the procedure. Two different FISP 2D sequences (one included in the standard vendor provided software package, and the other, experimentally developed by our team) were performed respectively at two fixed slice positions: midsagittal and perpendicular to the ETV fenestration, and displayed in a closed-loop cinematographic format in order to estimate the patency. The ventricular volume reduction has been observed as well. Cerebrospinal fluid (CSF) flow through the ETV fenestration was observed in midsagittal plane with both FISP 2D sequences in 93.11% subjects, while in 6.89% subjects the dynamic CSF flow MRI was inconclusive. In the perpendicular plane CSF flow through the ETV fenestration was visible only by use of experimentally developed FISP 2D (TR30/FA70) sequence. Postoperative volume reduction of lateral and third ventricle was detected in 67.24% subjects. Though both FISP 2D sequences acquired in midsagittal plane may be used to estimate the effects of performed ETV, due to achieved higher CSF pulsatile flow sensitivity, only the use of FISP 2D (TR30/FA70) sequence enables the estimation of the treatment effect in perpendicular plane in the absence of phase-contrast sequences.

Accurate Optical Flow via Direct Cost Volume Processing

We present an optical flow estimation approach that operates on the full four-dimensional cost volume. This direct approach shares the structural benefits of leading stereo matching pipelines, which are known to yield high accuracy. To this day, such approaches have been considered impractical due to the size of the cost volume. We show that the full four-dimensional cost volume can be constructed in a fraction of a second due to its regularity. We then exploit this regularity further by adapting semi-global matching to the four-dimensional setting. This yields a pipeline that achieves significantly higher accuracy than state-of-the-art optical flow methods while being faster than most. Our approach outperforms all published general-purpose optical flow methods on both Sintel and KITTI 2015 benchmarks.Comment: Published at the Conference on Computer Vision and Pattern Recognition (CVPR 2017