Domain-Transformable Sparse Representation for Anomaly Detection in Moving-Camera Videos.

This paper presents a special matrix factorization based on sparse representation that detects anomalies in video sequences generated with moving cameras. Such representation is made by associating the frames of the target video, that is a sequence to be tested for the presence of anomalies, with the frames of an anomaly-free reference video, which is a previously validated sequence. This factorization is done by a sparse coefficient matrix, and any target-video anomaly is encapsulated into a residue term.

Weak Classifier for Density Estimation in Eye Localization and Tracking.

In this paper, we propose a fast weak classifier that can detect and track eyes in video sequences. The approach relies on a least-squares detector based on the inner product detector (IPD) that can stimate a probability density distribution for a feature's location-which fits naturally with a Bayesian estimation cycle, such as a Kalman or particle filter. As a least-squares sliding window detector, it possesses tolerance to small variations in the desired pattern while maintaining good generalization capabilities and computational efficiency.

Image Coding Using Generalized Predictors Based on Sparsity and Geometric Transformations.

Directional intra prediction plays an important role in current state-of-the-art video coding standards. In directional prediction, neighbouring samples are projected along a specific direction to predict a block of samples. Ultimately, each prediction mode can be regarded as a set of very simple linear predictors, a different one for each pixel of a block.

Intra Predictive Depth Map Coding Using Flexible Block Partitioning.

A complete encoding solution for efficient intra-based depth map compression is proposed in this paper. The algorithm, denominated predictive depth coding (PDC), was specifically developed to efficiently represent the characteristics of depth maps, mostly composed by smooth areas delimited by sharp edges. At its core, PDC involves a directional intra prediction framework and a straightforward residue coding method, combined with an optimized flexible block partitioning scheme.

Multiscale image fusion using the undecimated wavelet transform with spectral factorization and nonorthogonal filter banks.

Multiscale transforms are among the most popular techniques in the field of pixel-level image fusion. However, the fusion performance of these methods often deteriorates for images derived from different sensor modalities. In this paper, we demonstrate that for such images, results can be improved using a novel undecimated wavelet transform (UWT)-based fusion scheme, which splits the image decomposition process into two successive filtering operations using spectral factorization of the analysis filters.

Recursive algorithms for bias and gain nonuniformity correction in infrared videos.

Infrared focal-plane array (IRFPA) detectors suffer from fixed-pattern noise (FPN) that degrades image quality, which is also known as spatial nonuniformity. FPN is still a serious problem, despite recent advances in IRFPA technology. This paper proposes new scene-based correction algorithms for continuous compensation of bias and gain nonuniformity in FPA sensors.

Production of lactobionic acid and sorbitol from lactose/fructose substrate using GFOR/GL enzymes from Zymomonas mobilis cells: a kinetic study.

In this work, we have investigated the kinetics of the biotechnological production of lactobionic acid (LBA) and sorbitol by the catalytic action of glucose-fructose oxidoreductase (GFOR) and glucono-δ-lactonase (GL) enzymes. The cells of bacterium Zymomonas mobilis ATCC 29191 containing this enzymatic complex were submitted to permeabilization and reticulation procedures. The effect of the concentration of substrates on the rate of product formation using a mobilized cell system was investigated.

No-reference blur assessment of digital pictures based on multifeature classifiers.

In this paper, we address the problem of no-reference quality assessment for digital pictures corrupted with blur. We start with the generation of a large real image database containing pictures taken by human users in a variety of situations, and the conduction of subjective tests to generate the ground truth associated to those images. Based upon this ground truth, we select a number of high quality pictures and artificially degrade them with different intensities of simulated blur (gaussian and linear motion), totalling 6000 simulated blur images.

Application of the Nernst-Planck approach to lead ion exchange in Ca-loaded Pelvetia canaliculata.

Ca-loaded Pelvetia canaliculata biomass was used to remove Pb(2+) in aqueous solution from batch and continuous systems. The physicochemical characterization of algae Pelvetia particles by potentiometric titration and FTIR analysis has shown a gel structure with two major binding groups - carboxylic (2.8 mmol g(-1)) and hydroxyl (0.

Scanned compound document encoding using multiscale recurrent patterns.

In this paper, we propose a new encoder for scanned compound documents, based upon a recently introduced coding paradigm called multidimensional multiscale parser (MMP). MMP uses approximate pattern matching, with adaptive multiscale dictionaries that contain concatenations of scaled versions of previously encoded image blocks. These features give MMP the ability to adjust to the input image's characteristics, resulting in high coding efficiencies for a wide range of image types.

On ECG signal compression with 1-D multiscale recurrent patterns allied to preprocessing techniques.

This paper presents the results of a multiscale pattern-matching-based ECG encoder, which employs simple preprocessing techniques for adapting the input signal. Experiments carried out with records from the Massachusetts Institute of Technology-Beth Israel Hospital database show that the proposed scheme is effective, outperforming some state-of-the-art schemes described in the literature.

On dictionary adaptation for recurrent pattern image coding.

In this paper, we exploit a recently introduced coding algorithm called multidimensional multiscale parser (MMP) as an alternative to the traditional transform quantization-based methods. MMP uses approximate pattern matching with adaptive multiscale dictionaries that contain concatenations of scaled versions of previously encoded image blocks. We propose the use of predictive coding schemes that modify the source's probability distribution, in order to favour the efficiency of MMP's dictionary adaptation.

ECG signal compression based on Dc equalization and complexity sorting.

In this brief, we present new preprocessing techniques for electrocardiogram signals, namely, dc equalization and complexity sorting, which when applied can improve current 2-D compression algorithms. The experimental results with signals from the Massachusetts Institute of Technology - Beth Israel Hospital (MIT-BIH) database outperform the ones from many state-of-the-art schemes described in the literature.

On EMG signal compression with recurrent patterns.

In this paper, the multidimensional multiscale parser (MMP) is employed for encoding electromyographic signals. The experiments were carried out with real signals acquired in laboratory and show that the proposed scheme is effective, outperforming even wavelet-based state-of-the-art schemes present in the literature in terms of percent root mean square difference x compression ratio.