Showing papers on "Filter (video) published in 2008"

Action MACH a spatio-temporal Maximum Average Correlation Height filter for action recognition

Abstract: In this paper we introduce a template-based method for recognizing human actions called action MACH. Our approach is based on a maximum average correlation height (MACH) filter. A common limitation of template-based methods is their inability to generate a single template using a collection of examples. MACH is capable of capturing intra-class variability by synthesizing a single Action MACH filter for a given action class. We generalize the traditional MACH filter to video (3D spatiotemporal volume), and vector valued data. By analyzing the response of the filter in the frequency domain, we avoid the high computational cost commonly incurred in template-based approaches. Vector valued data is analyzed using the Clifford Fourier transform, a generalization of the Fourier transform intended for both scalar and vector-valued data. Finally, we perform an extensive set of experiments and compare our method with some of the most recent approaches in the field by using publicly available datasets, and two new annotated human action datasets which include actions performed in classic feature films and sports broadcast television.

An Optimized Blockwise Nonlocal Means Denoising Filter for 3-D Magnetic Resonance Images

Abstract: A critical issue in image restoration is the problem of noise removal while keeping the integrity of relevant image information. Denoising is a crucial step to increase image quality and to improve the performance of all the tasks needed for quantitative imaging analysis. The method proposed in this paper is based on a 3-D optimized blockwise version of the nonlocal (NL)-means filter (Buades, , 2005). The NL-means filter uses the redundancy of information in the image under study to remove the noise. The performance of the NL-means filter has been already demonstrated for 2-D images, but reducing the computational burden is a critical aspect to extend the method to 3-D images. To overcome this problem, we propose improvements to reduce the computational complexity. These different improvements allow to drastically divide the computational time while preserving the performances of the NL-means filter. A fully automated and optimized version of the NL-means filter is then presented. Our contributions to the NL-means filter are: 1) an automatic tuning of the smoothing parameter; 2) a selection of the most relevant voxels; 3) a blockwise implementation; and 4) a parallelized computation. Quantitative validation was carried out on synthetic datasets generated with BrainWeb (Collins, , 1998). The results show that our optimized NL-means filter outperforms the classical implementation of the NL-means filter, as well as two other classical denoising methods [anisotropic diffusion (Perona and Malik, 1990)] and total variation minimization process (Rudin, , 1992) in terms of accuracy (measured by the peak signal-to-noise ratio) with low computation time. Finally, qualitative results on real data are presented.

A complementary filter for attitude estimation of a fixed-wing UAV

Abstract: This paper considers the question of using a nonlinear complementary filter for attitude estimation of fixed-wing unmanned aerial vehicle (UAV) given only measurements from a low-cost inertial measurement unit. A nonlinear complementary filter is proposed that combines accelerometer output for low frequency attitude estimation with integrated gyrometer output for high frequency estimation. The raw accelerometer output includes a component corresponding to airframe acceleration, occurring primarily when the aircraft turns, as well as the gravitational acceleration that is required for the filter. The airframe acceleration is estimated using a simple centripetal force model (based on additional airspeed measurements), augmented by a first order dynamic model for angle-of-attack, and used to obtain estimates of the gravitational direction independent of the airplane manoeuvres. Experimental results are provided on a real-world data set and the performance of the filter is evaluated against the output from a full GPS/INS that was available for the data set.

Tooth-shaped plasmonic waveguide filters with nanometeric sizes

Abstract: A novel nanometeric plasmonic filter in a tooth-shaped metal-insulator-metal waveguide is proposed and demonstrated numerically. An analytic model based on the scattering matrix method is given. The result reveals that the single tooth-shaped filter has a wavelength-filtering characteristic and an ultracompact size in the length of a few hundred nanometers, compared to gratinglike surface plasmon polariton (SPP) filters. Both analytic and simulation results show that the wavelength of the trough of the transmission has linear and nonlinear relationships with the tooth depth and the tooth width, respectively. The waveguide filter could be utilized to develop ultracompact photonic filters for high integration.

Filter Bank Spectrum Sensing for Cognitive Radios

Abstract: The primary task in any cognitive radio (CR) network is to dynamically explore the radio spectrum and reliably determine portion(s) of the frequency band that may be used for the communication link(s). Accordingly, each CR node in the network has to be equipped with a spectrum analyzer. In this paper, we propose filter banks as a tool for spectrum sensing in CR systems. Various choices of filter banks are suggested and their performance are evaluated theoretically and through numerical examples. Moreover, the proposed spectrum analyzer is contrasted with the Thomson's multitaper (MT) method - a method that in the recent literature has been recognized as the best choice for spectrum sensing in CR systems. A novel derivation of the MT method that facilitates our comparisons as well as reveals an important aspect of the MT method that has been less emphasized in the recent literature is also presented.

Predictive Current Control Strategy With Imposed Load Current Spectrum

Abstract: This paper presents a modified predictive current control strategy which allows one to have control over the spectrum of the load current. The proposed method uses a model of the system to predict the behavior of the current for each possible voltage vector generated by the inverter. For that purpose, at each sampling interval, signal predictions are evaluated using a cost function that quantifies the desired system behavior. The cost function used in this work evaluates the filtered error of the load currents. The inclusion of a filter for the load error allows one to manipulate current spectra. Thus, by designing this filter appropriately, the load spectrum can be shaped. The performance of the proposed control strategy is verified by simulation and experimental results.

Design and Analysis of a Novel ${\cal L}_1$ Adaptive Control Architecture With Guaranteed Transient Performance

Abstract: This paper presents a novel adaptive control architecture that adapts fast and ensures uniformly bounded transient response for system's both signals, input and output, simultaneously. This new architecture has a low-pass filter in the feedback loop and relies on the small-gain theorem for the proof of asymptotic stability. The tools from this paper can be used to develop a theoretically justified verification and validation framework for adaptive systems. Simulations illustrate the theoretical findings.

A Noise‐aware Filter for Real‐time Depth Upsampling

Abstract: A new generation of active 3D range sensors, such as time-of-flight cameras, enables recording of full-frame depth maps at video frame rate. Unfortunately, the captured data are typically starkly contaminated by noise and the sensors feature only a rather limited image resolution. We therefore present a pipeline to enhance the quality and increase the spatial resolution of range data in real-time by upsampling the range information with the data from a high resolution video camera. Our algorithm is an adaptive multi-lateral upsampling filter that takes into account the inherent noisy nature of real-time depth data. Thus, we can greatly improve reconstruction quality, boost the resolution of the data to that of the video sensor, and prevent unwanted artifacts like texture copy into geometry. Our technique has been crafted to achieve improvement in depth map quality while maintaining high computational efficiency for a real-time application. By implementing our approach on the GPU, the creation of a real-time 3D camera with video camera resolution is feasible.

A Simple Voltage Sensorless Active Damping Scheme for Three-Phase PWM Converters With an $LCL$ Filter

Abstract: Active three-phase pulsewidth-modulated rectifiers are connected to the grid by an inductance or an LCL filter. Although an filter is more effective since it more efficiently attenuates the switching harmonics, it causes stability problems. To enable a stable operation, either a damping resistor or an active damping (AD) algorithm has to be used. However, while a damping resistor causes additional losses, an AD algorithm usually requires extra sensors. To avoid these disadvantages, this paper shows simulation and experimental results of a simple AC voltage sensorless AD solution that is suitable for industrial applications.

Attenuation of Conducted EMI Emissions From an Inverter-Driven Motor

Abstract: This paper provides theoretical and experimental discussions on conducted electromagnetic interference (EMI) emissions from an inverter-driven motor rated at 400 V and 15 kW. It focuses on a line EMI filter and its combination with a motor EMI filter, along with their effects on attenuation of conducted emission voltage. When no EMI filter is connected, the motor drive cannot meet the conducted emission limits prescribed by Category 3 in the IEC61800-3 regulations. The reason is that the common-mode voltage generated by a voltage-source pulse width modulation (PWM) inverter causes a common-mode leakage current flowing into the ground wire lead through parasitic capacitors inside the motor. When the line EMI filter is connected, the motor drive can meet Category 3. The motor EMI filter eliminates the common-mode voltage from the motor terminals, thus bringing a drastic reduction to the leakage current. The combination of the two EMI filters can comply with the limits prescribed by Category 2, which are much stricter than those by Category 3.

A deterministic formulation of the ensemble Kalman filter: an alternative to ensemble square root filters

Abstract: The use of perturbed observations in the traditional ensemble Kalman filter (EnKF) results in a suboptimal filter behaviour, particularly for small ensembles. In this work, we propose a simple modification to the traditional EnKF that results in matching the analysed error covariance given by Kalman filter in cases when the correction is small; without perturbed observations. The proposed filter is based on the recognition that in the case of small corrections to the forecast the traditional EnKF without perturbed observations reduces the forecast error covariance by an amount that is nearly twice as large as that is needed to match Kalman filter. The analysis scheme works as follows: update the ensemble mean and the ensemble anomalies separately; update the mean using the standard analysis equation; update the anomalies with the same equation but half the Kalman gain. The proposed filter is shown to be a linear approximation to the ensemble square root filter (ESRF). Because of its deterministic character and its similarity to the traditional EnKF we call it the ‘deterministic EnKF’, or the DEnKF. A number of numerical experiments to compare the performance of the DEnKF with both the EnKF and an ESRF using three small models are conducted. We show that the DEnKF performs almost as well as the ESRF and is a significant improvement over the EnKF. Therefore, the DEnKF combines the numerical effectiveness, simplicity and versatility of the EnKF with the performance of the ESRFs. Importantly, the DEnKF readily permits the use of the traditional Schur product-based localization schemes.

User interface and method to facilitate hierarchical specification of queries using an information taxonomy

Abstract: A user interface, system, and method are disclosed to facilitate specification of queries and displaying corresponding results. The user interface presents the user with dimensions that contain one or more headings arranged according to an information taxonomy, which can vary based on the intended implementation for the system and user interface. A corresponding filter or query is constructed based on the user selecting of one or more headings. The filter is applied to one or more databases to return results that satisfy the filter. The results are presented in the user interface and can include interactive items based on a particular query as well as can correspond to a fully specified task.

FPGA Realization of FIR Filters by Efficient and Flexible Systolization Using Distributed Arithmetic

Abstract: In this paper, we present the design optimization of one- and two-dimensional fully pipelined computing structures for area-delay-power-efficient implementation of finite-impulse-response (FIR) filter by systolic decomposition of distributed arithmetic (DA)-based inner-product computation. The systolic decomposition scheme is found to offer a flexible choice of the address length of the lookup tables (LUT) for DA-based computation to decide on suitable area time tradeoff. It is observed that by using smaller address lengths for DA-based computing units, it is possible to reduce the memory size, but on the other hand that leads to increase of adder complexity and the latency. For efficient DA-based realization of FIR filters of different orders, the flexible linear systolic design is implemented on a Xilinx Virtex-E XCV2000E FPGA using a hybrid combination of Handel-C and parameterizable VHDL cores. Various key performance metrics such as number of slices, maximum usable frequency, dynamic power consumption, energy density, and energy throughput are estimated for different filter orders and address lengths. Analysis of the results obtained indicate that performance metrics of the proposed implementation is broadly in line with theoretical expectations. It is found that the choice of address length yields the best of area-delay-power-efficient realizations of the FIR filter for various filter orders. Moreover, the proposed FPGA implementation is found to involve significantly less area-delay complexity compared with the existing DA-based implementations of FIR filter.

Frequency-domain passivity-based current controller design

Abstract: Current controller design for three-phase voltage-source converters, by which a passive input admittance is ideally obtained, is considered. Two design alternatives, with and without voltage feedforward, respectively, are shown to give similar performance. It is demonstrated how additional parts can be added to the controller while preserving the passivity property. This is applied particularly to resonant parts. The design method is finally applied to converters with an LCL input filter, where it is shown in many cases to compare favourably with a scheme where an inner loop is added for improved damping of the LCL resonance.

FlexiTaint: A programmable accelerator for dynamic taint propagation

Abstract: This paper presents FlexiTaint, a hardware accelerator for dynamic taint propagation. FlexiTaint is implemented as an in-order addition to the back-end of the processor pipeline, and the taints for memory locations are stored as a packed array in regular memory. The taint propagation scheme is specified via a software handler that, given the operation and the sourcespsila taints, computes the new taint for the result. To keep performance overheads low, FlexiTaint caches recent taint propagation lookups and uses a filter to avoid lookups for simple common-case behavior. We also describe how to implement consistent taint propagation in a multi-core environment. Our experiments show that FlexiTaint incurs average performance overheads of only 1% for SPEC2000 benchmarks and 3.7% for Splash-2 benchmarks, even when simultaneously following two different taint propagation policies.

A Continuous-Time ADC/DSP/DAC System With No Clock and With Activity-Dependent Power Dissipation

Abstract: A continuous-time system that converts its analog input to a continuous-time digital representation without sampling, then processes the information digitally without the aid of a clock, is presented. Without sampling there is no aliasing, which reduces the in-band distortion power by not aliasing into band out-of-band distortion components. The 8-bit system, fabricated in a 90 nm CMOS process, utilizes continuous delay elements as part of a programmable transversal FIR filter. The input is encoded by a delta modulator without a clock into a series of non-uniformly spaced tokens, which are processed by the digital continuous-time filter and converted to an analog output using a custom DAC that guarantees there are no glitches in the output waveform. All activity is signal driven, automatically affording dynamic power scaling that tracks input activity.

Design of Novel Dual-Band Bandpass Filter with Microstrip Meander-Loop Resonator and CSRR DGS

Abstract: A novel dual-band bandpass filter with meander-loop resonator and complement split-ring resonator (CSRR) defected ground structure (DGS) is proposed in this letter. Microstrip meanderloop resonator and CSRR DGS are operated for respective passbands. Several finite attenuation poles in stopbands are realized to improve the selectivity of the proposed bandpass filter and isolation between the two passbands. Compact size, dual band and high selectivity characteristics are realized by this type of filter structure. The filter is evaluated by experiment and simulation with very good agreement.

The design of an optimal filter for monthly GRACE gravity models

Abstract: SUMMARY Most applications of the publicly released Gravity Recovery and Climate Experiment monthly gravity field models require the application of a spatial filter to help suppressing noise and other systematic errors present in the data The most common approach makes use of a simple Gaussian averaging process, which is often combined with a ‘destriping’ technique in which coefficient correlations within a given degree are removed As brute force methods, neither of these techniques takes into consideration the statistical information from the gravity solution itself and, while they perform well overall, they can often end up removing more signal than necessary Other optimal filters have been proposed in the literature; however, none have attempted to make full use of all information available from the monthly solutions By examining the underlying principles of filter design, a filter has been developed that incorporates the noise and full signal variance–covariance matrix to tailor the filter to the error characteristics of a particular monthly solution The filter is both anisotropic and nonsymmetric, meaning it can accommodate noise of an arbitrary shape, such as the characteristic stripes The filter minimizes the mean-square error and, in this sense, can be considered as the most optimal filter possible Through both simulated and real data scenarios, this improved filter will be shown to preserve the highest amount of gravity signal when compared to other standard techniques, while simultaneously minimizing leakage effects and producing smooth solutions in areas of low signal

Bulk acoustic wave RF technology

Abstract: In this article, we will provide an overview of BAW filter technology by discussing comparison between BAW and SAW RF filter technologies, working principles of BAW resonator and filter, BAW resonator key performance parameters, comparison between free-standing bulk acoustic resonator (FBAR) and solidly mounted resonator (SMR) technologies, status of BAW resonator design and models, BAW filter manufacturing challenges, and future BAW technology improvement directions.

Modeling the Effect of Voltage Ripple on the Power Output of Photovoltaic Modules

Abstract: This paper proposes a model for the static power loss in photovoltaic (PV) panels due to switching-frequency ripple. Small-signal modeling is used to determine the amplitude of the voltage ripple that is imposed on the PV panel, and a closed-form expression is developed for the output power. The expression is shown to be more accurate than the power loss that was predicted by small-signal modeling alone, resulting in a median error of 0.8%. The model presented allows dc-dc converter designers to more precisely choose the input filter components that are critical during times of low insolation.

Salt-and-pepper noise detection and reduction using fuzzy switching median filter

Abstract: This paper presents a new fuzzy switching median (FSM) filter employing fuzzy techniques in image processing. The proposed filter is able to remove salt-and-pepper noise in digital images while preserving image details and textures very well. By incorporating fuzzy reasoning in correcting the detected noisy pixel, the low complexity FSM filter is able to outperform some well known existing salt-and-pepper noise fuzzy and classical filters.

Ambient noise reduction system

Abstract: An adaptive, feed-forward, ambient noise-reduction system includes a reference microphone for generating first electrical signals representing incoming ambient noise, and a connection path including a circuit for inverting these signals and applying them to a loudspeaker directed into the ear of a user. The system also includes an error microphone for generating second electrical signals representative of sound (including that generated by the loudspeaker in response to the inverted first electrical signals) approaching the user's ear. An adaptive electronic filter is provided in the connection path, together with a controller for automatically adjusting one or more characteristics of the filter in response to the first and second electrical signals. The system is configured to constrain the operation of the adaptive filter such that it always conforms to one of a predetermined family of filter responses, thereby restricting the filter to operation within a predetermined and limited set of amplitude and phase characteristics.

A Modified CFOA and Its Applications to Simulated Inductors, Capacitance Multipliers, and Analog Filters

Abstract: In this paper, using a minimum number of passive components, i.e., new grounded and floating inductance simulators, grounded capacitance multipliers, and frequency-dependent negative resistors (FDNRs) based on one/two modified current-feedback operational amplifiers (MCFOAs), are proposed. The type of the simulators depends on the passive element selection used in the structure of the circuit without requiring critical active and passive component-matching conditions and/or cancellation constraints. In order to show the flexibility of the proposed MCFOA, a single-input three-output (SITO) voltage-mode (VM) filter, two three-input single-output (TISO) VM filters, and an SITO current-mode (CM) filter employing a single MCFOA are reported. The layout of the proposed MCFOA is also given. A number of simulations using the SPICE program and some experimental tests are performed to exhibit the performance of the introduced structures.

Implementation of Compact UWB Bandpass Filter With a Notch-Band

Abstract: An ultra-wideband (UWB) bandpass filter on microstrip line with notch-band, compact-size and improved upper-stopband performances is presented and implemented. A modified non-uniform resonator is at first formed by transversely attaching three pairs of impedance-stepped stubs. Its resonance behavior is thoroughly characterized so as to allocate the first three resonant frequencies within 3.1-10.6 GHz band while suppressing spurious harmonics in the upper-band. As this resonator is linked at two sides with two feed lines via interdigital coupled lines with enhanced coupling degree, a preferred UWB passband is realized. Then, one of two arms in the coupled-line sections is largely extended and folded, aiming to create a notch band at the frequency of 5.6 GHz by virtue of out-of-phase transmission cancellation. Two filter prototypes are optimized and fabricated to demonstrate the notch-band-included and upper-stopband-improved UWB bandpass performances.

A New Approximate Solution of the Optimal Nonlinear Filter for Data Assimilation in Meteorology and Oceanography

Abstract: This paper introduces a new approximate solution of the optimal nonlinear filter suitable for nonlinear oceanic and atmospheric data assimilation problems. The method is based on a local linearization in a low-rank kernel representation of the state's probability density function. In the resulting low-rank kernel particle Kalman (LRKPK) filter, the standard (weight type) particle filter correction is complemented by a Kalman-type correction for each particle using the covariance matrix of the kernel mixture. The LRKPK filter's solution is then obtained as the weighted average of several low-rank square root Kalman filters operating in parallel. The Kalman-type correction reduces the risk of ensemble degeneracy, which enables the filter to efficiently operate with fewer particles than the particle filter. Combined with the low-rank approximation, it allows the implementation of the LRKPK filter with high-dimensional oceanic and atmospheric systems. The new filter is described and its relevance demonstrated through applications with the simple Lorenz model and a realistic configuration of the Princeton Ocean Model (POM) in the Mediterranean Sea.