Online learning and fusion of orientation appearance models for robust rigid object tracking

We present a robust framework for learning and fusing different modalities for rigid object tracking. Our method fuses data obtained from a standard visual camera and dense depth maps obtained by low-cost consumer depths cameras such as the Kinect. To combine these two completely different modalities, we propose to use features that do not depend on the data representation: angles. More specifically, our method combines image gradient orientations as extracted from intensity images with the directions of surface normal computed from dense depth fields provided by the Kinect. To incorporate these features in a learning framework, we use a robust kernel based on the Euler representation of angles. This kernel enables us to cope with gross measurement errors, missing data as well as typical problems in visual tracking such as illumination changes and occlusions. Additionally, the employed kernel can be efficiently implemented online. Finally, we propose to capture the correlations between the obtained orientation appearance models using a fusion approach motivated by the original AAM. Thus the proposed learning and fusing framework is robust, exact, computationally efficient and does not require off-line training. By combining the proposed models with a particle filter, the proposed tracking framework achieved robust performance in very difficult tracking scenarios including extreme pose variations

The Effect of Crude Oil Price Moments on Socially Responsible Firms in Eurozone

The present study examines the effect of moments of crude oil prices including the variance, skewness and kurtosis, on the returns of the Dow Jones Sustainability Index (DJSI) of the Eurozone. The GARCH model is employed to examine the relationship of these moments with the DJSI of the Eurozone, for the time period from November 2001 until March 2015. According to our findings, an increase in the oil returns, as well as in the oil price volatility, leads to a decrease in the value of the Index employed. It was also found that asymmetry affects positively the stock price of the Eurozone social responsibility companies, because the more the asymmetry increases, the less the concentration of the prices to the right side of the distribution, consequently the more the investors feel that the related risk is reduced, as the frequency of oil prices is below the average oil price. On the contrary, it was found that the interaction of asymmetry and kurtosis of oil prices affect negatively the DJSI of the Eurozone, a fact that is attributed to the kind of the oil price distribution for the above mentioned time period.   Keywords: Volatility; Stock Exchange Market; GARCH model; Eurozone Dow Jones Sustainability Index JEL Classifications: C58, Q40, Q50, M2

Bidirectional relighting for 3D-aided 2D face recognition

In this paper, we present a new method for bidirectional relighting for 3D-aided 2D face recognition under large pose and illumination changes. During subject enrollment, we build subject-specific 3D annotated models by using the subjects' raw 3D data and 2D texture. During authentication, the probe 2D images are projected onto a normalized image space using the subject-specific 3D model in the gallery. Then, a bidirectional relighting algorithm and two similarity metrics (a view-dependent complex wavelet structural similarity and a global similarity) are employed to compare the gallery and probe. We tested our algorithms on the UHDB11 and UHDB12 databases that contain 3D data with probe images under large lighting and pose variations. The experimental results show the robustness of our approach in recognizing faces in difficult situations

Online learning and fusion of orientation appearance models for robust rigid object tracking

We introduce a robust framework for learning and fusing of orientation appearance models based on both texture and depth information for rigid object tracking. Our framework fuses data obtained from a standard visual camera and dense depth maps obtained by low-cost consumer depth cameras such as the Kinect. To combine these two completely different modalities, we propose to use features that do not depend on the data representation: angles. More specifically, our framework combines image gradient orientations as extracted from intensity images with the directions of surface normals computed from dense depth fields. We propose to capture the correlations between the obtained orientation appearance models using a fusion approach motivated by the original Active Appearance Models (AAMs). To incorporate these features in a learning framework, we use a robust kernel based on the Euler representation of angles which does not require off-line training, and can be efficiently implemented online. The robustness of learning from orientation appearance models is presented both theoretically and experimentally in this work. This kernel enables us to cope with gross measurement errors, missing data as well as other typical problems such as illumination changes and occlusions. By combining the proposed models with a particle filter, the proposed framework was used for performing 2D plus 3D rigid object tracking, achieving robust performance in very difficult tracking scenarios including extreme pose variations. © 2014 Elsevier B.V. All rights reserved

Mediterranean White Lupin Landraces as a Valuable Genetic Reserve for Breeding

Legumes crops are important for sustainable agriculture and global food security. Among them white lupin (Lupinus albus L.), is characterized by exceptional protein content of high nutritional value, competitive to that of soybean (Glycine max) and is well adapted to rainfed agriculture. However, its high seed-quinolizidine alkaloid (QA) content impedes its direct integration to human diet and animal feed. Additionally, its cultivation is not yet intensive, remains confined to local communities and marginal lands in Mediterranean agriculture, while adaptation to local microclimates restrains its cultivation from expanding globally. Hence, modern white lupin breeding aims to exploit genetic resources for the development of “sweet” elite cultivars, resilient to biotic adversities and well adapted for cultivation on a global level. Towards this aim, we evaluated white lupin local landrace germplasm from Greece, since the country is considered a center of white lupin diversity, along with cultivars and breeding lines for comparison. Seed morphological diversity and molecular genetic relationships were investigated. Most of the landraces were distinct from cultivars, indicating the uniqueness of their genetic make-up. The presence of pauper “sweet” marker allele linked to low seed QA content in some varieties was detected in one landrace, two breeding lines, and the cultivars. However, QA content in the examined genotypes did not relate with the marker profile, indicating that the marker’s predictive power is limited in this material. Marker alleles for vernalization unresponsiveness were detected in eight landraces and alleles for anthracnose resistance were found in two landraces, pointing to the presence of promising germplasm for utilization in white lupin breeding. The rich lupin local germplasm genetic diversity and the distinct genotypic composition compared to elite cultivars, highlights its potential use as a source of important agronomic traits to support current breeding efforts and assist its integration to modern sustainable agriculture

Adsorption/Desorption Patterns of Selenium for Acid and Alkaline Soils of Xerothermic Environments

Selenium adsorption/desorption behavior was examined for eight Greek top soils with different properties, aiming to describe the geochemistry of the elements in the selected soils in terms of bioavailability and contamination risk by leaching. Four soils were acid and four alkaline, and metal oxides content greatly differed between the two groups of soils. The concentrations of Se(IV) used for the performed adsorption batch experiments ranged from 1 to 50 mg/L, while the soil to solution ratio was 1 g/0.03 L. Acid soils adsorbed significantly higher amounts of the added Se(IV) than alkaline soils. Freundlich and Langmuir equations adequately described the adsorption of Se(IV) in the studied soils, and the parameters of both isotherms significantly correlated with soil properties. In particular, both KF and qm values significantly positively correlated with ammonium oxalate extractable Fe and with dithionite extractable Al and Mn, suggesting that amorphous Fe oxides and Al and Mn oxides greatly affect exogenous Se(IV) adsorption in the eight soils. These two parameters were also significantly negatively correlated with soil electrical conductivity (EC) values, indicating that increased soluble salts concentration suppresses Se(IV) adsorption. No significant relation between adsorbed Se(IV) and soil organic content was recorded. A weak salt (0.25 M KCl) was used at the same soil to solution ratio to extract the amount of the adsorbed Se(IV) that is easily exchangeable and thus highly available in the soil ecosystem. A much higher Se(IV) desorption from alkaline soils was observed, pointing to the stronger retention of added Se(IV) by the acid soils. This result implies that in acid soils surface complexes on metal oxides may have been formed restricting Se desorption