Human detection has recently received significant attention in the field of computer vision. Accurate detection of human bodies is an essential component required by a variety of applications such as automated surveil...
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Images acquired by remote sensing contain radiometric errors caused by variations in the sensor response. In this note, we present a unified treatment of the correction of periodic or nonperiodic errors, which provide...
Images acquired by remote sensing contain radiometric errors caused by variations in the sensor response. In this note, we present a unified treatment of the correction of periodic or nonperiodic errors, which provides some insight into the relation of correction algorithms to the type of radiometric degradation. Successful correction of a NOAA Very High Resolution Radiometer (VHRR) thermal infrared image is demonstrated.
Directional or Circular statistics are pertaining to the analysis and interpretation of directions or rotations. In this work, a novel probability distribution is proposed to model multidimensional sparse directional ...
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Directional or Circular statistics are pertaining to the analysis and interpretation of directions or rotations. In this work, a novel probability distribution is proposed to model multidimensional sparse directional data. The Generalized Directional Laplacian Distribution (DLD) is a hybrid between the Laplacian distribution and the von Mises-Fisher distribution. The distribution's parameters are estimated using Maximum-Likelihood Estimation over a set of training data points. Mixtures of Directional Laplacian Distributions (MDLD) are also introduced in order to model multiple concentrations of sparse directional data. The author explores the application of the derived DLD mixture model to cluster sound sources that exist in an underdetermined instantaneous sound mixture. The proposed model can solve the general K × L (K
Stable consumer electronic systems can assist traffic better. Good traffic consumer electronic systems require collaborative work between traffic algorithms and hardware. However, performance of popular traffic algori...
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The mean-squared-error measure of quality is used as a basis for a general nearest prototype signal-classification methodology. Canonical signal features for this methodology are identified. A consistency requirement ...
The mean-squared-error measure of quality is used as a basis for a general nearest prototype signal-classification methodology. Canonical signal features for this methodology are identified. A consistency requirement is proposed and used to develop a general approach for determining appropriate class prototypes in discriminant space. It is shown that the class indicator, which is a commonly used class prototype in pattern recognition applications, will often violate the consistency requirement. The general results are used to obtain a solution to a previously posed complexity-performance trade-off problem for matched-filter-tapped-delay-line receivers for serial signal classification in an M -ary data transmission system.
The adaptive adjustment algorithm for a prior art recursive-like noise canceller must incorporate a constraint that prevents convergence to the useless trivial solution. This constraint can also prevent convergence to...
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The adaptive adjustment algorithm for a prior art recursive-like noise canceller must incorporate a constraint that prevents convergence to the useless trivial solution. This constraint can also prevent convergence to the best attainable solution. An alternative to the prior-art hard-constrained recursive-like canceller, that "softens" the constraint by making it adaptive, is proposed.
An approach to the realization of a recursive-like adaptive noise canceller that employs only nonrecursive adaptive filters is presented. This approach is an alternative to prior art that has the advantage of guarante...
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An approach to the realization of a recursive-like adaptive noise canceller that employs only nonrecursive adaptive filters is presented. This approach is an alternative to prior art that has the advantage of guaranteed stability, but the disadvantage of residual signal distortion.
Two-stage noise cancellation is a recently introduced technique for cancelling noise while maintaining minimal signal distortion due to signal leakage into the noise reference. An alternative three-stage approach to n...
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Two-stage noise cancellation is a recently introduced technique for cancelling noise while maintaining minimal signal distortion due to signal leakage into the noise reference. An alternative three-stage approach to noise cancellation that extends applicability from intermittent or slowly fluctuating signals to arbitrary signals is presented. This alternative is viable whenever the signal source is accessible so that a pilot signal can be additively embedded.
Many speech enhancement algorithms that deal with noise reduction are based on a binary masking decision(termed as the hard decision), which may cause some regions of the synthesized speech to be discarded. In view of...
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Many speech enhancement algorithms that deal with noise reduction are based on a binary masking decision(termed as the hard decision), which may cause some regions of the synthesized speech to be discarded. In view of the problem, a soft decision is often used as an optimal technique for speech restoration. In this paper, considering a new fashion of speech and noise models, we present two model-based soft decision techniques. One technique estimates a ratio mask generated by the exact Bayesian estimators of speech and noise. For the second technique, we consider one issue that an optimum local criterion(LC) for a certain SNR may not be appropriate for other SNRs. So we estimate a probabilistic mask with a variable LC. Experimental results show that the proposed method achieves a better performance than reference methods in speech quality.
This paper describes the design and implementation of a hybrid intelligent surveillance system that consists of an embedded system and a personal computer (PC)-based system. The embedded system performs some of the im...
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