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Motion errors are inevitably introduced when data are acquired and considerably degrade the image quality in terms of geometric resolution, radiometric accuracy and image contrast, especially in high resolution spotlight synthetic aperture radar (SAR) imagery. In this paper, we describe a weighted contrast enhancement autofocus algorithm that is based on spatially variant model and adopts a mean square...
Biometric gait analysis using wearable sensors offers an objective and quantitative method for gait parameter extraction. However, current techniques are constrained to specific platform parameters, and hence significantly lack generality, scalability and sustainability. In this paper, we propose a platform-independent and self-adaptive approach for gait cycle detection and cadence estimation. Our...
For depth-from-stereo vision applications such as driving assistance and object-size estimation, the accuracy of disparity estimation determines the precision of depth measurement. Conventional dense methods are hard to estimate disparity within a 0.1 pixel precision. In this paper, we present a novel object-based method to achieve robust and deep sub-pixel accurate disparity estimation. In our experimental...
Gaze movements play a crucial role in humancomputer interaction (HCI) applications. Recently, gaze tracking systems with a wide variety of applications have attracted much interest by the industry as well as the scientific community. The state-of-the-art gaze trackers are mostly non-intrusive and report high estimation accuracies. However, they require complex setups such as camera and geometric calibration...
There has been an exponential growth in brain mapping studies in the past decade using functional MRI (fMRI). Apart from simple fMRI studies from a single site (scanner), multi-site studies are gaining great attention, as it has the potential to provide more data for brain mapping studies, thereby increasing the statistical power of the brain mapping studies. Major limitations with the multi-center...
Vehicle pose estimation with respect to the road plays a critical role in the advances of autonomous vehicle navigation and guidance. Vision-based road lane line detection provides a feasible and low cost solution as the vehicle pose can be derived from the detection. While good progress has been made, the lane line detection has remained an open one, given challenging road appearances. In this paper,...
By factorizing the A- and B-polynomials in an ARMAX model and filtering the input/output data with the appropriate factors, the parameters of the model are estimated in a decoupled fashion. This may improve the robustness of some estimators significantly, e.g., when applied to very stiff systems. Earlier work on these techniques has established both local and global convergence properties of some...
Although a number of speech disorders reflect varying involvement of brain areas, recently published automatic speech analyses have primarily been limited to hypokinetic dysarthria in Parkinson's disease (PD). Therefore, the aim of the present study was to provide an automatic algorithm suitable for the assessment of voice onset time (VOT) in various dysarthria types. Twenty-four PD participants with...
In this paper, we analyze a new class of iterative re-weighted least squares (IRLS) algorithms and their effectiveness in signal recovery from incomplete and inaccurate linear measurements. These methods can be interpreted as the constrained maximum likelihood estimation under a two-state Gaussian scale mixture assumption on the signal. We show that this class of algorithms, which performs exact recovery...
In this paper, we present a robust solution for data reduction in array processing. The purpose is to reduce the computation and improve the performance of applied signal processing algorithms by mapping the data into a lower-dimension beamspace through a transformation. Nulls steering to interference are incorporated into a transformation using the subspace projection technique, and the beamspace...
In this paper, we propose a new estimation method for the time difference of arrival (TDOA) between two microphones with improved accuracy by exploiting higher-order moments. In the proposed method analyzes the steered response power (SRP) of the observed signals after nonlinearly mapped onto a higher-dimensional space. Since the mapping operation enhances the linear independence between different...
When packed loss caused by bit error occurs in the data transmission of IP network, one should retransmit the corrupted data to avoid information loss. However, this will take more damage for those business in which retransmission is difficult to realize or will limit the performance of system. In order to reduce this damage, this paper studied the checksum restriction mechanism of the IPv4 header...
In rough set approaches, decision rules are induced from a given data table showing the relation between attribute values and classes of objects. The induced decision rules are used for the classification of new objects by their attribute values. However, some of new objects do not match any decision rule conditions because the given data table does not always include all possible patterns. In those...
This paper proposes a new Wi-Fi based indoor positioning method that is robust over unstable Wi-Fi access points (APs). Because Wi-Fi based indoor positioning relies on unstable and uncontrollable infrastructure (Wi-Fi APs), the positioning performance significantly decreases when such unstable APs are included in the localization system. This paper proposes a indoor positioning method by employing...
Depth from Defocus (DFD) is known as the technology which is able to estimate depth in the scene by a monocular camera without any additive devices. Using this advantage of DFD, we improved the speed of Auto Focus (AF). To apply DFD to AF, it is necessary to capture 2 images that have a small amount of “difference in focal positions” (we call DiFP). In this paper, we show the performance of the depth...
Stereo confidence measures are one of the most popular research topics in stereo vision. These measures give an indication about the certainty of the matching. The main aim of using confidence measures is to filter the erroneous disparity estimations at the end of the matching process. However, they can also be incorporated at the initial step of the matching process to obtain accurate estimations...
Methods based on Local Binary Patterns have been used successfully in a wide range of texture classification tasks. A restriction shared by all methods based on Local Binary Patterns is the high sensitivity to signal scale. In recent work we presented a general framework for scale-adaptive computation of Local Binary Patterns, improving the accuracy in texture classification scenarios involving varying...
Skew estimation is a preprocessing step in document image analysis to determine the global dominant orientation of a document's text lines. A skew angle can be introduced during scanning, or if a document is photographed. The correction of the skew angle is necessary for further image analysis, to avoid an influence to the performance of skew sensitive methods, e.g. Optical Character Recognition (OCR)...
A new modification of the popular finite-time-convergent robust exact sliding-mode-based differentiator is proposed. Such nth-order differentiator provides for the fast global convergence of its outputs to the first n exact derivatives of its input, provided a time-variable local Lipschitz constant of the input's nth derivative is available and has a bounded logarithmic derivative. It features the...
Linear discriminant analysis (LDA) is the most commonly used classification method for single trial data in a brain-computer interface (BCI) framework. The popularity of LDA arises from its robustness, simplicity and high accuracy. However, the standard LDA approach is not capable to exploit sublabel information (such as stimulus identity), which is accessible in data from event related potentials...
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