Target Detection and Tracking With Heterogeneous Sensors

We present a multimodal detection and tracking algorithm for sensors composed of a camera mounted between two microphones. Target localization is performed on color-based change detection in the video modality and on time difference of arrival (TDOA) estimation between the two microphones in the audio modality. The TDOA is computed by multiband generalized cross correlation (GCC) analysis. The estimated directions of arrival are then postprocessed using a Riccati Kalman filter. The visual and audio estimates are finally integrated, at the likelihood level, into a particle filter (PF) that uses a zero-order motion model, and a weighted probabilistic data association (WPDA) scheme. We demonstrate that the Kalman filtering (KF) improves the accuracy of the audio source localization and that the WPDA helps to enhance the tracking performance of sensor fusion in reverberant scenarios. The combination of multiband GCC, KF, and WPDA within the particle filtering framework improves the performance of the algorithm in noisy scenarios. We also show how the proposed audiovisual tracker summarizes the observed scene by generating metadata that can be transmitted to other network nodes instead of transmitting the raw images and can be used for very low bit rate communication. Moreover, the generated metadata can also be used to detect and monitor events of interest.

Reducing Drifts in the Inertial Measurements of Wrist and Elbow Positions

In this paper, we present an inertial-sensor-based monitoring system for measuring the movement of human upper limbs. Two wearable inertial sensors are placed near the wrist and elbow joints, respectively. The measurement drift in segment orientation is dramatically reduced after a Kalman filter is applied to estimate inclinations using accelerations and turning rates from gyroscopes. Using premeasured lengths of the upper and lower arms, we compute the position of the wrist and elbow joints via a proposed kinematic model. Experimental results demonstrate that this new motion capture system, in comparison to an optical motion tracker, possesses an RMS position error of less than 0.009 m, with a drift of less than 0.005 ms-1 in five daily activities. In addition, the RMS angle error is less than 3??. This indicates that the proposed approach has performed well in terms of accuracy and reliability.

Modeling Frequency-Dependent Boundaries as Digital Impedance Filters in FDTD and K-DWM Room Acoustics Simulations

A new method for modeling-frequency-dependent boundaries in finite-difference time-domain (FDTD) and Kirchhoff variable digital waveguide mesh (K-DWM) room acoustics simulations is presented. The proposed approach allows the direct incorporation of a digital impedance filter (DIF) in the Multidimensional (2D or 3D) FDTD boundary model of a locally reacting surface. An explicit boundary update equation is obtained by carefully constructing a Suitable recursive formulation. The method is analyzed in terms of pressure wave reflectance for different wall impedance filters and angles of incidence. Results obtained from numerical experiments confirm the high accuracy of the proposed digital impedance filter boundary model, the reflectance of which matches locally reacting surface (LRS) theory closely. Furthermore a numerical boundary analysis (NBA) formula is provided as a technique for an analytic evaluation of the numerical reflectance of the proposed digital impedance filter boundary formulation.

Room acoustics simulation using 3-D compact explicit FDTD schemes

This paper presents methods for simulating room acoustics using the finite-difference time-domain (FDTD) technique, focusing on boundary and medium modeling. A family of nonstaggered 3-D compact explicit FDTD schemes is analyzed in terms of stability, accuracy, and computational efficiency, and the most accurate and isotropic schemes based on a rectilinear grid are identified. A frequency-dependent boundary model that is consistent with locally reacting surface theory is also presented, in which the wall impedance is represented with a digital filter. For boundaries, accuracy in numerical reflection is analyzed and a stability proof is provided. The results indicate that the proposed 3-D interpolated wideband and isotropic schemes outperform directly related techniques based on Yee's staggered grid and standard digital waveguide mesh, and that the boundary formulations generally have properties that are similar to that of the basic scheme used.

Parametric FIR Design of Propagation Loss Filters in Digital Waveguide String Models

One of the attractive features of sound synthesis by physical modeling is the potential to build acoustic-sounding digital instruments that offer more flexibility and different options in its design and control than their real-life counterparts. In order to develop such virtual-acoustic instruments, the models they are based on need to be fully parametric, i.e., all coefficients employed in the model are functions of physical parameters that are controlled either online or at the (offline) design stage. In this letter we show how propagation losses can be parametrically incorporated in digital waveguide string models with the use of zero-phase FIR filters. Starting from the simplest possible design in the form of a three-tap FIR filter, a higher-order FIR strategy is presented and discussed within the perspective of string sound synthesis with digital waveguide models.

The role of non-protein sulphydryls in determining the chemical repair rates of free radical precursors of DNA damage and cell killing in Chinese hamster V79 cells. I

Chinese hamster V79 fibroblasts were irradiated in the gas explosion apparatus and the chemical repair rates of the oxygen-dependent free radical precursors of DNA double-strand breaks (dsb) and lethal lesions measured using filter elution (pH 9.6) and a clonogenic assay. Depletion of cellular GSH levels, from 4.16 fmol/cell to 0.05 fmol/cell, by treatment with buthionine sulphoximine (50 mumol dm-3; 18 h), led to sensitization as regards DNA dsb induction and cell killing. This was evident at all time settings but was particularly pronounced when the oxygen shot was given 1 ms after the irradiation pulse. A detailed analysis of the chemical repair kinetics showed that depletion of GSH led to a reduction in the first-order rate constant for dsb precursors from 385 s-1 to 144 s-1, and for lethal lesion precursors from 533 s-1 to 165 s-1. This is generally consistent with the role of GSH in the repair-fixation model of radiation damage at the critical DNA lesions. However, the reduction in chemical repair rate was not proportional to the severe thiol depletion (down to almost-equal-to 1% for GSH) and a residual repair capacity remained (almost-equal-to 30%). This was found not to be due to compartmentalization of residual GSH in the nucleus, as the repair rate for dsb precursors in isolated nuclei, washed virtually free of GSH, was identical to that found in GSH-depleted cells (144 s-1), also the OER remained substantially above unity. This suggests that other reducing agents may have a role to play in the chemical repair of oxygen-dependent damage. One possible candidate is the significant level of protein sulphydryls present in isolated nuclei.

SVM Training Phase Reduction Using Dataset Feature Filtering for Malware Detection

N-gram analysis is an approach that investigates the structure of a program using bytes, characters, or text strings. A key issue with N-gram analysis is feature selection amidst the explosion of features that occurs when N is increased. The experiments within this paper represent programs as operational code (opcode) density histograms gained through dynamic analysis. A support vector machine is used to create a reference model, which is used to evaluate two methods of feature reduction, which are 'area of intersect' and 'subspace analysis using eigenvectors.' The findings show that the relationships between features are complex and simple statistics filtering approaches do not provide a viable approach. However, eigenvector subspace analysis produces a suitable filter.

Quantifying mircoorganism/organic matter interactions in saturated porous media.

Proteins and humic acids are common constituents of waste water. Latex colloids (colloids) acted as surrogates for microorganisms in multiple pulse dynamic column experiments (MPEs) that permitted colloid mobility to be quantified before and after the injection of either BSA (a protein), or Suwannee River humic acid (SRHA).
At low OM coverage colloid breakthrough curves demonstrated both BSA and SRHA reduced colloid deposition rates, but did not affect colloid irreversible deposition mechanisms. By contrast, high levels of SRHA surface coverage not only further reduced the matrix’s ability to attenuate colloids, but also resulted in reversible adsorption of a significant fraction of colloids deposited. Modelling of colloid responses using random sequential adsorption modelling suggested that 1 microgram of SRHA had the same effect as the deposition of 5.90±0.14 x109 colloids; the model suggested that adsorption of the same mass of BSA was equivalent to the deposition of between 7.1x108 and 2.3x109 colloids.
Colloid responses in MPEs where BSA coverage of colloid deposition sites approached saturation demonstrated the sand matrix remained capable of adsorbing colloids. However, in contrast to responses observed in MPEs at low surface coverage, continued colloid injection showed that the sand’s attenuation capacity increased with time, i.e. colloid concentrations declined as more were deposited (filter ripening).
Importance: Study results highlight the contrasting responses that may arise due to the interactions between colloids and OM in porous media. Results not only underscore that colloids can interact differently with various forms of deposited OM, but also that a single type of OM may generate dramatically different responses depending on the degree of surface coverage. The MPE method provides a means of quantifying the influence of OM on microorganism mobility in porous media such as filter beds, which may be used for either drinking water treatment or waste water treatment. In the wider environment study findings have potential to allow more confident predictions of the mobility of sewage derived pathogens discharging to groundwater.

Physical Models of Wind Instruments : A Generalized Excitation Coupled with a Modular Tube Simulation Platform

To develop real-time simulations of wind instruments, digital waveguides filters can be used as an efficient representation of the air column. Many aerophones are shaped as horns which can be approximated using conical sections. Therefore the derivation of conical waveguide filters is of special interest. When these filters are used in combination with a generalized reed excitation, several classes of wind instruments can be simulated. In this paper we present the methods for transforming a continuous description of conical tube segments to a discrete filter representation. The coupling of the reed model with the conical waveguide and a simplified model of the termination at the open end are described in the same way. It turns out that the complete lossless conical waveguide requires only one type of filter.Furthermore, we developed a digital reed excitation model, which is purely based on numerical integration methods, i.e., without the use of a look-up table.

Robust visual tracking based on online learning sparse representation

Handling appearance variations is a very challenging problem for visual tracking. Existing methods usually solve this problem by relying on an effective appearance model with two features: (1) being capable of discriminating the tracked target from its background, (2) being robust to the target's appearance variations during tracking. Instead of integrating the two requirements into the appearance model, in this paper, we propose a tracking method that deals with these problems separately based on sparse representation in a particle filter framework. Each target candidate defined by a particle is linearly represented by the target and background templates with an additive representation error. Discriminating the target from its background is achieved by activating the target templates or the background templates in the linear system in a competitive manner. The target's appearance variations are directly modeled as the representation error. An online algorithm is used to learn the basis functions that sparsely span the representation error. The linear system is solved via ℓ1 minimization. The candidate with the smallest reconstruction error using the target templates is selected as the tracking result. We test the proposed approach using four sequences with heavy occlusions, large pose variations, drastic illumination changes and low foreground-background contrast. The proposed approach shows excellent performance in comparison with two latest state-of-the-art trackers.

Comparing the influence of two different natural organic matter types on colloid deposition in saturated porous medium

Humic acid and protein are two major organic matter types encountered in natural and polluted environment, respectively. This study employed Triple Pulse Experiments (TPEs) to investigate and compare the influence of Suwannee River Humic Acid (SRHA) (model humic acid) and Bovine Serum Albumin (BSA) (model protein) on colloid deposition in a column packed with saturated iron oxide-coated quartz sand. Study results suggest that adsorbed SRHA may inhibit colloid deposition by occupying colloid sites on the porous medium. Conversely, BSA may promote colloid deposition by a 'filter ripening' mechanism. This study provides insight to understand the complex behavior of colloids in organic matter-presented aquifers and sand filters. © (2012) Trans Tech Publications, Switzerland.

3D Analysis of Seepage under Hydraulic Structures with Intermediate Filters

Seepage flow under hydraulic structures provided with intermediate filters has been investigated. The flow through the banks of the canal has been included in the model. Different combinations of intermediate filter and canal width were studied. Different lengths of the floor, differential heads, and depths of the sheet pile driven beneath the floor were also investigated. The introduction of an intermediate filter to the floor of hydraulic structures reduced the uplift force acting on the downstream floor by up to 72%. The maximum uplift reduction occurred when the ratio of the distance of filter location downstream from the cutoff to the differential head was 1. Introducing a second filter in the downstream side resulted in a further reduction in the exit hydraulic gradient and in the uplift force, which reached 90%. The optimum locations of the two filters occurred when the first filter was placed just downstream of the cutoff wall and the second filter was placed nearly at the middistance between the cutoff and the end toe of the floor. The results showed significant differences between the three-dimensional (3D) and the two-dimensional (2D) analyses.

Generalized Laplacian Eigenmaps for Modeling and Tracking Human Motions

This paper presents generalized Laplacian eigenmaps, a novel dimensionality reduction approach designed to address stylistic variations in time series. It generates compact and coherent continuous spaces whose geometry is data-driven. This paper also introduces graph-based particle filter, a novel methodology conceived for efficient tracking in low dimensional space derived from a spectral dimensionality reduction method. Its strengths are a propagation scheme, which facilitates the prediction in time and style, and a noise model coherent with the manifold, which prevents divergence, and increases robustness. Experiments show that a combination of both techniques achieves state-of-the-art performance for human pose tracking in underconstrained scenarios.